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Sample records for pricing schedule based

  1. An EV Charging Scheduling Mechanism Based on Price Negotiation

    Directory of Open Access Journals (Sweden)

    Baocheng Wang

    2018-05-01

    Full Text Available Scheduling EV user’s charging behavior based on charging price and applying renewable energy resources are the effective methods to release the load pressure of power grids brought about by the large-scale popularity of electric vehicles (EVs. This paper presents a novel approach for EV charging scheduling based on price negotiation. Firstly, the EV charging system framework based on price negotiation and renewable energy resources is discussed. Secondly, the price negotiation model is presented, including the initial price models and the conditions of transactions. Finally, an EV charging scheduling mechanism based on price negotiation (CSM-PN, including the price adjustment strategies of both the operator and EV users is proposed to seek a final transaction during multi-round price negotiation. Simulation results show that this novel approach can effectively improve the charging station operator’s income, reduce the EV users’ costs, and balance the load of the power grid while improving the efficiency of the EV charging system.

  2. Robust Optimization-Based Generation Self-Scheduling under Uncertain Price

    Directory of Open Access Journals (Sweden)

    Xiao Luo

    2011-01-01

    Full Text Available This paper considers generation self-scheduling in electricity markets under uncertain price. Based on the robust optimization (denoted as RO methodology, a new self-scheduling model, which has a complicated max-min optimization structure, is set up. By using optimal dual theory, the proposed model is reformulated to an ordinary quadratic and quadratic cone programming problems in the cases of box and ellipsoidal uncertainty, respectively. IEEE 30-bus system is used to test the new model. Some comparisons with other methods are done, and the sensitivity with respect to the uncertain set is analyzed. Comparing with the existed uncertain self-scheduling approaches, the new method has twofold characteristics. First, it does not need a prediction of distribution of random variables and just requires an estimated value and the uncertain set of power price. Second, the counterpart of RO corresponding to the self-scheduling is a simple quadratic or quadratic cone programming. This indicates that the reformulated problem can be solved by many ordinary optimization algorithms.

  3. Real-Time Pricing-Based Scheduling Strategy in Smart Grids: A Hierarchical Game Approach

    Directory of Open Access Journals (Sweden)

    Jie Yang

    2014-01-01

    Full Text Available This paper proposes a scheduling strategy based on real-time pricing in smart grids. A hierarchical game is employed to analyze the decision-making process of generators and consumers. We prove the existence and uniqueness of Nash equilibrium and utilize a backward induction method to obtain the generation and consumption strategies. Then, we propose two dynamic algorithms for the generators and consumers to search for the equilibrium in a distributed fashion. Simulation results demonstrate that the proposed scheduling strategy can match supply with demand and shift load away from peak time.

  4. Generation and Demand Scheduling for a Grid-Connected Hybrid Microgrid Considering Price-based Incentives

    DEFF Research Database (Denmark)

    Hernández, Adriana Carolina Luna; Aldana, Nelson Leonardo Diaz; Savaghebi, Mehdi

    2017-01-01

    Microgrids rely on energy management levels to optimally schedule their components. Conventionally, the research in this field has been focused on the optimal formulation of the generation or the demand side management separately without considering real case scenarios and validated only...... by simulation. This paper presents the power scheduling of a real site microgrid under a price-based demand response program defined in Shanghai, China managing generation and demand simultaneously. The proposed optimization problem aims to minimize operating cost by managing renewable energy sources as well...

  5. The impact of alternative pricing methods for drugs in California Workers' Compensation System: Fee-schedule pricing.

    Science.gov (United States)

    Wilson, Leslie; Turkistani, Fatema A; Huang, Wei; Tran, Dang M; Lin, Tracy Kuo

    2018-01-01

    California's Workers' Compensation System (CAWCS) Department of Industrial Relations questioned the adequacy of the current Medi-Cal fee-schedule pricing and requested analysis of alternatives that maximize price availability and maintain budget neutrality. To compare CAWCS pharmacy-dispensed (PD) drug prices under alternative fee schedules, and identify combinations of alternative benchmarks that have prices available for the largest percentage of PD drugs and that best reach budget neutrality. Claims transaction-level data (2011-2013) from CAWCS were used to estimate total annual PD pharmaceutical payments. Medi-Cal pricing data was from the Workman's Compensation Insurance System (WCIS). Average Wholesale Prices (AWP), Wholesale Acquisition Costs (WAC), Direct Prices (DP), Federal Upper Limit (FUL) prices, and National Average Drug Acquisition Costs (NADAC) were from Medi-Span. We matched National Drug Codes (NDCs), pricing dates, and drug quantity for comparisons. We report pharmacy-dispensed (PD) claims frequency, reimbursement matching rate, and paid costs by CAWCS as the reference price against all alternative price benchmarks. Of 12,529,977 CAWCS claims for pharmaceutical products 11.6% (1,462,814) were for PD drugs. Prescription drug cost for CAWCS was over $152M; $63.9M, $47.9M, and $40.6M in 2011-2013. Ninety seven percent of these CAWCS PD claims had a Medi-Cal price. Alternative mechanisms provided a price for fewer claims; NADAC 94.23%, AWP 90.94%, FUL 73.11%, WAC 66.98%, and DP 14.33%. Among CAWCS drugs with no Medi-Cal price in PD claims, AWP, WAC, NADAC, DP, and FUL provided prices for 96.7%, 63.14%, 24.82%, 20.83%, and 15.08% of claims. Overall CAWCS paid 100.52% of Medi-Cal, 60% of AWP, 97% of WAC, 309.53% of FUL, 103.83% of DP, and 136.27% of NADAC. CAWCS current Medi-Cal fee-schedule price list for PD drugs is more complete than all alternative fee-schedules. However, all reimbursement approaches would require combinations of pricing benchmarks

  6. The impact of alternative pricing methods for drugs in California Workers’ Compensation System: Fee-schedule pricing

    Science.gov (United States)

    Wilson, Leslie; Turkistani, Fatema A.; Huang, Wei; Tran, Dang M.; Lin, Tracy Kuo

    2018-01-01

    Introduction California’s Workers’ Compensation System (CAWCS) Department of Industrial Relations questioned the adequacy of the current Medi-Cal fee-schedule pricing and requested analysis of alternatives that maximize price availability and maintain budget neutrality. Objectives To compare CAWCS pharmacy-dispensed (PD) drug prices under alternative fee schedules, and identify combinations of alternative benchmarks that have prices available for the largest percentage of PD drugs and that best reach budget neutrality. Methods Claims transaction-level data (2011–2013) from CAWCS were used to estimate total annual PD pharmaceutical payments. Medi-Cal pricing data was from the Workman’s Compensation Insurance System (WCIS). Average Wholesale Prices (AWP), Wholesale Acquisition Costs (WAC), Direct Prices (DP), Federal Upper Limit (FUL) prices, and National Average Drug Acquisition Costs (NADAC) were from Medi-Span. We matched National Drug Codes (NDCs), pricing dates, and drug quantity for comparisons. We report pharmacy-dispensed (PD) claims frequency, reimbursement matching rate, and paid costs by CAWCS as the reference price against all alternative price benchmarks. Results Of 12,529,977 CAWCS claims for pharmaceutical products 11.6% (1,462,814) were for PD drugs. Prescription drug cost for CAWCS was over $152M; $63.9M, $47.9M, and $40.6M in 2011–2013. Ninety seven percent of these CAWCS PD claims had a Medi-Cal price. Alternative mechanisms provided a price for fewer claims; NADAC 94.23%, AWP 90.94%, FUL 73.11%, WAC 66.98%, and DP 14.33%. Among CAWCS drugs with no Medi-Cal price in PD claims, AWP, WAC, NADAC, DP, and FUL provided prices for 96.7%, 63.14%, 24.82%, 20.83%, and 15.08% of claims. Overall CAWCS paid 100.52% of Medi-Cal, 60% of AWP, 97% of WAC, 309.53% of FUL, 103.83% of DP, and 136.27% of NADAC. Conclusions CAWCS current Medi-Cal fee-schedule price list for PD drugs is more complete than all alternative fee-schedules. However, all

  7. Heterogeneous Effects of a Nonlinear Price Schedule for Outpatient Care.

    Science.gov (United States)

    Farbmacher, Helmut; Ihle, Peter; Schubert, Ingrid; Winter, Joachim; Wuppermann, Amelie

    2017-10-01

    Nonlinear price schedules generally have heterogeneous effects on health-care demand. We develop and apply a finite mixture bivariate probit model to analyze whether there are heterogeneous reactions to the introduction of a nonlinear price schedule in the German statutory health insurance system. In administrative insurance claims data from the largest German health insurance plan, we find that some individuals strongly react to the new price schedule while a second group of individuals does not react. Post-estimation analyses reveal that the group of the individuals who do not react to the reform includes the relatively sick. These results are in line with forward-looking behavior: Individuals who are already sick expect that they will hit the kink in the price schedule and thus are less sensitive to the co-payment. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  8. Entity’s Irregular Demand Scheduling of the Wholesale Electricity Market based on the Forecast of Hourly Price Ratios

    Directory of Open Access Journals (Sweden)

    O. V. Russkov

    2015-01-01

    Full Text Available The article considers a hot issue to forecast electric power demand amounts and prices for the entities of wholesale electricity market (WEM, which are in capacity of a large user with production technology requirements prevailing over hourly energy planning ones. An electric power demand of such entities is on irregular schedule. The article analyses mathematical models, currently applied to forecast demand amounts and prices. It describes limits of time-series models and fundamental ones in case of hourly forecasting an irregular demand schedule of the electricity market entity. The features of electricity trading at WEM are carefully analysed. Factors that influence on irregularity of demand schedule of the metallurgical plant are shown. The article proposes method for the qualitative forecast of market price ratios as a tool to reduce a dependence on the accuracy of forecasting an irregular schedule of demand. It describes the differences between the offered method and the similar ones considered in research studies and scholarly works. The correlation between price ratios and relaxation in the requirements for the forecast accuracy of the electric power consumption is analysed. The efficiency function of forecast method is derived. The article puts an increased focus on description of the mathematical model based on the method of qualitative forecast. It shows main model parameters and restrictions the electricity market imposes on them. The model prototype is described as a programme module. Methods to assess an effectiveness of the proposed forecast model are examined. The positive test results of the model using JSC «Volzhsky Pipe Plant» data are given. A conclusion is drawn concerning the possibility to decrease dependence on the forecast accuracy of irregular schedule of entity’s demand at WEM. The effective trading tool has been found for the entities of irregular demand schedule at WEM. The tool application allows minimizing cost

  9. Resource-Optimal Scheduling Using Priced Timed Automata

    DEFF Research Database (Denmark)

    Larsen, Kim Guldstrand; Rasmussen, Jacob Illum; Subramani, K.

    2004-01-01

    In this paper, we show how the simple structure of the linear programs encountered during symbolic minimum-cost reachability analysis of priced timed automata can be exploited in order to substantially improve the performance of the current algorithm. The idea is rooted in duality of linear......-80 percent performance gain. As a main application area, we show how to solve energy-optimal task graph scheduling problems using the framework of priced timed automata....

  10. Price schedules coordination for electricity pool markets

    Science.gov (United States)

    Legbedji, Alexis Motto

    2002-04-01

    We consider the optimal coordination of a class of mathematical programs with equilibrium constraints, which is formally interpreted as a resource-allocation problem. Many decomposition techniques were proposed to circumvent the difficulty of solving large systems with limited computer resources. The considerable improvement in computer architecture has allowed the solution of large-scale problems with increasing speed. Consequently, interest in decomposition techniques has waned. Nonetheless, there is an important class of applications for which decomposition techniques will still be relevant, among others, distributed systems---the Internet, perhaps, being the most conspicuous example---and competitive economic systems. Conceptually, a competitive economic system is a collection of agents that have similar or different objectives while sharing the same system resources. In theory, constructing a large-scale mathematical program and solving it centrally, using currently available computing power can optimize such systems of agents. In practice, however, because agents are self-interested and not willing to reveal some sensitive corporate data, one cannot solve these kinds of coordination problems by simply maximizing the sum of agent's objective functions with respect to their constraints. An iterative price decomposition or Lagrangian dual method is considered best suited because it can operate with limited information. A price-directed strategy, however, can only work successfully when coordinating or equilibrium prices exist, which is not generally the case when a weak duality is unavoidable. Showing when such prices exist and how to compute them is the main subject of this thesis. Among our results, we show that, if the Lagrangian function of a primal program is additively separable, price schedules coordination may be attained. The prices are Lagrange multipliers, and are also the decision variables of a dual program. In addition, we propose a new form of

  11. Incorporating price-responsive customers in day-ahead scheduling of smart distribution networks

    International Nuclear Information System (INIS)

    Mazidi, Mohammadreza; Monsef, Hassan; Siano, Pierluigi

    2016-01-01

    Highlights: • Proposing a model for incorporating price-responsive customers in day-ahead scheduling of smart distribution networks; this model provides a win–win situation. • Introducing a risk management model based on a bi-level information-gap decision theory and recasting it into its equivalent single-level robust optimization problem using Karush–Kuhn–Tucker optimality conditions. • Utilizing mixed-integer linear programing formulation that is efficiently solved by commercial optimization software. - Abstract: Demand response and real-time pricing of electricity are key factors in a smart grid as they can increase economic efficiency and technical performances of power grids. This paper focuses on incorporating price-responsive customers in day-ahead scheduling of smart distribution networks under a dynamic pricing environment. A novel method is proposed and formulated as a tractable mixed integer linear programming optimization problem whose objective is to find hourly sale prices offered to customers, transactions (purchase/sale) with the wholesale market, commitment of distribution generation units, dispatch of battery energy storage systems and planning of interruptible loads in a way that the profit of the distribution network operator is maximized while customers’ benefit is guaranteed. To hedge distribution network operator against financial risk arising from uncertainty of wholesale market prices, a risk management model based on a bi-level information-gap decision theory is proposed. The proposed bi-level problem is solved by recasting it into its equivalent single-level robust optimization problem using Karush–Kuhn–Tucker optimality conditions. Performance of the proposed model is verified by applying it to a modified version of the IEEE 33-bus distribution test network. Numerical results demonstrate the effectiveness and efficiency of the proposed method.

  12. Estimating the price elasticity of expenditure for prescription drugs in the presence of non-linear price schedules: an illustration from Quebec, Canada.

    Science.gov (United States)

    Contoyannis, Paul; Hurley, Jeremiah; Grootendorst, Paul; Jeon, Sung-Hee; Tamblyn, Robyn

    2005-09-01

    The price elasticity of demand for prescription drugs is a crucial parameter of interest in designing pharmaceutical benefit plans. Estimating the elasticity using micro-data, however, is challenging because insurance coverage that includes deductibles, co-insurance provisions and maximum expenditure limits create a non-linear price schedule, making price endogenous (a function of drug consumption). In this paper we exploit an exogenous change in cost-sharing within the Quebec (Canada) public Pharmacare program to estimate the price elasticity of expenditure for drugs using IV methods. This approach corrects for the endogeneity of price and incorporates the concept of a 'rational' consumer who factors into consumption decisions the price they expect to face at the margin given their expected needs. The IV method is adapted from an approach developed in the public finance literature used to estimate income responses to changes in tax schedules. The instrument is based on the price an individual would face under the new cost-sharing policy if their consumption remained at the pre-policy level. Our preferred specification leads to expenditure elasticities that are in the low range of previous estimates (between -0.12 and -0.16). Naïve OLS estimates are between 1 and 4 times these magnitudes. (c) 2005 John Wiley & Sons, Ltd.

  13. Group Elevator Peak Scheduling Based on Robust Optimization Model

    Directory of Open Access Journals (Sweden)

    ZHANG, J.

    2013-08-01

    Full Text Available Scheduling of Elevator Group Control System (EGCS is a typical combinatorial optimization problem. Uncertain group scheduling under peak traffic flows has become a research focus and difficulty recently. RO (Robust Optimization method is a novel and effective way to deal with uncertain scheduling problem. In this paper, a peak scheduling method based on RO model for multi-elevator system is proposed. The method is immune to the uncertainty of peak traffic flows, optimal scheduling is realized without getting exact numbers of each calling floor's waiting passengers. Specifically, energy-saving oriented multi-objective scheduling price is proposed, RO uncertain peak scheduling model is built to minimize the price. Because RO uncertain model could not be solved directly, RO uncertain model is transformed to RO certain model by elevator scheduling robust counterparts. Because solution space of elevator scheduling is enormous, to solve RO certain model in short time, ant colony solving algorithm for elevator scheduling is proposed. Based on the algorithm, optimal scheduling solutions are found quickly, and group elevators are scheduled according to the solutions. Simulation results show the method could improve scheduling performances effectively in peak pattern. Group elevators' efficient operation is realized by the RO scheduling method.

  14. Optimal household appliances scheduling under day-ahead pricing and load-shaping demand response strategies

    NARCIS (Netherlands)

    Paterakis, N.G.; Erdinç, O.; Bakirtzis, A.G.; Catalao, J.P.S.

    2015-01-01

    In this paper, a detailed home energy management system structure is developed to determine the optimal dayahead appliance scheduling of a smart household under hourly pricing and peak power-limiting (hard and soft power limitation)-based demand response strategies. All types of controllable assets

  15. Optimal scheduling using priced timed automata

    DEFF Research Database (Denmark)

    Behrmann, Gerd; Larsen, Kim Guldstrand; Rasmussen, Jacob Illum

    2005-01-01

    This contribution reports on the considerable effort made recently towards extending and applying well-established timed automata technology to optimal scheduling and planning problems. The effort of the authors in this direction has to a large extent been carried out as part of the European...... projects VHS [20] and AMETIST [16] and are available in the recently released UPPAAL CORA [12], a variant of the real-time verification tool UPPAAL [18, 5] specialized for cost-optimal reachability for the extended model of so-called priced timed automata....

  16. Scheduling of a hydro producer considering head-dependency, price scenarios and risk-aversion

    International Nuclear Information System (INIS)

    Pousinho, H.M.I.; Mendes, V.M.F.; Catalão, J.P.S.

    2012-01-01

    Highlights: ► A MIQP approach is proposed for the short-term hydro scheduling problem. ► Head-dependency, discontinuous operating regions and discharge ramping constraints are considered. ► As new contribution to earlier studies, market uncertainty is introduced in the model via price scenarios. ► Also, risk aversion is incorporated by limiting the volatility of the expected profit through CVaR. ► A case study based on one of the main Portuguese cascaded hydro systems is provided. - Abstract: In this paper, a mixed-integer quadratic programming approach is proposed for the short-term hydro scheduling problem, considering head-dependency, discontinuous operating regions and discharge ramping constraints. As new contributions to earlier studies, market uncertainty is introduced in the model via price scenarios, and risk aversion is also incorporated by limiting the volatility of the expected profit through the conditional value-at-risk. Our approach has been applied successfully to solve a case study based on one of the main Portuguese cascaded hydro systems, requiring a negligible computational time.

  17. Optimal hydro scheduling and offering strategies considering price uncertainty and risk management

    International Nuclear Information System (INIS)

    Catalão, J.P.S.; Pousinho, H.M.I.; Contreras, J.

    2012-01-01

    Hydro energy represents a priority in the energy policy of Portugal, with the aim of decreasing the dependence on fossil fuels. In this context, optimal hydro scheduling acquires added significance in moving towards a sustainable environment. A mixed-integer nonlinear programming approach is considered to enable optimal hydro scheduling for the short-term time horizon, including the effect of head on power production, start-up costs related to the units, multiple regions of operation, and constraints on discharge variation. As new contributions to the field, market uncertainty is introduced in the model via price scenarios and risk management is included using Conditional Value-at-Risk to limit profit volatility. Moreover, plant scheduling and pool offering by the hydro power producer are simultaneously considered to solve a realistic cascaded hydro system. -- Highlights: ► A mixed-integer nonlinear programming approach is considered for optimal hydro scheduling. ► Market uncertainty is introduced in the model via price scenarios. ► Risk management is included using conditional value-at-risk. ► Plant scheduling and pool offering by the hydro power producer are simultaneously considered. ► A realistic cascaded hydro system is solved.

  18. On using priced timed automata to achieve optimal scheduling

    DEFF Research Database (Denmark)

    Rasmussen, Jacob Illum; Larsen, Kim Guldstrand; Subramani, K.

    2006-01-01

    This contribution reports on the considerable effort made recently towards extending and applying well-established timed automata technology to optimal scheduling and planning problems. The effort of the authors in this direction has to a large extent been carried out as part of the European proj...... of so-called priced timed automata....

  19. U.S. Army Engineering and Support Center, Huntsville, Price Reasonableness Determinations for Federal Supply Schedule Orders for Supplies Need Improvement

    Science.gov (United States)

    2016-03-29

    Army Engineering and Support Center, Huntsville, Price Reasonableness Determinations for Federal Supply Schedule Orders for Supplies Need...0207.000) │ i Results in Brief U.S. Army Engineering and Support Center, Huntsville, Price Reasonableness Determinations for Federal Supply Schedule...officers made determinations of fair and reasonable pricing for General Services Administration Federal supply schedule orders awarded for purchases

  20. A branch-and-price algorithm for the long-term home care scheduling problem

    DEFF Research Database (Denmark)

    Gamst, Mette; Jensen, Thomas Sejr

    2012-01-01

    In several countries, home care is provided for certain citizens living at home. The long-term home care scheduling problem is to generate work plans such that a high quality of service is maintained, the work hours of the employees are respected, and the overall cost is kept as low as possible. We...... propose a branchand-price algorithm for the long-term home care scheduling problem. The pricing problem generates a one-day plan for an employee, and the master problem merges the plans with respect to regularity constraints. The method is capable of generating plans with up to 44 visits during one week....

  1. Price and Service Discrimination in Queuing Systems: Incentive Compatibility of Gc\\mu Scheduling

    OpenAIRE

    Jan A. Van Mieghem

    2000-01-01

    This article studies the optimal prices and service quality grades that a queuing system---the "firm"---provides to heterogeneous, utility-maximizing customers who measure quality by their experienced delay distributions. Results are threefold: First, delay cost curves are introduced that allow for a flexible description of a customer's quality sensitivity. Second, a comprehensive executable approach is proposed that analytically specifies scheduling, delay distributions and prices for arbitr...

  2. Integrated model for pricing, delivery time setting, and scheduling in make-to-order environments

    Science.gov (United States)

    Garmdare, Hamid Sattari; Lotfi, M. M.; Honarvar, Mahboobeh

    2018-03-01

    Usually, in make-to-order environments which work only in response to the customer's orders, manufacturers for maximizing the profits should offer the best price and delivery time for an order considering the existing capacity and the customer's sensitivity to both the factors. In this paper, an integrated approach for pricing, delivery time setting and scheduling of new arrival orders are proposed based on the existing capacity and accepted orders in system. In the problem, the acquired market demands dependent on the price and delivery time of both the manufacturer and its competitors. A mixed-integer non-linear programming model is presented for the problem. After converting to a pure non-linear model, it is validated through a case study. The efficiency of proposed model is confirmed by comparing it to both the literature and the current practice. Finally, sensitivity analysis for the key parameters is carried out.

  3. Collaborative Scheduling between OSPPs and Gasholders in Steel Mill under Time-of-Use Power Price

    Directory of Open Access Journals (Sweden)

    Juxian Hao

    2017-08-01

    Full Text Available Byproduct gases generated during steel production process are the main fuels for on-site power plants (OSPPs in steel enterprises. Recently, with the implementation of time-of-use (TOU power price in China, increasing attention has been paid to the collaborative scheduling between OSPPs and gasholders. However, the load shifting potential of OSPPs has seldom been discussed in previous studies. In this paper, a mixed integer linear programming (MILP-based scheduling model is built to evaluate the load shifting potential and the corresponding economic benefits. A case study is conducted on two steel enterprises with different configurations of OSPPs, and the optimal operation strategy is also discussed.

  4. Price Transparency in Primary Care: Can Patients Learn About Costs When Scheduling an Appointment?

    Science.gov (United States)

    Saloner, Brendan; Cope, Lisa Clemans; Hempstead, Katherine; Rhodes, Karin V; Polsky, Daniel; Kenney, Genevieve M

    2017-07-01

    Cost-sharing in health insurance plans creates incentives for patients to shop for lower prices, but it is unknown what price information patients can obtain when scheduling office visits. To determine whether new patients can obtain price information for a primary care visit and identify variation across insurance types, offices, and geographic areas. Simulated patient methodology in which trained interviewers posed as non-elderly adults seeking new patient primary care appointments. Caller insurance type (employer-sponsored insurance [ESI], Marketplace, or uninsured) and plan were experimentally manipulated. Callers who were offered a visit asked for price information. Unadjusted means and regression-adjusted differences by insurance, office types, and geography were calculated. Calls to a representative sample of primary care offices in ten states in 2014: Arkansas, Georgia, Iowa, Illinois, Massachusetts, Montana, New Jersey, Oregon, Pennsylvania, and Texas (N = 7865). Callers recorded whether they were able to obtain a price. If not, they recorded whether they were referred to other sources for price information. Overall, 61.8% of callers with ESI were able to obtain a price, versus 89.2% of uninsured and 47.3% of Marketplace callers (P information was also more readily available in small offices and in counties with high uninsured rates. Among callers not receiving a price, 72.1% of callers with ESI were referred to other sources (billing office or insurance company), versus 25.8% of uninsured and 50.9% of Marketplace callers (P information is often unavailable for privately insured patients seeking primary care visits at the time a visit is scheduled.

  5. Presenting a multi-objective generation scheduling model for pricing demand response rate in micro-grid energy management

    International Nuclear Information System (INIS)

    Aghajani, G.R.; Shayanfar, H.A.; Shayeghi, H.

    2015-01-01

    Highlights: • Using DRPs to cover the uncertainties resulted from power generation by WT and PV. • Proposing the use of price-offer packages and amount of DR for implement DRPs. • Considering a multi-objective scheduling model and use of MOPSO algorithm. - Abstract: In this paper, a multi-objective energy management system is proposed in order to optimize micro-grid (MG) performance in a short-term in the presence of Renewable Energy Sources (RESs) for wind and solar energy generation with a randomized natural behavior. Considering the existence of different types of customers including residential, commercial, and industrial consumers can participate in demand response programs. As with declare their interruptible/curtailable demand rate or select from among different proposed prices so as to assist the central micro-grid control in terms of optimizing micro-grid operation and covering energy generation uncertainty from the renewable sources. In this paper, to implement Demand Response (DR) schedules, incentive-based payment in the form of offered packages of price and DR quantity collected by Demand Response Providers (DRPs) is used. In the typical micro-grid, different technologies including Wind Turbine (WT), PhotoVoltaic (PV) cell, Micro-Turbine (MT), Full Cell (FC), battery hybrid power source and responsive loads are used. The simulation results are considered in six different cases in order to optimize operation cost and emission with/without DR. Considering the complexity and non-linearity of the proposed problem, Multi-Objective Particle Swarm Optimization (MOPSO) is utilized. Also, fuzzy-based mechanism and non-linear sorting system are applied to determine the best compromise considering the set of solutions from Pareto-front space. The numerical results represented the effect of the proposed Demand Side Management (DSM) scheduling model on reducing the effect of uncertainty obtained from generation power and predicted by WT and PV in a MG.

  6. Optimal scheduling for electric heat booster under day-ahead electricity and heat pricing

    DEFF Research Database (Denmark)

    Cai, Hanmin; You, Shi; Bindner, Henrik W.

    2017-01-01

    Multi-energy system (MES) operation calls for active management of flexible resources across energy sectors to improve efficiency and meet challenging environmental targets. Electric heat booster, a solution for Domestic Hot Water (DHW) preparation under Low-Temperature-District-Heating (LTDH......) context, is identified as one of aforementioned flexible resources for electricity and heat sectors. This paper extends the concept of optimal load scheduling under day-ahead pricing from electricity sector only to both electricity and heat sectors. A case study constructing day-ahead energy prices...

  7. Evaluating the effectiveness of mixed-integer linear programming for day-ahead hydro-thermal self-scheduling considering price uncertainty and forced outage rate

    International Nuclear Information System (INIS)

    Esmaeily, Ali; Ahmadi, Abdollah; Raeisi, Fatima; Ahmadi, Mohammad Reza; Esmaeel Nezhad, Ali; Janghorbani, Mohammadreza

    2017-01-01

    A new optimization framework based on MILP model is introduced in the paper for the problem of stochastic self-scheduling of hydrothermal units known as HTSS Problem implemented in a joint energy and reserve electricity market with day-ahead mechanism. The proposed MILP framework includes some practical constraints such as the cost due to valve-loading effect, the limit due to DRR and also multi-POZs, which have been less investigated in electricity market models. For the sake of more accuracy, for hydro generating units’ model, multi performance curves are also used. The problem proposed in this paper is formulated using a model on the basis of a stochastic optimization technique while the objective function is maximizing the expected profit utilizing MILP technique. The suggested stochastic self-scheduling model employs the price forecast error in order to take into account the uncertainty due to price. Besides, LMCS is combined with roulette wheel mechanism so that the scenarios corresponding to the non-spinning reserve price and spinning reserve price as well as the energy price at each hour of the scheduling are generated. Finally, the IEEE 118-bus power system is used to indicate the performance and the efficiency of the suggested technique. - Highlights: • Characterizing the uncertainties of price and FOR of units. • Replacing the fixed ramping rate constraints with the dynamic ones. • Proposing linearized model for the valve-point effects of thermal units. • Taking into consideration the multi-POZs relating to the thermal units. • Taking into consideration the multi-performance curves of hydroelectric units.

  8. The Questionable Economic Case for Value-Based Drug Pricing in Market Health Systems.

    Science.gov (United States)

    Pauly, Mark V

    2017-02-01

    This article investigates the economic theory and interpretation of the concept of "value-based pricing" for new breakthrough drugs with no close substitutes in a context (such as the United States) in which a drug firm with market power sells its product to various buyers. The interpretation is different from that in a country that evaluates medicines for a single public health insurance plan or a set of heavily regulated plans. It is shown that there will not ordinarily be a single value-based price but rather a schedule of prices with different volumes of buyers at each price. Hence, it is incorrect to term a particular price the value-based price, or to argue that the profit-maximizing monopoly price is too high relative to some hypothesized value-based price. When effectiveness of treatment or value of health is heterogeneous, the profit-maximizing price can be higher than that associated with assumed values of quality-adjusted life-years. If the firm sets a price higher than the value-based price for a set of potential buyers, the optimal strategy of the buyers is to decline to purchase that drug. The profit-maximizing price will come closer to a unique value-based price if demand is less heterogeneous. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  9. Constraint-based job shop scheduling with ILOG SCHEDULER

    NARCIS (Netherlands)

    Nuijten, W.P.M.; Le Pape, C.

    1998-01-01

    We introduce constraint-based scheduling and discuss its main principles. An approximation algorithm based on tree search is developed for the job shop scheduling problem using ILOG SCHEDULER. A new way of calculating lower bounds on the makespan of the job shop scheduling problem is presented and

  10. Value-based pricing

    OpenAIRE

    Netseva-Porcheva Tatyana

    2010-01-01

    The main aim of the paper is to present the value-based pricing. Therefore, the comparison between two approaches of pricing is made - cost-based pricing and value-based pricing. The 'Price sensitively meter' is presented. The other topic of the paper is the perceived value - meaning of the perceived value, the components of perceived value, the determination of perceived value and the increasing of perceived value. In addition, the best company strategies in matrix 'value-cost' are outlined. .

  11. Value-based pricing

    Directory of Open Access Journals (Sweden)

    Netseva-Porcheva Tatyana

    2010-01-01

    Full Text Available The main aim of the paper is to present the value-based pricing. Therefore, the comparison between two approaches of pricing is made - cost-based pricing and value-based pricing. The 'Price sensitively meter' is presented. The other topic of the paper is the perceived value - meaning of the perceived value, the components of perceived value, the determination of perceived value and the increasing of perceived value. In addition, the best company strategies in matrix 'value-cost' are outlined. .

  12. Scenario-based stochastic optimal operation of wind, photovoltaic, pump-storage hybrid system in frequency- based pricing

    International Nuclear Information System (INIS)

    Zare Oskouei, Morteza; Sadeghi Yazdankhah, Ahmad

    2015-01-01

    Highlights: • Two-stage objective function is proposed for optimization problem. • Hourly-based optimal contractual agreement is calculated. • Scenario-based stochastic optimization problem is solved. • Improvement of system frequency by utilizing PSH unit. - Abstract: This paper proposes the operating strategy of a micro grid connected wind farm, photovoltaic and pump-storage hybrid system. The strategy consists of two stages. In the first stage, the optimal hourly contractual agreement is determined. The second stage corresponds to maximizing its profit by adapting energy management strategy of wind and photovoltaic in coordination with optimum operating schedule of storage device under frequency based pricing for a day ahead electricity market. The pump-storage hydro plant is utilized to minimize unscheduled interchange flow and maximize the system benefit by participating in frequency control based on energy price. Because of uncertainties in power generation of renewable sources and market prices, generation scheduling is modeled by a stochastic optimization problem. Uncertainties of parameters are modeled by scenario generation and scenario reduction method. A powerful optimization algorithm is proposed using by General Algebraic Modeling System (GAMS)/CPLEX. In order to verify the efficiency of the method, the algorithm is applied to various scenarios with different wind and photovoltaic power productions in a day ahead electricity market. The numerical results demonstrate the effectiveness of the proposed approach.

  13. Consumer Behavior towards Scheduling and Pricing of Electric Cars Recharging: Theoretical and Experimental Analysis

    DEFF Research Database (Denmark)

    Fetene, Gebeyehu Manie

    electric cars. The last chapter deals with analysis of energy consumption rate and its determinants of electric cars under the hands of customers. A variety of techniques are used including analysis of field data, economics laboratory experiments and theoretical modeling with simulation. Chapter one...... and Pricing of Electric Vehicle Recharging’, proposes, and tests at laboratory, contracts about recharging BEVs combining the ultimatum game framework and the myopic loss aversion (MLA) behavioral hypothesis. The model represents the behavior of EV-owners trading-off between the amount of the discount on fee...... price as long-term contracts may curtail MLA behavior and help BEV owners to choose cost minimizing recharging time and, simultaneously, may help to reduce BEVs impact on the electricity grid system. The fourth chapter, ‘Using the Peer Effect in Scheduling and Pricing Electric Vehicles Recharging...

  14. Electric power systems advanced forecasting techniques and optimal generation scheduling

    CERN Document Server

    Catalão, João P S

    2012-01-01

    Overview of Electric Power Generation SystemsCláudio MonteiroUncertainty and Risk in Generation SchedulingRabih A. JabrShort-Term Load ForecastingAlexandre P. Alves da Silva and Vitor H. FerreiraShort-Term Electricity Price ForecastingNima AmjadyShort-Term Wind Power ForecastingGregor Giebel and Michael DenhardPrice-Based Scheduling for GencosGovinda B. Shrestha and Songbo QiaoOptimal Self-Schedule of a Hydro Producer under UncertaintyF. Javier Díaz and Javie

  15. Modelling the transition from cost-based to bid-based pricing in a deregulated electricity-market

    International Nuclear Information System (INIS)

    Druce, Donald J.

    2007-01-01

    Alberta is a province in western Canada with a deregulated electricity-market. Market clearing prices for most hours reflect the cost of either coal-fired or gas-fired thermal generation. Whenever there is a chronic shortage of generation or even a temporary one due to an outage, prices can be bid much higher than fuel costs would suggest. The province of British Columbia borders Alberta to the west and its electric utility, BC Hydro, has a history of trade with the utilities in Alberta. BC Hydro has predominantly hydroelectric resources and large storage reservoirs. Prior to Alberta's deregulation in 1996, BC Hydro was able to enter into mutually beneficial load-factoring contracts with the Alberta utilities. Now, as long as the transmission is available, BC Hydro can buy low priced off-peak coal-fired energy and sell into the high priced periods without having to share the benefits. BC Hydro uses a combination of econometric and Monte Carlo modelling to simulate hourly price-duration curves for Alberta that capture both cost-based and bid-based characteristics. This approach provides a good fit with the stochastic dynamic programming model that BC Hydro has developed for its mid-term hydro scheduling

  16. Research on intelligent power consumption strategy based on time-of-use pricing

    Science.gov (United States)

    Fu, Wei; Gong, Li; Chen, Heli; He, Yu

    2017-06-01

    In this paper, through the analysis of shortcomings of the current domestic and foreign household power consumption strategy: Passive way of power consumption, ignoring the different priority of electric equipment, neglecting the actual load pressure of the grid, ignoring the interaction with the user, to decrease the peak-valley difference and improve load curve in residential area by demand response (DR technology), an intelligent power consumption scheme based on time-of-use(TOU) pricing for household appliances is proposed. The main contribution of this paper is: (1) Three types of household appliance loads are abstracted from different operating laws of various household appliances, and the control models and DR strategies corresponding to these types are established. (2) The fuzzified processing for the information of TOU price, which is based on the time intervals, is performed to get the price priority, in accordance with such DR events as the maximum restricted load of DR, the time of DR and the duration of interruptible load and so on, the DR control rule and pre-scheduling mechanism are led in. (3) The dispatching sequence of household appliances in the control and scheduling queue are switched and controlled to implement the equilibrium of peak and valley loads. The equilibrium effects and economic benefits of power system by pre-scheduling and DR dispatching are compared and analyzed by simulation example, and the results show that using the proposed household appliance control (HAC) scheme the overall cost of consumers can be reduced and the power system load can be alleviated, so the proposed household appliance control (HAC) scheme is feasible and reasonable.

  17. Optimal Scheduling of Domestic Appliances via MILP

    Directory of Open Access Journals (Sweden)

    Zdenek Bradac

    2014-12-01

    Full Text Available This paper analyzes a consumption scheduling mechanism for domestic appliances within a home area network. The aim of the proposed scheduling is to minimize the total energy price paid by the consumer and to reduce power peaks in order to achieve a balanced daily load schedule. An exact and computationally efficient mixed-integer linear programming (MILP formulation of the problem is presented. This model is verified by several problem instances. Realistic scenarios based on the real price tariffs commercially available in the Czech Republic are calculated. The results obtained by solving the optimization problem are compared with a simulation of the ripple control service currently used by many domestic consumers in the Czech Republic.

  18. Nonlinear Price Schedules and Tied Products.

    OpenAIRE

    Ormiston, Michael B; Phillips, Owen R

    1988-01-01

    Illegal tying often occurs when a monopolist jointly sells a product with a complementary requirement, also sold competitively. Along with selling the complement at its competi tive price, this paper shows that profit can increase when a monopoli st lets consumers bundle any amount of the requirement with the basic product at a fixed price. Examples illustrate demand conditions that enhance the profitability of this nonlinear price strategy and show that profits can approximate those earned f...

  19. Nonlinear Pricing in Energy and Environmental Markets

    Science.gov (United States)

    Ito, Koichiro

    This dissertation consists of three empirical studies on nonlinear pricing in energy and environmental markets. The first investigates how consumers respond to multi-tier nonlinear price schedules for residential electricity. Chapter 2 asks a similar research question for residential water pricing. Finally, I examine the effect of nonlinear financial rewards for energy conservation by applying a regression discontinuity design to a large-scale electricity rebate program that was implemented in California. Economic theory generally assumes that consumers respond to marginal prices when making economic decisions, but this assumption may not hold for complex price schedules. The chapter "Do Consumers Respond to Marginal or Average Price? Evidence from Nonlinear Electricity Pricing" provides empirical evidence that consumers respond to average price rather than marginal price when faced with nonlinear electricity price schedules. Nonlinear price schedules, such as progressive income tax rates and multi-tier electricity prices, complicate economic decisions by creating multiple marginal prices for the same good. Evidence from laboratory experiments suggests that consumers facing such price schedules may respond to average price as a heuristic. I empirically test this prediction using field data by exploiting price variation across a spatial discontinuity in electric utility service areas. The territory border of two electric utilities lies within several city boundaries in southern California. As a result, nearly identical households experience substantially different nonlinear electricity price schedules. Using monthly household-level panel data from 1999 to 2008, I find strong evidence that consumers respond to average price rather than marginal or expected marginal price. I show that even though this sub-optimizing behavior has a minimal impact on individual welfare, it can critically alter the policy implications of nonlinear pricing. The second chapter " How Do

  20. Modelling the transition from cost-based to bid-based pricing in a deregulated electricity-market

    Energy Technology Data Exchange (ETDEWEB)

    Druce, Donald J. [BC Hydro, 6911 Southpoint Drive, Burnaby, British Columbia (Canada)

    2007-12-15

    Alberta is a province in western Canada with a deregulated electricity-market. Market clearing prices for most hours reflect the cost of either coal-fired or gas-fired thermal generation. Whenever there is a chronic shortage of generation or even a temporary one due to an outage, prices can be bid much higher than fuel costs would suggest. The province of British Columbia borders Alberta to the west and its electric utility, BC Hydro, has a history of trade with the utilities in Alberta. BC Hydro has predominantly hydroelectric resources and large storage reservoirs. Prior to Alberta's deregulation in 1996, BC Hydro was able to enter into mutually beneficial load-factoring contracts with the Alberta utilities. Now, as long as the transmission is available, BC Hydro can buy low priced off-peak coal-fired energy and sell into the high priced periods without having to share the benefits. BC Hydro uses a combination of econometric and Monte Carlo modelling to simulate hourly price-duration curves for Alberta that capture both cost-based and bid-based characteristics. This approach provides a good fit with the stochastic dynamic programming model that BC Hydro has developed for its mid-term hydro scheduling. (author)

  1. Day-ahead resource scheduling of a renewable energy based virtual power plant

    International Nuclear Information System (INIS)

    Zamani, Ali Ghahgharaee; Zakariazadeh, Alireza; Jadid, Shahram

    2016-01-01

    Highlights: • Simultaneous energy and reserve scheduling of a VPP. • Aggregate uncertainties of electricity prices, renewable generation and load demand. • Develop a stochastic scheduling model using the point estimate method. - Abstract: The evolution of energy markets is accelerating in the direction of a greater reliance upon distributed energy resources (DERs). To manage this increasing two-way complexity, virtual power plants (VPPs) are being deployed today all over the world. In this paper, a probabilistic model for optimal day ahead scheduling of electrical and thermal energy resources in a VPP is proposed where participation of energy storage systems and demand response programs (DRPs) are also taken into account. In the proposed model, energy and reserve is simultaneously scheduled considering the uncertainties of market prices, electrical demand and intermittent renewable power generation. The Point Estimate Method (PEM) is applied in order to model the uncertainties of VPP’s scheduling problem. Moreover, the optimal reserve scheduling of VPP is presented which efficiently decreases VPP’s risk facing the unexpected fluctuations of uncertain parameters at the power delivery time. The results demonstrated that implementation of demand response programs (DRPs) would decrease total operation costs of VPP as well as its dependency on the upstream network.

  2. Pricing Mining Concessions Based on Combined Multinomial Pricing Model

    Directory of Open Access Journals (Sweden)

    Chang Xiao

    2017-01-01

    Full Text Available A combined multinomial pricing model is proposed for pricing mining concession in which the annualized volatility of the price of mineral products follows a multinomial distribution. First, a combined multinomial pricing model is proposed which consists of binomial pricing models calculated according to different volatility values. Second, a method is provided to calculate the annualized volatility and the distribution. Third, the value of convenience yields is calculated based on the relationship between the futures price and the spot price. The notion of convenience yields is used to adjust our model as well. Based on an empirical study of a Chinese copper mine concession, we verify that our model is easy to use and better than the model with constant volatility when considering the changing annualized volatility of the price of the mineral product.

  3. Frequency Based Real-time Pricing for Residential Prosumers

    Science.gov (United States)

    Hambridge, Sarah Mabel

    stability in a free, competitive, market. Frequency based pricing is applied to secondary frequency control in this work, providing support at one to five minute time intervals. In Chapter 2, a frequency based pricing curve is designed as a preliminary study and the response of the prosumer is optimized for economic dispatch. In Chapter 3, a day-ahead schedule and real-time adjustment energy management framework is presented for the prosumer, creating a market structure similar to the existing energy market supervised by Independent System Operators (ISOs). Enabling technology, such as the solid state transformer (SST) is described for prosumer energy transactions, controlling power flow from the prosumer's energy cell to the grid or neighboring prosumer as an energy router. Experimental results are shown to demonstrate this capability. Additionally, the SST is capable of measuring the grid frequency. Lastly, a frequency based real-time hybrid electricity rate is presented in Chapter 4 and Chapter 5. Chapter 4 specializes in a single direction rate while Chapter 5 presents a bi-directional rate. A Time-of-use (TOU) rate is combined with the real-time frequency based price to lower energy bills for a residential prosumer with ESS, in agreement with the proposed day-ahead and real-time energy management framework. The cost to the ESS is also considered in this section. Linear programming and strategic rule based methods are utilized to find the lowest energy bill. As a result, prosumers can use ESS to balance the grid, reducing their bill as much per kWh as PV or DG under a TOU net-metering price scheme, while providing distributed frequency support to the grid authority. The variability of the frequency based rate is similar to variability in the stock market, which gives a sense of how prosumers will interact with variable prices in a system supported by The Energy Internet.

  4. Edgeworth Price Cycles, Cost-Based Pricing, and Sticky Pricing in Retail Gasoline Markets

    OpenAIRE

    Michael D. Noel

    2007-01-01

    This paper examines dynamic pricing behavior in retail gasoline markets for 19 Canadian cities over 574 weeks. I find three distinct retail pricing patterns: 1. cost-based pricing, 2. sticky pricing, and 3. steep, asymmetric retail price cycles that, while seldom documented empirically, resemble those of Maskin & Tirole[1988]. Using a Markov switching regression, I estimate the prevalence of patterns and the structural characteristics of the cycles. Retail price cycles prevail in over 40% of ...

  5. Intelligent Scheduling of a Grid-Connected Heat Pump in a Danish Detached House

    DEFF Research Database (Denmark)

    Gianniou, Panagiota; Foteinaki, Kyriaki; Heller, Alfred

    This study proposes a methodology for intelligent scheduling of a heat pump installed in a refurbished grid-connected detached house in Denmark. This scheduling is conducted through the coupling of a dynamic building simulation tool with an optimization tool. The optimization of the operation of ...... thermal comfort conditions. The proposed methodology bridges dynamic building modelling with optimization of real-time operation of HVAC systems offering a detailed model for building physics, especially regarding thermal mass and a stochastic price-based control....... of the system is based on a price-signal considering a three-day period for different weather cases. The results show that the optimal scheduling of the system is successful in terms of reducing the peak load during times when electricity prices are high, thus achieving cost savings as well as maintaining good......This study proposes a methodology for intelligent scheduling of a heat pump installed in a refurbished grid-connected detached house in Denmark. This scheduling is conducted through the coupling of a dynamic building simulation tool with an optimization tool. The optimization of the operation...

  6. Constraint-based scheduling

    Science.gov (United States)

    Zweben, Monte

    1993-01-01

    The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operations Company, and the Lockheed Artificial Intelligence Center, uses a method called constraint-based iterative repair. Using this technique, one encodes both hard rules and preference criteria into data structures called constraints. GERRY repeatedly attempts to improve schedules by seeking repairs for violated constraints. The system provides a general scheduling framework which is being tested on two NASA applications. The larger of the two is the Space Shuttle Ground Processing problem which entails the scheduling of all the inspection, repair, and maintenance tasks required to prepare the orbiter for flight. The other application involves power allocation for the NASA Ames wind tunnels. Here the system will be used to schedule wind tunnel tests with the goal of minimizing power costs. In this paper, we describe the GERRY system and its application to the Space Shuttle problem. We also speculate as to how the system would be used for manufacturing, transportation, and military problems.

  7. Nonlinear Pricing to Produce Information

    OpenAIRE

    David J. Braden; Shmuel S. Oren

    1994-01-01

    We investigate the firm's dynamic nonlinear pricing problem when facing consumers whose tastes vary according to a scalar index. We relax the standard assumption that the firm knows the distribution of this index. In general the firm should determine its marginal price schedule as if it were myopic, and produce information by lowering the price schedule; “bunching” consumers at positive purchase levels should be avoided. As a special case we also consider a market characterized by homogeneous...

  8. Day Ahead Real Time Pricing and Critical Peak Pricing Based Power Scheduling for Smart Homes with Different Duty Cycles

    Directory of Open Access Journals (Sweden)

    Nadeem Javaid

    2018-06-01

    Full Text Available In this paper, we propose a demand side management (DSM scheme in the residential area for electricity cost and peak to average ratio (PAR alleviation with maximum users’ satisfaction. For this purpose, we implement state-of-the-art algorithms: enhanced differential evolution (EDE and teacher learning-based optimization (TLBO. Furthermore, we propose a hybrid technique (HT having the best features of both aforementioned algorithms. We consider a system model for single smart home as well as for a community (multiple homes and each home consists of multiple appliances with different priorities. The priority is assigned (to each appliance by electricity consumers and then the proposed scheme finds an optimal solution according to the assigned priorities. Day-ahead real time pricing (DA-RTP and critical peak pricing (CPP are used for electricity cost calculation. To validate our proposed scheme, simulations are carried out and results show that our proposed scheme efficiently achieves the aforementioned objectives. However, when we perform a comparison with existing schemes, HT outperforms other state-of-the-art schemes (TLBO and EDE in terms of electricity cost and PAR reduction while minimizing the average waiting time.

  9. Electricity usage scheduling in smart building environments using smart devices.

    Science.gov (United States)

    Lee, Eunji; Bahn, Hyokyung

    2013-01-01

    With the recent advances in smart grid technologies as well as the increasing dissemination of smart meters, the electricity usage of every moment can be detected in modern smart building environments. Thus, the utility company adopts different price of electricity at each time slot considering the peak time. This paper presents a new electricity usage scheduling algorithm for smart buildings that adopts real-time pricing of electricity. The proposed algorithm detects the change of electricity prices by making use of a smart device and changes the power mode of each electric device dynamically. Specifically, we formulate the electricity usage scheduling problem as a real-time task scheduling problem and show that it is a complex search problem that has an exponential time complexity. An efficient heuristic based on genetic algorithms is performed on a smart device to cut down the huge searching space and find a reasonable schedule within a feasible time budget. Experimental results with various building conditions show that the proposed algorithm reduces the electricity charge of a smart building by 25.6% on average and up to 33.4%.

  10. Optimal Day-ahead Charging Scheduling of Electric Vehicles through an Aggregative Game Model

    DEFF Research Database (Denmark)

    Liu, Zhaoxi; Wu, Qiuwei; Huang, Shaojun

    2017-01-01

    The electric vehicle (EV) market has been growing rapidly around the world. With large scale deployment of EVs in power systems, both the grid and EV owners will benefit if the flexible demand of EV charging is properly managed through the electricity market. When EV charging demand is considerable...... in a grid, it will impact spot prices in the electricity market and consequently influence the charging scheduling itself. The interaction between the spot prices and the EV demand needs to be considered in the EV charging scheduling, otherwise it will lead to a higher charging cost. A day-ahead EV charging...... scheduling based on an aggregative game model is proposed in this paper. The impacts of the EV demand on the electricity prices are formulated with the game model in the scheduling considering possible actions of other EVs. The existence and uniqueness of the pure strategy Nash equilibrium are proved...

  11. A Personalized Rolling Optimal Charging Schedule for Plug-In Hybrid Electric Vehicle Based on Statistical Energy Demand Analysis and Heuristic Algorithm

    Directory of Open Access Journals (Sweden)

    Fanrong Kong

    2017-09-01

    Full Text Available To alleviate the emission of greenhouse gas and the dependence on fossil fuel, Plug-in Hybrid Electrical Vehicles (PHEVs have gained an increasing popularity in current decades. Due to the fluctuating electricity prices in the power market, a charging schedule is very influential to driving cost. Although the next-day electricity prices can be obtained in a day-ahead power market, a driving plan is not easily made in advance. Although PHEV owners can input a next-day plan into a charging system, e.g., aggregators, day-ahead, it is a very trivial task to do everyday. Moreover, the driving plan may not be very accurate. To address this problem, in this paper, we analyze energy demands according to a PHEV owner’s historical driving records and build a personalized statistic driving model. Based on the model and the electricity spot prices, a rolling optimization strategy is proposed to help make a charging decision in the current time slot. On one hand, by employing a heuristic algorithm, the schedule is made according to the situations in the following time slots. On the other hand, however, after the current time slot, the schedule will be remade according to the next tens of time slots. Hence, the schedule is made by a dynamic rolling optimization, but it only decides the charging decision in the current time slot. In this way, the fluctuation of electricity prices and driving routine are both involved in the scheduling. Moreover, it is not necessary for PHEV owners to input a day-ahead driving plan. By the optimization simulation, the results demonstrate that the proposed method is feasible to help owners save charging costs and also meet requirements for driving.

  12. A Comparison of Software Schedule Estimators

    Science.gov (United States)

    1990-09-01

    SLIM ...................................... 33 SPQR /20 ................................... 35 System -4 .................................... 37 Previous...24 3. PRICE-S Outputs ..................................... 26 4. COCOMO Factors by Category ........................... 28 5. SPQR /20 Activities...actual schedules experienced on the projects. The models analyzed were REVIC, PRICE-S, System-4, SPQR /20, and SEER. ix A COMPARISON OF SOFTWARE

  13. Constraint-based scheduling applying constraint programming to scheduling problems

    CERN Document Server

    Baptiste, Philippe; Nuijten, Wim

    2001-01-01

    Constraint Programming is a problem-solving paradigm that establishes a clear distinction between two pivotal aspects of a problem: (1) a precise definition of the constraints that define the problem to be solved and (2) the algorithms and heuristics enabling the selection of decisions to solve the problem. It is because of these capabilities that Constraint Programming is increasingly being employed as a problem-solving tool to solve scheduling problems. Hence the development of Constraint-Based Scheduling as a field of study. The aim of this book is to provide an overview of the most widely used Constraint-Based Scheduling techniques. Following the principles of Constraint Programming, the book consists of three distinct parts: The first chapter introduces the basic principles of Constraint Programming and provides a model of the constraints that are the most often encountered in scheduling problems. Chapters 2, 3, 4, and 5 are focused on the propagation of resource constraints, which usually are responsibl...

  14. Demand side management in recycling and electricity retail pricing

    Science.gov (United States)

    Kazan, Osman

    This dissertation addresses several problems from the recycling industry and electricity retail market. The first paper addresses a real-life scheduling problem faced by a national industrial recycling company. Based on their practices, a scheduling problem is defined, modeled, analyzed, and a solution is approximated efficiently. The recommended application is tested on the real-life data and randomly generated data. The scheduling improvements and the financial benefits are presented. The second problem is from electricity retail market. There are well-known patterns in daily usage in hours. These patterns change in shape and magnitude by seasons and days of the week. Generation costs are multiple times higher during the peak hours of the day. Yet most consumers purchase electricity at flat rates. This work explores analytic pricing tools to reduce peak load electricity demand for retailers. For that purpose, a nonlinear model that determines optimal hourly prices is established based on two major components: unit generation costs and consumers' utility. Both are analyzed and estimated empirically in the third paper. A pricing model is introduced to maximize the electric retailer's profit. As a result, a closed-form expression for the optimal price vector is obtained. Possible scenarios are evaluated for consumers' utility distribution. For the general case, we provide a numerical solution methodology to obtain the optimal pricing scheme. The models recommended are tested under various scenarios that consider consumer segmentation and multiple pricing policies. The recommended model reduces the peak load significantly in most cases. Several utility companies offer hourly pricing to their customers. They determine prices using historical data of unit electricity cost over time. In this dissertation we develop a nonlinear model that determines optimal hourly prices with parameter estimation. The last paper includes a regression analysis of the unit generation cost

  15. Value-based differential pricing: efficient prices for drugs in a global context.

    Science.gov (United States)

    Danzon, Patricia; Towse, Adrian; Mestre-Ferrandiz, Jorge

    2015-03-01

    This paper analyzes pharmaceutical pricing between and within countries to achieve second-best static and dynamic efficiency. We distinguish countries with and without universal insurance, because insurance undermines patients' price sensitivity, potentially leading to prices above second-best efficient levels. In countries with universal insurance, if each payer unilaterally sets an incremental cost-effectiveness ratio (ICER) threshold based on its citizens' willingness-to-pay for health; manufacturers price to that ICER threshold; and payers limit reimbursement to patients for whom a drug is cost-effective at that price and ICER, then the resulting price levels and use within each country and price differentials across countries are roughly consistent with second-best static and dynamic efficiency. These value-based prices are expected to differ cross-nationally with per capita income and be broadly consistent with Ramsey optimal prices. Countries without comprehensive insurance avoid its distorting effects on prices but also lack financial protection and affordability for the poor. Improving pricing efficiency in these self-pay countries includes improving regulation and consumer information about product quality and enabling firms to price discriminate within and between countries. © 2013 The Authors. Health Economics published by John Wiley & Sons Ltd.

  16. Optimal load scheduling in commercial and residential microgrids

    Science.gov (United States)

    Ganji Tanha, Mohammad Mahdi

    Residential and commercial electricity customers use more than two third of the total energy consumed in the United States, representing a significant resource of demand response. Price-based demand response, which is in response to changes in electricity prices, represents the adjustments in load through optimal load scheduling (OLS). In this study, an efficient model for OLS is developed for residential and commercial microgrids which include aggregated loads in single-units and communal loads. Single unit loads which include fixed, adjustable and shiftable loads are controllable by the unit occupants. Communal loads which include pool pumps, elevators and central heating/cooling systems are shared among the units. In order to optimally schedule residential and commercial loads, a community-based optimal load scheduling (CBOLS) is proposed in this thesis. The CBOLS schedule considers hourly market prices, occupants' comfort level, and microgrid operation constraints. The CBOLS' objective in residential and commercial microgrids is the constrained minimization of the total cost of supplying the aggregator load, defined as the microgrid load minus the microgrid generation. This problem is represented by a large-scale mixed-integer optimization for supplying single-unit and communal loads. The Lagrangian relaxation methodology is used to relax the linking communal load constraint and decompose the independent single-unit functions into subproblems which can be solved in parallel. The optimal solution is acceptable if the aggregator load limit and the duality gap are within the bounds. If any of the proposed criteria is not satisfied, the Lagrangian multiplier will be updated and a new optimal load schedule will be regenerated until both constraints are satisfied. The proposed method is applied to several case studies and the results are presented for the Galvin Center load on the 16th floor of the IIT Tower in Chicago.

  17. Hybrid Particle Swarm Optimization based Day-Ahead Self-Scheduling for Thermal Generator in Competitive Electricity Market

    DEFF Research Database (Denmark)

    Pindoriya, Naran M.; Singh, S.N.; Østergaard, Jacob

    2009-01-01

    in day-ahead energy market subject to operational constraints and 2) at the same time, to minimize the risk due to uncertainty in price forecast. Therefore, it is a conflicting bi-objective optimization problem which has both binary and continuous optimization variables considered as constrained mixed......This paper presents a hybrid particle swarm optimization algorithm (HPSO) to solve the day-ahead self-scheduling for thermal power producer in competitive electricity market. The objective functions considered to model the self-scheduling problem are 1) to maximize the profit from selling energy...... integer nonlinear programming. To demonstrate the effectiveness of the proposed method for self-scheduling in a day-ahead energy market, the locational margin price (LMP) forecast uncertainty in PJM electricity market is considered. An adaptive wavelet neural network (AWNN) is used to forecast the day...

  18. Ensuring the Reliable Operation of the Power Grid: State-Based and Distributed Approaches to Scheduling Energy and Contingency Reserves

    Science.gov (United States)

    Prada, Jose Fernando

    Keeping a contingency reserve in power systems is necessary to preserve the security of real-time operations. This work studies two different approaches to the optimal allocation of energy and reserves in the day-ahead generation scheduling process. Part I presents a stochastic security-constrained unit commitment model to co-optimize energy and the locational reserves required to respond to a set of uncertain generation contingencies, using a novel state-based formulation. The model is applied in an offer-based electricity market to allocate contingency reserves throughout the power grid, in order to comply with the N-1 security criterion under transmission congestion. The objective is to minimize expected dispatch and reserve costs, together with post contingency corrective redispatch costs, modeling the probability of generation failure and associated post contingency states. The characteristics of the scheduling problem are exploited to formulate a computationally efficient method, consistent with established operational practices. We simulated the distribution of locational contingency reserves on the IEEE RTS96 system and compared the results with the conventional deterministic method. We found that assigning locational spinning reserves can guarantee an N-1 secure dispatch accounting for transmission congestion at a reasonable extra cost. The simulations also showed little value of allocating downward reserves but sizable operating savings from co-optimizing locational nonspinning reserves. Overall, the results indicate the computational tractability of the proposed method. Part II presents a distributed generation scheduling model to optimally allocate energy and spinning reserves among competing generators in a day-ahead market. The model is based on the coordination between individual generators and a market entity. The proposed method uses forecasting, augmented pricing and locational signals to induce efficient commitment of generators based on firm

  19. A scalable delivery framework and a pricing model for streaming media with advertisements

    Science.gov (United States)

    Al-Hadrusi, Musab; Sarhan, Nabil J.

    2008-01-01

    This paper presents a delivery framework for streaming media with advertisements and an associated pricing model. The delivery model combines the benefits of periodic broadcasting and stream merging. The advertisements' revenues are used to subsidize the price of the media content. The pricing is determined based on the total ads' viewing time. Moreover, this paper presents an efficient ad allocation scheme and three modified scheduling policies that are well suited to the proposed delivery framework. Furthermore, we study the effectiveness of the delivery framework and various scheduling polices through extensive simulation in terms of numerous metrics, including customer defection probability, average number of ads viewed per client, price, arrival rate, profit, and revenue.

  20. Comparison of two dose and three dose human papillomavirus vaccine schedules: cost effectiveness analysis based on transmission model.

    Science.gov (United States)

    Jit, Mark; Brisson, Marc; Laprise, Jean-François; Choi, Yoon Hong

    2015-01-06

    To investigate the incremental cost effectiveness of two dose human papillomavirus vaccination and of additionally giving a third dose. Cost effectiveness study based on a transmission dynamic model of human papillomavirus vaccination. Two dose schedules for bivalent or quadrivalent human papillomavirus vaccines were assumed to provide 10, 20, or 30 years' vaccine type protection and cross protection or lifelong vaccine type protection without cross protection. Three dose schedules were assumed to give lifelong vaccine type and cross protection. United Kingdom. Males and females aged 12-74 years. No, two, or three doses of human papillomavirus vaccine given routinely to 12 year old girls, with an initial catch-up campaign to 18 years. Costs (from the healthcare provider's perspective), health related utilities, and incremental cost effectiveness ratios. Giving at least two doses of vaccine seems to be highly cost effective across the entire range of scenarios considered at the quadrivalent vaccine list price of £86.50 (€109.23; $136.00) per dose. If two doses give only 10 years' protection but adding a third dose extends this to lifetime protection, then the third dose also seems to be cost effective at £86.50 per dose (median incremental cost effectiveness ratio £17,000, interquartile range £11,700-£25,800). If two doses protect for more than 20 years, then the third dose will have to be priced substantially lower (median threshold price £31, interquartile range £28-£35) to be cost effective. Results are similar for a bivalent vaccine priced at £80.50 per dose and when the same scenarios are explored by parameterising a Canadian model (HPV-ADVISE) with economic data from the United Kingdom. Two dose human papillomavirus vaccine schedules are likely to be the most cost effective option provided protection lasts for at least 20 years. As the precise duration of two dose schedules may not be known for decades, cohorts given two doses should be closely

  1. BIM-BASED SCHEDULING OF CONSTRUCTION

    DEFF Research Database (Denmark)

    Andersson, Niclas; Büchmann-Slorup, Rolf

    2010-01-01

    The potential of BIM is generally recognized in the construction industry, but the practical application of BIM for management purposes is, however, still limited among contractors. The objective of this study is to review the current scheduling process of construction in light of BIM...... and communicate. Scheduling on the detailed level, on the other hand, follows a stipulated approach to scheduling, i.e. the Last Planner System (LPS), which is characterized by involvement of all actors in the construction phase. Thus, the major challenge when implementing BIM-based scheduling is to improve...

  2. Topology-based hierarchical scheduling using deficit round robin

    DEFF Research Database (Denmark)

    Yu, Hao; Yan, Ying; Berger, Michael Stubert

    2009-01-01

    according to the topology. The mapping process could be completed through the network management plane or by manual configuration. Based on the knowledge of the network, the scheduler can manage the traffic on behalf of other less advanced nodes, avoid potential traffic congestion, and provide flow...... protection and isolation. Comparisons between hierarchical scheduling, flow-based scheduling, and class-based scheduling schemes have been carried out under a symmetric tree topology. Results have shown that the hierarchical scheduling scheme provides better flow protection and isolation from attack...

  3. A Decomposition-Based Pricing Method for Solving a Large-Scale MILP Model for an Integrated Fishery

    Directory of Open Access Journals (Sweden)

    M. Babul Hasan

    2007-01-01

    The IFP can be decomposed into a trawler-scheduling subproblem and a fish-processing subproblem in two different ways by relaxing different sets of constraints. We tried conventional decomposition techniques including subgradient optimization and Dantzig-Wolfe decomposition, both of which were unacceptably slow. We then developed a decomposition-based pricing method for solving the large fishery model, which gives excellent computation times. Numerical results for several planning horizon models are presented.

  4. Exploiting Flexibility in Coupled Electricity and Natural Gas Markets: A Price-Based Approach

    DEFF Research Database (Denmark)

    Ordoudis, Christos; Delikaraoglou, Stefanos; Pinson, Pierre

    2017-01-01

    Natural gas-fired power plants (NGFPPs) are considered a highly flexible component of the energy system and can facilitate the large-scale integration of intermittent renewable generation. Therefore, it is necessary to improve the coordination between electric power and natural gas systems....... Considering a market-based coupling of these systems, we introduce a decision support tool that increases market efficiency in the current setup where day-ahead and balancing markets are cleared sequentially. The proposed approach relies on the optimal adjustment of natural gas price to modify the scheduling...

  5. Long-term home care scheduling

    DEFF Research Database (Denmark)

    Gamst, Mette; Jensen, Thomas Sejr

    In several countries, home care is provided for certain citizens living at home. The long-term home care scheduling problem is to generate work plans spanning several days such that a high quality of service is maintained and the overall cost is kept as low as possible. A solution to the problem...... provides detailed information on visits and visit times for each employee on each of the covered days. We propose a branch-and-price algorithm for the long-term home care scheduling problem. The pricing problem generates one-day plans for an employee, and the master problem merges the plans with respect...

  6. An algorithm for on-line price discrimination

    NARCIS (Netherlands)

    D.D.B. van Bragt; D.J.A. Somefun (Koye); E. Kutschinski; J.A. La Poutré (Han)

    2002-01-01

    textabstractThe combination of on-line dynamic pricing with price discrimination can be very beneficial for firms operating on the Internet. We therefore develop an on-line dynamic pricing algorithm that can adjust the price schedule for a good or service on behalf of a firm. This algorithm (a

  7. Knowledge-based scheduling of arrival aircraft

    Science.gov (United States)

    Krzeczowski, K.; Davis, T.; Erzberger, H.; Lev-Ram, I.; Bergh, C.

    1995-01-01

    A knowledge-based method for scheduling arrival aircraft in the terminal area has been implemented and tested in real-time simulation. The scheduling system automatically sequences, assigns landing times, and assigns runways to arrival aircraft by utilizing continuous updates of aircraft radar data and controller inputs. The scheduling algorithms is driven by a knowledge base which was obtained in over two thousand hours of controller-in-the-loop real-time simulation. The knowledge base contains a series of hierarchical 'rules' and decision logic that examines both performance criteria, such as delay reduction, as well as workload reduction criteria, such as conflict avoidance. The objective of the algorithms is to devise an efficient plan to land the aircraft in a manner acceptable to the air traffic controllers. This paper will describe the scheduling algorithms, give examples of their use, and present data regarding their potential benefits to the air traffic system.

  8. Location-based Scheduling

    DEFF Research Database (Denmark)

    Andersson, Niclas; Christensen, Knud

    on the market. However, CPM is primarily an activity based method that takes the activity as the unit of focus and there is criticism raised, specifically in the case of construction projects, on the method for deficient management of construction work and continuous flow of resources. To seek solutions...... to the identified limitations of the CPM method, an alternative planning and scheduling methodology that includes locations is tested. Location-based Scheduling (LBS) implies a shift in focus, from primarily the activities to the flow of work through the various locations of the project, i.e. the building. LBS uses...... the graphical presentation technique of Line-of-balance, which is adapted for planning and management of work-flows that facilitates resources to perform their work without interruptions caused by other resources working with other activities in the same location. As such, LBS and Lean Construction share...

  9. Real Time Information Based Energy Management Using Customer Preferences and Dynamic Pricing in Smart Homes

    Directory of Open Access Journals (Sweden)

    Muhammad Babar Rasheed

    2016-07-01

    Full Text Available This paper presents real time information based energy management algorithms to reduce electricity cost and peak to average ratio (PAR while preserving user comfort in a smart home. We categorize household appliances into thermostatically controlled (tc, user aware (ua, elastic (el, inelastic (iel and regular (r appliances/loads. An optimization problem is formulated to reduce electricity cost by determining the optimal use of household appliances. The operational schedules of these appliances are optimized in response to the electricity price signals and customer preferences to maximize electricity cost saving and user comfort while minimizing curtailed energy. Mathematical optimization models of tc appliances, i.e., air-conditioner and refrigerator, are proposed which are solved by using intelligent programmable communication thermostat ( iPCT. We add extra intelligence to conventional programmable communication thermostat (CPCT by using genetic algorithm (GA to control tc appliances under comfort constraints. The optimization models for ua, el, and iel appliances are solved subject to electricity cost minimization and PAR reduction. Considering user comfort, el appliances are considered where users can adjust appliance waiting time to increase or decrease their comfort level. Furthermore, energy demand of r appliances is fulfilled via local supply where the major objective is to reduce the fuel cost of various generators by proper scheduling. Simulation results show that the proposed algorithms efficiently schedule the energy demand of all types of appliances by considering identified constraints (i.e., PAR, variable prices, temperature, capacity limit and waiting time.

  10. Towards Cost and Comfort Based Hybrid Optimization for Residential Load Scheduling in a Smart Grid

    Directory of Open Access Journals (Sweden)

    Nadeem Javaid

    2017-10-01

    Full Text Available In a smart grid, several optimization techniques have been developed to schedule load in the residential area. Most of these techniques aim at minimizing the energy consumption cost and the comfort of electricity consumer. Conversely, maintaining a balance between two conflicting objectives: energy consumption cost and user comfort is still a challenging task. Therefore, in this paper, we aim to minimize the electricity cost and user discomfort while taking into account the peak energy consumption. In this regard, we implement and analyse the performance of a traditional dynamic programming (DP technique and two heuristic optimization techniques: genetic algorithm (GA and binary particle swarm optimization (BPSO for residential load management. Based on these techniques, we propose a hybrid scheme named GAPSO for residential load scheduling, so as to optimize the desired objective function. In order to alleviate the complexity of the problem, the multi dimensional knapsack is used to ensure that the load of electricity consumer will not escalate during peak hours. The proposed model is evaluated based on two pricing schemes: day-ahead and critical peak pricing for single and multiple days. Furthermore, feasible regions are calculated and analysed to develop a relationship between power consumption, electricity cost, and user discomfort. The simulation results are compared with GA, BPSO and DP, and validate that the proposed hybrid scheme reflects substantial savings in electricity bills with minimum user discomfort. Moreover, results also show a phenomenal reduction in peak power consumption.

  11. Self-scheduling and bidding strategies of thermal units with stochastic emission constraints

    International Nuclear Information System (INIS)

    Laia, R.; Pousinho, H.M.I.; Melíco, R.; Mendes, V.M.F.

    2015-01-01

    Highlights: • The management of thermal power plants is considered for different emission allowance levels. • The uncertainty on electricity price is considered by a set of scenarios. • A stochastic MILP approach allows devising the bidding strategies and hedging against price uncertainty and emission allowances. - Abstract: This paper is on the self-scheduling problem for a thermal power producer taking part in a pool-based electricity market as a price-taker, having bilateral contracts and emission-constrained. An approach based on stochastic mixed-integer linear programming approach is proposed for solving the self-scheduling problem. Uncertainty regarding electricity price is considered through a set of scenarios computed by simulation and scenario-reduction. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. A requirement on emission allowances to mitigate carbon footprint is modelled by a stochastic constraint. Supply functions for different emission allowance levels are accessed in order to establish the optimal bidding strategy. A case study is presented to illustrate the usefulness and the proficiency of the proposed approach in supporting biding strategies

  12. Optimal methodology for a machining process scheduling in spot electricity markets

    International Nuclear Information System (INIS)

    Yusta, J.M.; Torres, F.; Khodr, H.M.

    2010-01-01

    Electricity spot markets have introduced hourly variations in the price of electricity. These variations allow the increase of the energy efficiency by the appropriate scheduling and adaptation of the industrial production to the hourly cost of electricity in order to obtain the maximum profit for the industry. In this article a mathematical optimization model simulates costs and the electricity demand of a machining process. The resultant problem is solved using the generalized reduced gradient approach, to find the optimum production schedule that maximizes the industry profit considering the hourly variations of the price of electricity in the spot market. Different price scenarios are studied to analyze the impact of the spot market prices for electricity on the optimal scheduling of the machining process and on the industry profit. The convenience of the application of the proposed model is shown especially in cases of very high electricity prices.

  13. Tracing the Base: A Topographic Test for Collusive Basing-Point Pricing

    NARCIS (Netherlands)

    Bos, Iwan; Schinkel, Maarten Pieter

    2009-01-01

    Basing-point pricing is known to have been abused by geographically dispersed firms in order to eliminate competition on transportation costs. This paper develops a topographic test for collusive basing-point pricing. The method uses transaction data (prices, quantities) and customer project site

  14. Tracing the base: A topographic test for collusive basing-point pricing

    NARCIS (Netherlands)

    Bos, I.; Schinkel, M.P.

    2008-01-01

    Basing-point pricing is known to have been abused by geographically dispersed firms in order to eliminate competition on transportation costs. This paper develops a topographic test for collusive basing-point pricing. The method uses transaction data (prices, quantities) and customer project site

  15. Proceedings: 1996 EPRI conference on innovative approaches to electricity pricing: Managing the transition to market-based pricing

    International Nuclear Information System (INIS)

    1996-03-01

    This report presents the proceedings from the EPRI conference on innovative approaches to electricity pricing. Topics discussed include: power transmission pricing; retail pricing; price risk management; new pricing paradigms; changes from cost-based to a market-based pricing scheme; ancillary services; retail market strategies; profitability; unbundling; and value added services. This is the leading abstract. Papers are processed separately for the databases

  16. Risk-constrained self-scheduling of a fuel and emission constrained power producer using rolling window procedure

    International Nuclear Information System (INIS)

    Kazempour, S. Jalal; Moghaddam, Mohsen Parsa

    2011-01-01

    This work addresses a relevant methodology for self-scheduling of a price-taker fuel and emission constrained power producer in day-ahead correlated energy, spinning reserve and fuel markets to achieve a trade-off between the expected profit and the risk versus different risk levels based on Markowitz's seminal work in the area of portfolio selection. Here, a set of uncertainties including price forecasting errors and available fuel uncertainty are considered. The latter uncertainty arises because of uncertainties in being called for reserve deployment in the spinning reserve market and availability of power plant. To tackle the price forecasting errors, variances of energy, spinning reserve and fuel prices along with their covariances which are due to markets correlation are taken into account using relevant historical data. In order to tackle available fuel uncertainty, a framework for self-scheduling referred to as rolling window is proposed. This risk-constrained self-scheduling framework is therefore formulated and solved as a mixed-integer non-linear programming problem. Furthermore, numerical results for a case study are discussed. (author)

  17. PARTICAL SWARM OPTIMIZATION OF TASK SCHEDULING IN CLOUD COMPUTING

    OpenAIRE

    Payal Jaglan*, Chander Diwakar

    2016-01-01

    Resource provisioning and pricing modeling in cloud computing makes it an inevitable technology both on developer and consumer end. Easy accessibility of software and freedom of hardware configuration increase its demand in IT industry. It’s ability to provide a user-friendly environment, software independence, quality, pricing index and easy accessibility of infrastructure via internet. Task scheduling plays an important role in cloud computing systems. Task scheduling in cloud computing mea...

  18. A Regional Time-of-Use Electricity Price Based Optimal Charging Strategy for Electrical Vehicles

    Directory of Open Access Journals (Sweden)

    Jun Yang

    2016-08-01

    Full Text Available With the popularization of electric vehicles (EVs, the out-of-order charging behaviors of large numbers of EVs will bring new challenges to the safe and economic operation of power systems. This paper studies an optimal charging strategy for EVs. For that a typical urban zone is divided into four regions, a regional time-of-use (RTOU electricity price model is proposed to guide EVs when and where to charge considering spatial and temporal characteristics. In light of the elastic coefficient, the user response to the RTOU electricity price is analyzed, and also a bilayer optimization charging strategy including regional-layer and node-layer models is suggested to schedule the EVs. On the one hand, the regional layer model is designed to coordinate the EVs located in different time and space. On the other hand, the node layer model is built to schedule the EVs to charge in certain nodes. According to the simulations of an IEEE 33-bus distribution network, the performance of the proposed optimal charging strategy is verified. The results demonstrate that the proposed bilayer optimization strategy can effectively decrease the charging cost of users, mitigate the peak-valley load difference and the network loss. Besides, the RTOU electricity price shows better performance than the time-of-use (TOU electricity price.

  19. Designing of Vague Logic Based 2-Layered Framework for CPU Scheduler

    Directory of Open Access Journals (Sweden)

    Supriya Raheja

    2016-01-01

    Full Text Available Fuzzy based CPU scheduler has become of great interest by operating system because of its ability to handle imprecise information associated with task. This paper introduces an extension to the fuzzy based round robin scheduler to a Vague Logic Based Round Robin (VBRR scheduler. VBRR scheduler works on 2-layered framework. At the first layer, scheduler has a vague inference system which has the ability to handle the impreciseness of task using vague logic. At the second layer, Vague Logic Based Round Robin (VBRR scheduling algorithm works to schedule the tasks. VBRR scheduler has the learning capability based on which scheduler adapts intelligently an optimum length for time quantum. An optimum time quantum reduces the overhead on scheduler by reducing the unnecessary context switches which lead to improve the overall performance of system. The work is simulated using MATLAB and compared with the conventional round robin scheduler and the other two fuzzy based approaches to CPU scheduler. Given simulation analysis and results prove the effectiveness and efficiency of VBRR scheduler.

  20. Optimal joint scheduling of electrical and thermal appliances in a smart home environment

    International Nuclear Information System (INIS)

    Shirazi, Elham; Zakariazadeh, Alireza; Jadid, Shahram

    2015-01-01

    Highlights: • Thermal appliances are scheduled based on desired temperature and energy prices. • A discomfort index has been introduced within the home energy scheduling model. • Appliances are scheduled based on activity probability and desired options. • Starting probability depends on the social random factor and consumption behavior. - Abstract: With the development of home area network, residents have the opportunity to schedule their power usage in the home by themselves aiming at reducing electricity expenses. Moreover, as renewable energy sources are deployed in home, a home energy management system needs to consider both energy consumption and generation simultaneously to minimize the energy cost. In this paper, a smart home energy management model has been presented in which electrical and thermal appliances are jointly scheduled. The proposed method aims at minimizing the electricity cost of a residential customer by scheduling various type of appliances considering the residents consumption behavior, seasonal probability, social random factor, discomfort index and appliances starting probability functions. In this model, the home central controller receives the electricity price information, environmental factors data as well as the resident desired options in order to optimally schedule appliances including electrical and thermal. The scheduling approach is tested on a typical home including variety of home appliances, a small wind turbine, photovoltaic panel, combined heat and power unit, boiler and electrical and thermal storages over a 24-h period. The results show that the scheduling of different appliances can be reached simultaneously by using the proposed formulation. Moreover, simulation results evidenced that the proposed home energy management model exhibits a lower cost and, therefore, is more economical.

  1. Value based pricing: the least valued pricing strategy

    OpenAIRE

    Hoenen, Bob

    2017-01-01

    Pricing has been one of the least researched topics in marketing, although within these pricing strategies: cost-plus pricing is considered as the leading pricing strategy worldwide. Why should companies use such an unprofitable strategy, where fighting for a higher market share due to low prices is more a rule than exception? VBP is one of the most underestimated strategies by organizations. The definition of VBP is: 'value pricing applies to products that have the potential of being differe...

  2. Dynamic electricity pricing for electric vehicles using stochastic programming

    International Nuclear Information System (INIS)

    Soares, João; Ghazvini, Mohammad Ali Fotouhi; Borges, Nuno; Vale, Zita

    2017-01-01

    Electric Vehicles (EVs) are an important source of uncertainty, due to their variable demand, departure time and location. In smart grids, the electricity demand can be controlled via Demand Response (DR) programs. Smart charging and vehicle-to-grid seem highly promising methods for EVs control. However, high capital costs remain a barrier to implementation. Meanwhile, incentive and price-based schemes that do not require high level of control can be implemented to influence the EVs' demand. Having effective tools to deal with the increasing level of uncertainty is increasingly important for players, such as energy aggregators. This paper formulates a stochastic model for day-ahead energy resource scheduling, integrated with the dynamic electricity pricing for EVs, to address the challenges brought by the demand and renewable sources uncertainty. The two-stage stochastic programming approach is used to obtain the optimal electricity pricing for EVs. A realistic case study projected for 2030 is presented based on Zaragoza network. The results demonstrate that it is more effective than the deterministic model and that the optimal pricing is preferable. This study indicates that adequate DR schemes like the proposed one are promising to increase the customers' satisfaction in addition to improve the profitability of the energy aggregation business. - Highlights: • A stochastic model for energy scheduling tackling several uncertainty sources. • A two-stage stochastic programming is used to tackle the developed model. • Optimal EV electricity pricing seems to improve the profits. • The propose results suggest to increase the customers' satisfaction.

  3. 76 FR 77271 - Competitive Product Postal Price Changes

    Science.gov (United States)

    2011-12-12

    ... POSTAL REGULATORY COMMISSION [Docket No. CP2012-2; Order No. 997] Competitive Product Postal Price... recently-filed Postal Service request for a change in competitive products prices. The changes will take... and justification for the changes, the effective date, and a schedule of the changed rates. The price...

  4. Dynamic Oligopoly Pricing: Evidence from the Airline Industry

    OpenAIRE

    Siegert, Caspar; Ulbricht, Robert

    2014-01-01

    We explore how pricing dynamics in the European airline industry vary with the competitive environment. Our results highlight substantial variations in pricing dynamics that are consistent with a theory of intertemporal price discrimination. First, the rate at which prices increase towards the scheduled travel date is decreasing in competition, supporting the idea that competition restrains the ability of airlines to price-discriminate. Second, the sensitivity to competition is substantially ...

  5. A Market-Based Approach to Multi-factory Scheduling

    Science.gov (United States)

    Vytelingum, Perukrishnen; Rogers, Alex; MacBeth, Douglas K.; Dutta, Partha; Stranjak, Armin; Jennings, Nicholas R.

    In this paper, we report on the design of a novel market-based approach for decentralised scheduling across multiple factories. Specifically, because of the limitations of scheduling in a centralised manner - which requires a center to have complete and perfect information for optimality and the truthful revelation of potentially commercially private preferences to that center - we advocate an informationally decentralised approach that is both agile and dynamic. In particular, this work adopts a market-based approach for decentralised scheduling by considering the different stakeholders representing different factories as self-interested, profit-motivated economic agents that trade resources for the scheduling of jobs. The overall schedule of these jobs is then an emergent behaviour of the strategic interaction of these trading agents bidding for resources in a market based on limited information and their own preferences. Using a simple (zero-intelligence) bidding strategy, we empirically demonstrate that our market-based approach achieves a lower bound efficiency of 84%. This represents a trade-off between a reasonable level of efficiency (compared to a centralised approach) and the desirable benefits of a decentralised solution.

  6. Solutions for wood-based bio-energy price discovery

    Energy Technology Data Exchange (ETDEWEB)

    Teraes, Timo [FOEX Indexes Ltd., Helsinki (Finland)], e-mail: timo@foex.fi

    2012-11-01

    Energy prices are highly volatile. This volatility can have serious ill-effects on the profitability of companies engaged in the energy business. There are, however, a number of price risk management tools which can be used to reduce the problems caused by price volatility. International trade of wood pellets and wood chips is rapidly growing. A good price transparency helps in developing the trade further. In order to meet the renewable energy targets within the EU, further growth of volumes is needed, at least within Europe and from overseas supply sources to the European markets. Reliable price indices are a central element in price risk management and in general price discovery. Exchanges have provided, in the past, the most widely known price discovery systems. Since 1990's, an increasing number of price risk management tools has been based on cash settlement concept. Cash settlement requires high quality benchmark price indices. These have been developed by the exchanges themselves, by trade press and by independent price benchmark provider companies. The best known of these benchmarks in forest industry and now also in wood-based bioenergy products are the PIX indices, provided by FOEX Indexes Ltd. This presentation discusses the key requirements for a good price index and the different ways of using the indices. Price relationships between wood chip prices and pellet prices are also discussed as will be the outlook for the future volume growth and trade flows in woodchips and pellets mainly from the European perspective.

  7. 48 CFR 538.270 - Evaluation of multiple award schedule (MAS) offers.

    Science.gov (United States)

    2010-10-01

    ... SERVICES ADMINISTRATION SPECIAL CATEGORIES OF CONTRACTING FEDERAL SUPPLY SCHEDULE CONTRACTING Establishing and Administering Federal Supply Schedules 538.270 Evaluation of multiple award schedule (MAS) offers... determining the Government's price negotiation objectives, consider the following factors: (1) Aggregate...

  8. Hierarchical energy and frequency security pricing in a smart microgrid: An equilibrium-inspired epsilon constraint based multi-objective decision making approach

    International Nuclear Information System (INIS)

    Rezaei, Navid; Kalantar, Mohsen

    2015-01-01

    Highlights: • Proposing a multi-objective security pricing mechanism for islanded microgrids. • Generating Pareto points using epsilon constraint methodology. • Best compromise solution using a novel decision making approach. • An equilibrium-inspired technique is used as an efficient decision making method. • Stochastic management of hierarchical reserves in a droop controlled microgrid. - Abstract: The present paper formulates a frequency security constrained energy management system for an islanded microgrid. Static and dynamic securities of the microgrids have been modeled in depth based on droop control paradigm. The derived frequency dependent modeling is incorporated into a multi-objective energy management system. Microgrid central controller is in charge to determine optimal prices of energy and frequency security such that technical, economic and environmental targets are satisfied simultaneously. The associated prices are extracted based on calculating related Lagrange multipliers corresponding to providing the microgrid hourly energy and reserve requirements. Besides, to generate optimal Pareto solutions of the proposed multi-objective framework augmented epsilon constraint method is applied. Moreover, a novel methodology on the basis of Nash equilibrium strategy is devised and employed to select the best compromise solution from the generated Pareto front. Comprehensive analysis tool is implemented in a typical test microgrid and executed over a 24 h scheduling time horizon. The energy, primary and secondary frequency control reserves have been scheduled appropriately in three different case-studies which are defined based on the microgrid various operational policies. The optimization results verify that the operational policies adopted by means of the microgrid central controller have direct impacts on determined energy and security prices. The illustrative implementations can give the microgrid central controller an insight view to provide

  9. Real-time pricing strategy of micro-grid energy centre considering price-based demand response

    Science.gov (United States)

    Xu, Zhiheng; Zhang, Yongjun; Wang, Gan

    2017-07-01

    With the development of energy conversion technology such as power to gas (P2G), fuel cell and so on, the coupling between energy sources becomes more and more closely. Centralized dispatch among electricity, natural gas and heat will become a trend. With the goal of maximizing the system revenue, this paper establishes the model of micro-grid energy centre based on energy hub. According to the proposed model, the real-time pricing strategy taking into account price-based demand response of load is developed. And the influence of real-time pricing strategy on the peak load shifting is discussed. In addition, the impact of wind power predicted inaccuracy on real-time pricing strategy is analysed.

  10. Action dependent heuristic dynamic programming based residential energy scheduling with home energy inter-exchange

    International Nuclear Information System (INIS)

    Xu, Yancai; Liu, Derong; Wei, Qinglai

    2015-01-01

    Highlights: • The algorithm is developed in the two-household energy management environment. • We develop the absent energy penalty cost for the first time. • The algorithm has ability to keep adapting in real-time operations. • Its application can lower total costs and achieve better load balancing. - Abstract: Residential energy scheduling is a hot topic nowadays in the background of energy saving and environmental protection worldwide. To achieve this objective, a new residential energy scheduling algorithm is developed for energy management, based on action dependent heuristic dynamic programming. The algorithm works under the circumstance of residential real-time pricing and two adjacent housing units with energy inter-exchange, which can reduce the overall cost and enhance renewable energy efficiency after long-term operation. It is designed to obtain the optimal control policy to manage the directions and amounts of electricity energy flux. The algorithm’s architecture is mainly constructed based on neural networks, denoting the learned characteristics in the linkage of layers. To get close to real situations, many constraints such as maximum charging/discharging power of batteries are taken into account. The absent energy penalty cost is developed for the first time as a part of the performance index function. When the environment changes, the residential energy scheduling algorithm gains new features and keeps adapting in real-time operations. Simulation results show that the developed algorithm is beneficial to energy conversation

  11. On Nonlinear Prices in Timed Automata

    Directory of Open Access Journals (Sweden)

    Devendra Bhave

    2016-12-01

    Full Text Available Priced timed automata provide a natural model for quantitative analysis of real-time systems and have been successfully applied in various scheduling and planning problems. The optimal reachability problem for linearly-priced timed automata is known to be PSPACE-complete. In this paper we investigate priced timed automata with more general prices and show that in the most general setting the optimal reachability problem is undecidable. We adapt and implement the construction of Audemard, Cimatti, Kornilowicz, and Sebastiani for non-linear priced timed automata using state-of-the-art theorem prover Z3 and present some preliminary results.

  12. Bumpless Transfer between Observer-based Gain Scheduled Controllers

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Stoustrup, Jakob; Trangbæk, Klaus

    2005-01-01

    This paper deals with bumpless transfer between a number of observer-based controllers in a gain scheduling architecture. Linear observer-based controllers are designed for a number of linear approximations of a nonlinear system in a set of operating points, and gain scheduling control can...

  13. 76 FR 4395 - Postal Service Price Adjustment

    Science.gov (United States)

    2011-01-25

    ... pricing design changes in First-Class Mail. One involves the introduction of two separate pricing... the value of the services the accounting fee supports and the goal of recovering institutional costs... INFORMATION: I. Introduction II. Class-Specific Summary III. Preferred Mail IV. Mail Classification Schedule...

  14. Future aircraft networks and schedules

    Science.gov (United States)

    Shu, Yan

    2011-07-01

    Because of the importance of air transportation scheduling, the emergence of small aircraft and the vision of future fuel-efficient aircraft, this thesis has focused on the study of aircraft scheduling and network design involving multiple types of aircraft and flight services. It develops models and solution algorithms for the schedule design problem and analyzes the computational results. First, based on the current development of small aircraft and on-demand flight services, this thesis expands a business model for integrating on-demand flight services with the traditional scheduled flight services. This thesis proposes a three-step approach to the design of aircraft schedules and networks from scratch under the model. In the first step, both a frequency assignment model for scheduled flights that incorporates a passenger path choice model and a frequency assignment model for on-demand flights that incorporates a passenger mode choice model are created. In the second step, a rough fleet assignment model that determines a set of flight legs, each of which is assigned an aircraft type and a rough departure time is constructed. In the third step, a timetable model that determines an exact departure time for each flight leg is developed. Based on the models proposed in the three steps, this thesis creates schedule design instances that involve almost all the major airports and markets in the United States. The instances of the frequency assignment model created in this thesis are large-scale non-convex mixed-integer programming problems, and this dissertation develops an overall network structure and proposes iterative algorithms for solving these instances. The instances of both the rough fleet assignment model and the timetable model created in this thesis are large-scale mixed-integer programming problems, and this dissertation develops subproblem schemes for solving these instances. Based on these solution algorithms, this dissertation also presents

  15. Economic analysis of coal price-electricity price adjustment in China based on the CGE model

    International Nuclear Information System (INIS)

    He, Y.X.; Zhang, S.L.; Yang, L.Y.; Wang, Y.J.; Wang, J.

    2010-01-01

    In recent years, coal price has risen rapidly, which has also brought a sharp increase in the expenditures of thermal power plants in China. Meantime, the power production price and power retail price have not been adjusted accordingly and a large number of thermal power plants have incurred losses. The power industry is a key industry in the national economy. As such, a thorough analysis and evaluation of the economic influence of the electricity price should be conducted before electricity price adjustment is carried out. This paper analyses the influence of coal price adjustment on the electric power industry, and the influence of electricity price adjustment on the macroeconomy in China based on computable general equilibrium models. The conclusions are as follows: (1) a coal price increase causes a rise in the cost of the electric power industry, but the influence gradually descends with increase in coal price; and (2) an electricity price increase has an adverse influence on the total output, Gross Domestic Product (GDP), and the Consumer Price Index (CPI). Electricity price increases have a contractionary effect on economic development and, consequently, electricity price policy making must consequently consider all factors to minimize their adverse influence.

  16. Providing frequency regulation reserve services using demand response scheduling

    International Nuclear Information System (INIS)

    Motalleb, Mahdi; Thornton, Matsu; Reihani, Ehsan; Ghorbani, Reza

    2016-01-01

    Highlights: • Proposing a market model for contingency reserve services using demand response. • Considering transient limitations of grid frequency for inverter-based generations. • Price-sensitive scheduling of residential batteries and water heaters using dynamic programming. • Calculating the profits of both generation companies and demand response aggregators. - Abstract: During power grid contingencies, frequency regulation is a primary concern. Historically, frequency regulation during contingency events has been the sole responsibility of the power utility. We present a practical method of using distributed demand response scheduling to provide frequency regulation during contingency events. This paper discusses the implementation of a control system model for the use of distributed energy storage systems such as battery banks and electric water heaters as a source of ancillary services. We present an algorithm which handles the optimization of demand response scheduling for normal operation and during contingency events. We use dynamic programming as an optimization tool. A price signal is developed using optimal power flow calculations to determine the locational marginal price of electricity, while sensor data for water usage is also collected. Using these inputs to dynamic programming, the optimal control signals are given as output. We assume a market model in which distributed demand response resources are sold as a commodity on the open market and profits from demand response aggregators as brokers of distributed demand response resources can be calculated. In considering control decisions for regulation of transient changes in frequency, we focus on IEEE standard 1547 in order to prevent the safety shut-off of inverter-based generation and further exacerbation of frequency droop. This method is applied to IEEE case 118 as a demonstration of the method in practice.

  17. The Price-Anderson Act

    International Nuclear Information System (INIS)

    Jones, R.

    2000-01-01

    The Price-Anderson Act establishes nuclear liability law in the United States. First passed in 1957, it has influenced other nuclear liability legislation around the world. The insurer response the nuclear accident at Three Mile Island in 1979 demonstrates the application of the Act in a real life situation. The Price-Anderson Act is scheduled to be renewed in 2002, and the future use of commercial nuclear power in tge United States will be influenced by this renewal. (author)

  18. Nonlinear Pricing in Markets with Interdependent Demand

    OpenAIRE

    Shmuel S. Oren; Stephen A. Smith; Robert B. Wilson

    1982-01-01

    This paper provides a mathematical framework for modeling demand and determining optimal price schedules in markets which have demand externalities and can sustain nonlinear pricing. These fundamental economic concepts appear in the marketplace in the form of mutual buyers' benefits and quantity discounts. The theory addressing these aspects is relevant to a wide variety of goods and services. Examples include tariffs for electronic communications services, pricing of franchises, and royalty ...

  19. Discount-Optimal Infinite Runs in Priced Timed Automata

    DEFF Research Database (Denmark)

    Fahrenberg, Uli; Larsen, Kim Guldstrand

    2009-01-01

    We introduce a new discounting semantics for priced timed automata. Discounting provides a way to model optimal-cost problems for infinite traces and has applications in optimal scheduling and other areas. In the discounting semantics, prices decrease exponentially, so that the contribution...

  20. The Value of Negotiating Cost-Based Transfer Prices

    Directory of Open Access Journals (Sweden)

    Anne Chwolka

    2010-10-01

    Full Text Available This paper analyzes the potential of one-step transfer prices based on either variable or full costs for coordinating decentralized production and quality-improving investment decisions. Transfer prices based on variable costs fail to induce investments on the upstream stage. In contrast, transfer prices based on full costs provide strong investment incentives for the upstream divisions. However, they fail to coordinate the investment decisions. We show that negotiations prevent such coordination failure. In particular, we find that the firm benefits from a higher degree of decentralization so that total profit increases in the number of parameters being subject to negotiations.

  1. Economic and environmental scheduling of smart homes with microgrid: DER operation and electrical tasks

    International Nuclear Information System (INIS)

    Zhang, Di; Evangelisti, Sara; Lettieri, Paola; Papageorgiou, Lazaros G.

    2016-01-01

    Highlights: • An MILP model is formulated for energy consumption scheduling among smart homes. • Environmental and economic aspects are both addressed. • The model is implemented on an example with data profiles from the UK. • Pareto-optimal curves between cost and CO_2 emissions are obtained. • Real-time pricing and critical peak pricing schemes are investigated. - Abstract: Microgrids are promising in reducing energy consumption and carbon emissions, compared with the current centralised energy generation systems. Smart homes are becoming popular for their lower energy cost and provision of comfort. Flexible energy-consuming household tasks can be scheduled co-ordinately among multiple smart homes to reduce economic cost and CO_2. However, the electricity tariff is not always positively correlated with CO_2 intensity. In this work, a mixed integer linear programming (MILP) model is proposed to schedule the energy consumption within smart homes using a microgrid system. The daily power consumption tasks are scheduled by coupling environmental and economic sustainability in a multi-objective optimisation with ε-constraint method. The two conflicting objectives are to minimise the daily energy cost and CO_2 emissions. Distributed energy resources (DER) operation and electricity-consumption household tasks are scheduled based on electricity tariff, CO_2 intensity and electricity task time window. The proposed model is implemented on a smart building of 30 homes under three different price schemes. Electricity tariff and CO_2 intensity profiles of the UK are employed for the case study. The Pareto curves for cost and CO_2 emissions present the trade-off between the two conflicting objectives.

  2. 76 FR 13902 - Fair Credit Reporting Risk-Based Pricing Regulations

    Science.gov (United States)

    2011-03-15

    ... TRADE COMMISSION 16 CFR Parts 640 and 698 RIN R411009 Fair Credit Reporting Risk-Based Pricing... respective risk-based pricing rules to require disclosure of credit scores and information relating to credit scores in risk-based pricing notices if a credit score of the consumer is used in setting the material...

  3. Security-constrained self-scheduling of generation companies in day-ahead electricity markets considering financial risk

    International Nuclear Information System (INIS)

    Amjady, Nima; Vahidinasab, Vahid

    2013-01-01

    Highlights: ► A security-constrained self-scheduling is presented. ► The proposed framework takes into account the uncertainty of the predicted market prices. ► We model the risk and profit tradeoff of a GENCO based on an efficient multi-objective model. ► Unit commitment and inter-temporal constraints of generators are considered in an MIP model. ► Simulation results are presented on the IEEE 30-bus and IEEE 118-bus test systems. - Abstract: In this paper, a new security-constrained self-scheduling framework incorporating the transmission flow limits in both steady state conditions and post-contingent states is presented to produce efficient bidding strategy for generation companies (GENCOs) in day-ahead electricity markets. Moreover, the proposed framework takes into account the uncertainty of the predicted market prices and models the risk and profit tradeoff of a GENCO based on an efficient multi-objective model. Furthermore, unit commitment and inter-temporal constraints of generators are considered in the suggested model converting it to a mixed-integer programming (MIP) optimization problem. Sensitivity of the proposed framework with respect to both the level of the market prices and adopted risk level is also evaluated in the paper. Simulation results are presented on the IEEE 30-bus and IEEE 118-bus test systems illustrating the performance of the proposed self-scheduling model.

  4. A Novel Assembly Line Scheduling Algorithm Based on CE-PSO

    Directory of Open Access Journals (Sweden)

    Xiaomei Hu

    2015-01-01

    Full Text Available With the widespread application of assembly line in enterprises, assembly line scheduling is an important problem in the production since it directly affects the productivity of the whole manufacturing system. The mathematical model of assembly line scheduling problem is put forward and key data are confirmed. A double objective optimization model based on equipment utilization and delivery time loss is built, and optimization solution strategy is described. Based on the idea of solution strategy, assembly line scheduling algorithm based on CE-PSO is proposed to overcome the shortcomings of the standard PSO. Through the simulation experiments of two examples, the validity of the assembly line scheduling algorithm based on CE-PSO is proved.

  5. Optimal Residential Load Scheduling Under Utility and Rooftop Photovoltaic Units

    Directory of Open Access Journals (Sweden)

    Ghulam Hafeez

    2018-03-01

    Full Text Available With the rapid advancement in technology, electrical energy consumption is increasing rapidly. Especially, in the residential sector, more than 80% of electrical energy is being consumed because of consumer negligence. This brings the challenging task of maintaining the balance between the demand and supply of electric power. In this paper, we focus on the problem of load balancing via load scheduling under utility and rooftop photovoltaic (PV units to reduce electricity cost and peak to average ratio (PAR in demand-side management. For this purpose, we adopted genetic algorithm (GA, binary particle swarm optimization (BPSO, wind-driven optimization (WDO, and our proposed genetic WDO (GWDO algorithm, which is a hybrid of GA and WDO, to schedule the household load. For energy cost estimation, combined real-time pricing (RTP and inclined block rate (IBR were used. The proposed algorithm shifts load from peak consumption hours to off-peak hours based on combined pricing scheme and generation from rooftop PV units. Simulation results validate our proposed GWDO algorithm in terms of electricity cost and PAR reduction while considering all three scenarios which we have considered in this work: (1 load scheduling without renewable energy sources (RESs and energy storage system (ESS, (2 load scheduling with RESs, and (3 load scheduling with RESs and ESS. Furthermore, our proposed scheme reduced electricity cost and PAR by 22.5% and 29.1% in scenario 1, 47.7% and 30% in scenario 2, and 49.2% and 35.4% in scenario 3, respectively, as compared to unscheduled electricity consumption.

  6. Market based solutions for power pricing

    International Nuclear Information System (INIS)

    Wangensteen, Ivar

    2002-06-01

    The report examines how the price for effect reserves, spot market power and regulated power is formed provided ideal market conditions rule. Primarily the price determining factors in a market for power reserves are examined and how the connection between this market and the energy market (the spot market) is. In a free market there would be a balance between what the actors may obtain by operating in the open market for power reserves/regulated power on the one hand and the market for spot power on the other. Primarily we suppose that the desired amount of power reserve is known. Secondly the problem constellation is extended to comprise the size of the effect reserves i.e. the optimising of the requirement to the power reserves. The optimal amount of power reserves is obtained when there is a balance between the cost and the benefit. This optimal balance is achieved when expected macro economical loss due to outfacing balances against the cost of maintaining larger reserves. By using a simple model it is demonstrated that a system operator regulates the maximal price in the regulated market and this equals the rationing price. The actors will offer sufficient reserves even if the reserve price is zero (provided risk neutrality). If the maximal price for regulated power is lower the price of effect reserves will rise. Based on the same simple model calculations are made for how short and long term market balance will be for increasing demands

  7. The applicability of knowledge-based scheduling to the utilities industry

    International Nuclear Information System (INIS)

    Yoshimoto, G.; Gargan, R. Jr.; Duggan, P.

    1992-01-01

    The Electric Power Research Institute (EPRI), Nuclear Power Division, has identified the three major goals of high technology applications for nuclear power plants. These goals are to enhance power production through increasing power generation efficiency, to increase productivity of the operations, and to reduce the threats to the safety of the plant. Our project responds to the second goal by demonstrating that significant productivity increases can be achieved for outage maintenance operations based on existing knowledge-based scheduling technology. Its use can also mitigate threats to potential safety problems by means of the integration of risk assessment features into the scheduler. The scheduling approach uses advanced techniques enabling the automation of the routine scheduling decision process that previously was handled by people. The process of removing conflicts in scheduling is automated. This is achieved by providing activity representations that allow schedulers to express a variety of different scheduling constraints and by implementing scheduling mechanisms that simulate kinds of processes that humans use to find better solutions from a large number of possible solutions. This approach allows schedulers to express detailed constraints between activities and other activities, resources (material and personnel), and requirements that certain states exist for their execution. Our scheduler has already demonstrated its benefit to improving the shuttle processing flow management at Kennedy Space Center. Knowledge-based scheduling techniques should be examined by utilities industry researchers, developers, operators and management for application to utilities planning problems because of its great cost benefit potential. 4 refs., 4 figs

  8. 48 CFR 915.404-4-71-5 - Fee schedules.

    Science.gov (United States)

    2010-10-01

    ... METHODS AND CONTRACT TYPES CONTRACTING BY NEGOTIATION Contract Pricing 915.404-4-71-5 Fee schedules. (a... subcontracting, normal contractor services performed by the government or another contractor: (1) The target fee...) The target fee schedule provides for 45 percent of the contract work to be subcontracted for such...

  9. Pricing and competition in the private dental market in Finland.

    Science.gov (United States)

    Widström, E; Väisänen, A; Mikkola, H

    2011-06-01

    To investigate how the prices were set in private dental care, which factors determined prices and whether the recent National Dental Care Reform had increased competition in the dental care market in Finland. A questionnaire to all full time private dentists (n = 1,121) in the ten largest cities. Characteristics of the practice, prices charged, price setting, perceived competition and expectations for the practices were requested. The response rate was 59.6%. Correlation analysis (Pearson's) was used to study relationships between the prices of different treatment items. Linear regression analysis was used to study determinants of the price of a one surface filling. Most dentists' fee schedules were based on the price of a one surface filling and updated annually. Changes in practice costs calculated by the dentists' professional association and information on average prices charged on dental treatments in the country influenced pricing. High price levels were associated with specialisation, working in a group practice, working close to many other practices or in a town with a dental school. Less than half of the respondents had faced competition in dental services and price competition was insignificant. Price setting followed traditional patterns and private markets in dental services were not found to be very competitive.

  10. Determining optimal selling price and lot size with process reliability and partial backlogging considerations

    Science.gov (United States)

    Hsieh, Tsu-Pang; Cheng, Mei-Chuan; Dye, Chung-Yuan; Ouyang, Liang-Yuh

    2011-01-01

    In this article, we extend the classical economic production quantity (EPQ) model by proposing imperfect production processes and quality-dependent unit production cost. The demand rate is described by any convex decreasing function of the selling price. In addition, we allow for shortages and a time-proportional backlogging rate. For any given selling price, we first prove that the optimal production schedule not only exists but also is unique. Next, we show that the total profit per unit time is a concave function of price when the production schedule is given. We then provide a simple algorithm to find the optimal selling price and production schedule for the proposed model. Finally, we use a couple of numerical examples to illustrate the algorithm and conclude this article with suggestions for possible future research.

  11. Price Comparisons on the Internet Based on Computational Intelligence

    Science.gov (United States)

    Kim, Jun Woo; Ha, Sung Ho

    2014-01-01

    Information-intensive Web services such as price comparison sites have recently been gaining popularity. However, most users including novice shoppers have difficulty in browsing such sites because of the massive amount of information gathered and the uncertainty surrounding Web environments. Even conventional price comparison sites face various problems, which suggests the necessity of a new approach to address these problems. Therefore, for this study, an intelligent product search system was developed that enables price comparisons for online shoppers in a more effective manner. In particular, the developed system adopts linguistic price ratings based on fuzzy logic to accommodate user-defined price ranges, and personalizes product recommendations based on linguistic product clusters, which help online shoppers find desired items in a convenient manner. PMID:25268901

  12. Aspects if stochastic models for short-term hydropower scheduling and bidding

    Energy Technology Data Exchange (ETDEWEB)

    Belsnes, Michael Martin [Sintef Energy, Trondheim (Norway); Follestad, Turid [Sintef Energy, Trondheim (Norway); Wolfgang, Ove [Sintef Energy, Trondheim (Norway); Fosso, Olav B. [Dep. of electric power engineering NTNU, Trondheim (Norway)

    2012-07-01

    This report discusses challenges met when turning from deterministic to stochastic decision support models for short-term hydropower scheduling and bidding. The report describes characteristics of the short-term scheduling and bidding problem, different market and bidding strategies, and how a stochastic optimization model can be formulated. A review of approaches for stochastic short-term modelling and stochastic modelling for the input variables inflow and market prices is given. The report discusses methods for approximating the predictive distribution of uncertain variables by scenario trees. Benefits of using a stochastic over a deterministic model are illustrated by a case study, where increased profit is obtained to a varying degree depending on the reservoir filling and price structure. Finally, an approach for assessing the effect of using a size restricted scenario tree to approximate the predictive distribution for stochastic input variables is described. The report is a summary of the findings of Work package 1 of the research project #Left Double Quotation Mark#Optimal short-term scheduling of wind and hydro resources#Right Double Quotation Mark#. The project aims at developing a prototype for an operational stochastic short-term scheduling model. Based on the investigations summarized in the report, it is concluded that using a deterministic equivalent formulation of the stochastic optimization problem is convenient and sufficient for obtaining a working prototype. (author)

  13. MARKET SIGNALS IN VALUE-BASED PRICING PREMIUMS AND DISCOUNTS

    OpenAIRE

    Feuz, Dillon M.

    1999-01-01

    There is concern in the beef industry that present marketing practices may be impending the transmission of economic signals from consumers to producers. Presently, fed cattle may be sold on a show list, pen-by-pen, or on an individual head basis, and may be priced using live weight, dressed weight, or grid or formula pricing. Market signals are more likely to reach producers if cattle are priced individually. Current value-based pricing are discussed. Three grid pricing systems are evaluated...

  14. PLACEMENT APPLICATIONS SCHEDULING LECTURE IN INTERNATIONAL PROGRAM UNIKOM BASED ANDROID

    Directory of Open Access Journals (Sweden)

    Andri Sahata Sitanggang

    2017-12-01

    Full Text Available One who determines life of a classroom namely mapping scheduling courses especially at college. The process scheduling has included time or schedule of a class of available, room available, lecture who is scheduled for, and schedule for lecturer going to teach. Hopefully with a scheduling it will facilitate the students and teachers in obtaining information lecture schedule. With the emergence of the android application ( is implanted in mobile phones , the public can now use the internet so fast that is based .So with that researchers give one a technology based solutions to build android application .This is because one of the technology has given the functions which may make it easier for students and university lecturers in terms of access to information. In building this application used method of the prototype consisting 2 access namely access user and admin , where module user consisting of modules register , login , scheduling module , while for admin given module login , register and arrangement information scheduling courses both the administration and lecturers .Application made will be integrated with internet so that this program is real-time application.

  15. Agent-based transportation planning compared with scheduling heuristics

    NARCIS (Netherlands)

    Mes, Martijn R.K.; van der Heijden, Matthijs C.; van Harten, Aart

    2004-01-01

    Here we consider the problem of dynamically assigning vehicles to transportation orders that have di¤erent time windows and should be handled in real time. We introduce a new agent-based system for the planning and scheduling of these transportation networks. Intelligent vehicle agents schedule

  16. Microgrids Real-Time Pricing Based on Clustering Techniques

    Directory of Open Access Journals (Sweden)

    Hao Liu

    2018-05-01

    Full Text Available Microgrids are widely spreading in electricity markets worldwide. Besides the security and reliability concerns for these microgrids, their operators need to address consumers’ pricing. Considering the growth of smart grids and smart meter facilities, it is expected that microgrids will have some level of flexibility to determine real-time pricing for at least some consumers. As such, the key challenge is finding an optimal pricing model for consumers. This paper, accordingly, proposes a new pricing scheme in which microgrids are able to deploy clustering techniques in order to understand their consumers’ load profiles and then assign real-time prices based on their load profile patterns. An improved weighted fuzzy average k-means is proposed to cluster load curve of consumers in an optimal number of clusters, through which the load profile of each cluster is determined. Having obtained the load profile of each cluster, real-time prices are given to each cluster, which is the best price given to all consumers in that cluster.

  17. Microcomputer-based workforce scheduling for hospital porters.

    Science.gov (United States)

    Lin, C K

    1999-01-01

    This paper focuses on labour scheduling for hospital porters who are the major workforce providing routine cleansing of wards, transportation and messenger services. Generating an equitable monthly roster for porters while meeting the daily minimum demand is a tedious task scheduled manually by a supervisor. In considering a variety of constraints and goals, a manual schedule was usually produced in seven to ten days. To be in line with the strategic goal of scientific management of an acute care regional hospital in Hong Kong, a microcomputer-based algorithm was developed to schedule the monthly roster. The algorithm, coded in Digital Visual Fortran 5.0 Professional, could generate a monthly roster in seconds. Implementation has been carried out since September 1998 and the results proved to be useful to hospital administrators and porters. This paper discusses both the technical and human issues involved during the computerization process.

  18. Drug pricing and reimbursement information management: processes and decision making in the global economy.

    Science.gov (United States)

    Tsourougiannis, Dimitrios

    2017-01-01

    Background : Cost-containment initiatives are re-shaping the pharmaceutical business environment and affecting market access as well as pricing and reimbursement decisions. Effective price management procedures are too complex to accomplish manually. Prior to February 2013, price management within Astellas Pharma Europe Ltd was done manually using an Excel database. The system was labour intensive, slow to update, and prone to error. An innovative web-based pricing information management system was developed to address the shortcomings of the previous system. Development : A secure web-based system for submitting, reviewing and approving pricing requests was designed to: track all pricing applications and approval status; update approved pricing information automatically; provide fixed and customizable reports of pricing information; collect pricing and reimbursement rules from each country; validate pricing and reimbursement rules monthly. Several sequential phases of development emphasized planning, time schedules, target dates, budgets and implementation of the entire system. A test system was used to pilot the electronic (e)-pricing system with three affiliates (four users) in February 2013. Outcomes : The web-based system was introduced in March 2013, currently has about 227 active users globally and comprises more than 1000 presentations of 150 products. The overall benefits of switching from a manual to an e-pricing system were immediate and highly visible in terms of efficiency, transparency, reliability and compliance. Conclusions : The e-pricing system has improved the efficiency, reliability, compliance, transparency and ease of access to multinational drug pricing and approval information.

  19. Comparing Book- and Tablet-Based Picture Activity Schedules: Acquisition and Preference.

    Science.gov (United States)

    Giles, Aimee; Markham, Victoria

    2017-09-01

    Picture activity schedules consist of a sequence of images representing the order of tasks for a person to complete. Although, picture activity schedules have traditionally been presented in a book format, recently picture activity schedules have been evaluated on technological devices such as an iPod™ touch. The present study compared the efficiency of picture activity schedule acquisition on book- and tablet-based modalities. In addition, participant preference for each modality was assessed. Three boys aged below 5 years with a diagnosis of autism participated. Participants were taught to follow the schedules using both modalities. Following mastery of each modality of picture activity schedule, a concurrent-chains preference assessment was conducted to evaluate participant preference for each modality. Differences in acquisition rates across the two modalities were marginal. Preference for book- or tablet-based schedules was idiosyncratic across participants.

  20. Power Transmission Scheduling for Generators in a Deregulated Environment Based on a Game-Theoretic Approach

    Directory of Open Access Journals (Sweden)

    Bingtuan Gao

    2015-12-01

    Full Text Available In a deregulated environment of the power market, in order to lower their energy price and guarantee the stability of the power network, appropriate transmission lines have to be considered for electricity generators to sell their energy to the end users. This paper proposes a game-theoretic power transmission scheduling for multiple generators to lower their wheeling cost. Based on the embedded cost method, a wheeling cost model consisting of congestion cost, cost of losses and cost of transmission capacity is presented. By assuming each generator behaves in a selfish and rational way, the competition among the multiple generators is formulated as a non-cooperative game, where the players are the generators and the strategies are their daily schedules of power transmission. We will prove that there exists at least one pure-strategy Nash equilibrium of the formulated power transmission game. Moreover, a distributed algorithm will be provided to realize the optimization in terms of minimizing the wheeling cost. Finally, simulations were performed and discussed to verify the feasibility and effectiveness of the proposed non-cooperative game approach for the generators in a deregulated environment.

  1. Effect of the accuracy of price forecasting on profit in a Price Based Unit Commitment

    International Nuclear Information System (INIS)

    Delarue, Erik; Van Den Bosch, Pieterjan; D'haeseleer, William

    2010-01-01

    This paper discusses and quantifies the so-called loss of profit (i.e., the sub-optimality of profit) that can be expected in a Price Based Unit Commitment (PBUC), when incorrect price forecasts are used. For this purpose, a PBUC model has been developed and utilized, using Mixed Integer Linear Programming (MILP). Simulations are used to determine the relationship between the Mean Absolute Percentage Error (MAPE) of a certain price forecast and the loss of profit, for four different types of power plants. A Combined Cycle (CC) power plant and a pumped storage unit show highest sensitivity to incorrect forecasts. A price forecast with a MAPE of 15%, on average, yields 13.8% and 12.1% profit loss, respectively. A classic thermal power plant (coal fired) and cascade hydro unit are less affected by incorrect forecasts, with only 2.4% and 2.0% profit loss, respectively, at the same price forecast MAPE. This paper further demonstrates that if price forecasts show an average bias (upward or downward), using the MAPE as measure of the price forecast might not be sufficient to quantify profit loss properly. Profit loss in this case has been determined as a function of both shift and MAPE of the price forecast. (author)

  2. 48 CFR 552.216-70 - Economic Price Adjustment-FSS Multiple Award Schedule Contracts.

    Science.gov (United States)

    2010-10-01

    ... ___* percent of the original contract unit price. The Government reserves the right to raise this ceiling where... price increase. (e) The Government reserves the right to exercise one of the following options: (1... 48 Federal Acquisition Regulations System 4 2010-10-01 2010-10-01 false Economic Price Adjustment...

  3. Distributed Research Project Scheduling Based on Multi-Agent Methods

    Directory of Open Access Journals (Sweden)

    Constanta Nicoleta Bodea

    2011-01-01

    Full Text Available Different project planning and scheduling approaches have been developed. The Operational Research (OR provides two major planning techniques: CPM (Critical Path Method and PERT (Program Evaluation and Review Technique. Due to projects complexity and difficulty to use classical methods, new approaches were developed. Artificial Intelligence (AI initially promoted the automatic planner concept, but model-based planning and scheduling methods emerged later on. The paper adresses the project scheduling optimization problem, when projects are seen as Complex Adaptive Systems (CAS. Taken into consideration two different approaches for project scheduling optimization: TCPSP (Time- Constrained Project Scheduling and RCPSP (Resource-Constrained Project Scheduling, the paper focuses on a multiagent implementation in MATLAB for TCSP. Using the research project as a case study, the paper includes a comparison between two multi-agent methods: Genetic Algorithm (GA and Ant Colony Algorithm (ACO.

  4. Fast Lagrangian relaxation for constrained generation scheduling in a centralized electricity market

    International Nuclear Information System (INIS)

    Ongsakul, Weerakorn; Petcharaks, Nit

    2008-01-01

    This paper proposes a fast Lagrangian relaxation (FLR) for constrained generation scheduling (CGS) problem in a centralized electricity market. FLR minimizes the consumer payment rather than the total supply cost subject to the power balance, spinning reserve, transmission line, and generator operating constraints. FLR algorithm is improved by new initialization of Lagrangian multipliers and adaptive adjustment of Lagrangian multipliers. The adaptive subgradient method using high quality initial feasible multipliers requires much less number of iterations to converge, leading to a faster computational time. If congestion exists, the alleviating congestion index is proposed for congestion management. Finally, the unit decommitment is performed to prevent excessive spinning reserve. The FLR for CGS is tested on the 4 unit and the IEEE 24 bus reliability test systems. The proposed uniform electricity price results in a lower consumer payment than system marginal price based on uniformly fixed cost amortized allocation, non-uniform price, and electricity price incorporating side payment, leading to a lower electricity price. In addition, observations on objective functions, pricing scheme comparison and interpretation of Lagrangian multipliers are provided. (author)

  5. Agent-Based Modeling of Day-Ahead Real Time Pricing in a Pool-Based Electricity Market

    Directory of Open Access Journals (Sweden)

    Sh. Yousefi

    2011-09-01

    Full Text Available In this paper, an agent-based structure of the electricity retail market is presented based on which day-ahead (DA energy procurement for customers is modeled. Here, we focus on operation of only one Retail Energy Provider (REP agent who purchases energy from DA pool-based wholesale market and offers DA real time tariffs to a group of its customers. As a model of customer response to the offered real time prices, an hourly acceptance function is proposed in order to represent the hourly changes in the customer’s effective demand according to the prices. Here, Q-learning (QL approach is applied in day-ahead real time pricing for the customers enabling the REP agent to discover which price yields the most benefit through a trial-and-error search. Numerical studies are presented based on New England day-ahead market data which include comparing the results of RTP based on QL approach with that of genetic-based pricing.

  6. Adaptive Priority-Based Downlink Scheduling for WiMAX Networks

    OpenAIRE

    Wu, Shih-Jung; Huang, Shih-Yi; Huang, Kuo-Feng

    2012-01-01

    Supporting quality of service (QoS) guarantees for diverse multimedia services are the primary concerns for WiMAX (IEEE 802.16) networks. A scheduling scheme that satisfies QoS requirements has become more important for wireless communications. We propose a downlink scheduling scheme called adaptive priority-based downlink scheduling (APDS) for providing QoS guarantees in IEEE 802.16 networks. APDS comprises two major components: priority assignment and resource allocation. Different service-...

  7. Some fundamental technical concepts about cost based transmission pricing

    International Nuclear Information System (INIS)

    Shirmohammadi, D.; Filho, X.V.; Gorenstin, B.; Pereira, M.V.P.

    1996-01-01

    In this paper the authors describe the basic technical concepts involved in developing cost based transmission prices. They introduce the concepts of transmission pricing paradigms and methodologies to better illustrate how transmission costs are transformed into transmission prices. The authors also briefly discuss the role of these paradigms and methodologies in promoting ''economic efficiency'' which is narrowly defined in this paper. They conclude the paper with an example of the application of some of these paradigms and methodologies for pricing transmission services in Brazil

  8. Dynamic Pricing

    DEFF Research Database (Denmark)

    Sharifi, Reza; Anvari-Moghaddam, Amjad; Fathi, S. Hamid

    2017-01-01

    Dynamic pricing scheme, also known as real-time pricing (RTP), can be more efficient and technically beneficial than the other price-based schemes (such as flat-rate or time-of-use (TOU) pricing) for enabling demand response (DR) actions. Over the past few years, advantages of RTP-based schemes h...... of dynamic pricing can lead to increased willingness of consumers to participate in DR programs which in turn improve the operation of liberalized electricity markets.......Dynamic pricing scheme, also known as real-time pricing (RTP), can be more efficient and technically beneficial than the other price-based schemes (such as flat-rate or time-of-use (TOU) pricing) for enabling demand response (DR) actions. Over the past few years, advantages of RTP-based schemes...

  9. Power generation scheduling. A free market based procedure with reserve constraints included

    International Nuclear Information System (INIS)

    Huse, Einar Staale

    1998-01-01

    This thesis deals with the short-term scheduling of electric power generation in a competitive market. This involves determination of start-ups and shut-downs, and production levels of all units in all hours of the optimization period, considering unit characteristics and system restrictions. The unit characteristics and restrictions handled are minimum and maximum production levels, fuel cost function, start-up costs, minimum up time and minimum down time. The system restrictions handled are power balance (supply equals demand in all hours) and spinning reserve requirement. The thesis has two main contributions: (1) A new organization of an hourly electric power market that simultaneously sets the price of both energy and reserve power is proposed. A power exchange is used as a trading place for electricity. Its responsibility is to balance supply and demand bids and to secure enough spinning reserve. Routines for bidding and market clearing are developed. (2) A computer programme that simulates the proposed electricity market has been implemented. The program can also be used as a new method for solving the single owner generation scheduling problem. Simulations show that the performance of the program is excellent. Simulations also show that it is possible to obtain efficient schedules through the proposed electricity market. 37 refs., 20 figs., 15 tabs

  10. Power generation scheduling. A free market based procedure with reserve constraints included

    Energy Technology Data Exchange (ETDEWEB)

    Huse, Einar Staale

    1999-12-31

    This thesis deals with the short-term scheduling of electric power generation in a competitive market. This involves determination of start-ups and shut-downs, and production levels of all units in all hours of the optimization period, considering unit characteristics and system restrictions. The unit characteristics and restrictions handled are minimum and maximum production levels, fuel cost function, start-up costs, minimum up time and minimum down time. The system restrictions handled are power balance (supply equals demand in all hours) and spinning reserve requirement. The thesis has two main contributions: (1) A new organization of an hourly electric power market that simultaneously sets the price of both energy and reserve power is proposed. A power exchange is used as a trading place for electricity. Its responsibility is to balance supply and demand bids and to secure enough spinning reserve. Routines for bidding and market clearing are developed. (2) A computer programme that simulates the proposed electricity market has been implemented. The program can also be used as a new method for solving the single owner generation scheduling problem. Simulations show that the performance of the program is excellent. Simulations also show that it is possible to obtain efficient schedules through the proposed electricity market. 37 refs., 20 figs., 15 tabs.

  11. Power generation scheduling. A free market based procedure with reserve constraints included

    Energy Technology Data Exchange (ETDEWEB)

    Huse, Einar Staale

    1998-12-31

    This thesis deals with the short-term scheduling of electric power generation in a competitive market. This involves determination of start-ups and shut-downs, and production levels of all units in all hours of the optimization period, considering unit characteristics and system restrictions. The unit characteristics and restrictions handled are minimum and maximum production levels, fuel cost function, start-up costs, minimum up time and minimum down time. The system restrictions handled are power balance (supply equals demand in all hours) and spinning reserve requirement. The thesis has two main contributions: (1) A new organization of an hourly electric power market that simultaneously sets the price of both energy and reserve power is proposed. A power exchange is used as a trading place for electricity. Its responsibility is to balance supply and demand bids and to secure enough spinning reserve. Routines for bidding and market clearing are developed. (2) A computer programme that simulates the proposed electricity market has been implemented. The program can also be used as a new method for solving the single owner generation scheduling problem. Simulations show that the performance of the program is excellent. Simulations also show that it is possible to obtain efficient schedules through the proposed electricity market. 37 refs., 20 figs., 15 tabs.

  12. List prices vs. bargain prices: which solution to estimate consumer price indices?

    OpenAIRE

    Carlo De Gregorio

    2010-01-01

    Alternative approaches to CPI surveys are here evaluated, in markets where final prices are based on some sort of price listing. Three types of surveys are compared: local surveys (LOC), with small samples and a local price collection; list price surveys (LIS), with huge samples and centralised collection; mixed surveys (MXD), in which LOC and LIS are jointly used. Based on a multiplicative pricing model, some conditions are derived to establish the relative efficiency of these approaches. Th...

  13. Biogas slurry pricing method based on nutrient content

    Science.gov (United States)

    Zhang, Chang-ai; Guo, Honghai; Yang, Zhengtao; Xin, Shurong

    2017-11-01

    In order to promote biogas-slurry commercialization, A method was put forward to valuate biogas slurry based on its nutrient contents. Firstly, element contents of biogas slurry was measured; Secondly, each element was valuated based on its market price, and then traffic cost, using cost and market effect were taken into account, the pricing method of biogas slurry were obtained lastly. This method could be useful in practical production. Taking cattle manure raw meterial biogas slurry and con stalk raw material biogas slurry for example, their price were 38.50 yuan RMB per ton and 28.80 yuan RMB per ton. This paper will be useful for recognizing the value of biogas projects, ensuring biogas project running, and instructing the cyclic utilization of biomass resources in China.

  14. The Combination Forecasting of Electricity Price Based on Price Spikes Processing: A Case Study in South Australia

    Directory of Open Access Journals (Sweden)

    Jianzhou Wang

    2014-01-01

    Full Text Available Electricity price forecasting holds very important position in the electricity market. Inaccurate price forecasting may cause energy waste and management chaos in the electricity market. However, electricity price forecasting has always been regarded as one of the largest challenges in the electricity market because it shows high volatility, which makes electricity price forecasting difficult. This paper proposes the use of artificial intelligence optimization combination forecasting models based on preprocessing data, called “chaos particles optimization (CPSO weight-determined combination models.” These models allow for the weight of the combined model to take values of [-1,1]. In the proposed models, the density-based spatial clustering of applications with noise (DBSCAN algorithm is used to identify outliers, and the outliers are replaced by a new data-produced linear interpolation function. The proposed CPSO weight-determined combination models are then used to forecast the projected future electricity price. In this case study, the electricity price data of South Australia are simulated. The results indicate that, while the weight of the combined model takes values of [-1,1], the proposed combination model can always provide adaptive, reliable, and comparatively accurate forecast results in comparison to traditional combination models.

  15. Economic-environmental active and reactive power scheduling of modern distribution systems in presence of wind generations: A distribution market-based approach

    International Nuclear Information System (INIS)

    Samimi, Abouzar; Kazemi, Ahad; Siano, Pierluigi

    2015-01-01

    Highlights: • A new market-based approach is proposed to schedule active and reactive powers. • Multi-component reactive power bidding structures for DERs is introduced. • A new economical/environmental operational scheduling method is proposed. • At distribution level, a reactive power market is developed in presence of DERs. - Abstract: Distribution System Operator (DSO) is responsible for active and reactive power scheduling in a distribution system. DSO purchases its active and reactive power requirements from Distributed Energy Resources (DERs) as well as the wholesale electricity market. In this paper, a new economical/environmental operational scheduling method based on sequential day-ahead active and reactive power markets at distribution level is proposed to dispatch active and reactive powers in distribution systems with high penetration of DERs. In the proposed model, after day-ahead active power market was cleared the participants submit their reactive power bids and then the reactive power market will be settled. At distribution level, developing a Var market, in which DERs like synchronous machine-based Distributed Generation (DG) units and Wind Turbines (WTs) could offer their reactive power prices, DERs are motivated to actively participate in the Volt/VAr Control (VVC) problem. To achieve this purpose, based on the capability curves of considered DERs, innovative multi-component reactive power bidding structures for DERs are introduced. Moreover, the effect of reactive power market clearing on the active power scheduling is explicitly considered into the proposed model by rescheduling of active power by usage of energy-balance service bids. On the other hand, environmental concerns that arise from the operation of fossil fuel fired electric generators are included in the proposed model by employing CO_2 emission penalty cost. The suggested reactive power market is cleared through a mixed-integer nonlinear optimization program. The

  16. An Event-driven, Value-based, Pull Systems Engineering Scheduling Approach

    Science.gov (United States)

    2012-03-01

    combining a services approach to systems engineering with a kanban -based scheduling system. It provides the basis for validating the approach with...agent-based simulations. Keywords-systems engineering; systems engineering process; lean; kanban ; process simulation I. INTRODUCTION AND BACKGROUND...approaches [8], [9], we are investigating the use of flow-based pull scheduling techniques ( kanban systems) in a rapid response development

  17. Electricity Price Forecasting Based on AOSVR and Outlier Detection

    Institute of Scientific and Technical Information of China (English)

    Zhou Dianmin; Gao Lin; Gao Feng

    2005-01-01

    Electricity price is of the first consideration for all the participants in electric power market and its characteristics are related to both market mechanism and variation in the behaviors of market participants. It is necessary to build a real-time price forecasting model with adaptive capability; and because there are outliers in the price data, they should be detected and filtrated in training the forecasting model by regression method. In view of these points, this paper presents an electricity price forecasting method based on accurate on-line support vector regression (AOSVR) and outlier detection. Numerical testing results show that the method is effective in forecasting the electricity prices in electric power market.

  18. Joint pricing, inventory, and preservation decisions for deteriorating items with stochastic demand and promotional efforts

    Science.gov (United States)

    Soni, Hardik N.; Chauhan, Ashaba D.

    2018-03-01

    This study models a joint pricing, inventory, and preservation decision-making problem for deteriorating items subject to stochastic demand and promotional effort. The generalized price-dependent stochastic demand, time proportional deterioration, and partial backlogging rates are used to model the inventory system. The objective is to find the optimal pricing, replenishment, and preservation technology investment strategies while maximizing the total profit per unit time. Based on the partial backlogging and lost sale cases, we first deduce the criterion for optimal replenishment schedules for any given price and technology investment cost. Second, we show that, respectively, total profit per time unit is concave function of price and preservation technology cost. At the end, some numerical examples and the results of a sensitivity analysis are used to illustrate the features of the proposed model.

  19. Metroplex Optimization Model Expansion and Analysis: The Airline Fleet, Route, and Schedule Optimization Model (AFRS-OM)

    Science.gov (United States)

    Sherry, Lance; Ferguson, John; Hoffman, Karla; Donohue, George; Beradino, Frank

    2012-01-01

    This report describes the Airline Fleet, Route, and Schedule Optimization Model (AFRS-OM) that is designed to provide insights into airline decision-making with regards to markets served, schedule of flights on these markets, the type of aircraft assigned to each scheduled flight, load factors, airfares, and airline profits. The main inputs to the model are hedged fuel prices, airport capacity limits, and candidate markets. Embedded in the model are aircraft performance and associated cost factors, and willingness-to-pay (i.e. demand vs. airfare curves). Case studies demonstrate the application of the model for analysis of the effects of increased capacity and changes in operating costs (e.g. fuel prices). Although there are differences between airports (due to differences in the magnitude of travel demand and sensitivity to airfare), the system is more sensitive to changes in fuel prices than capacity. Further, the benefits of modernization in the form of increased capacity could be undermined by increases in hedged fuel prices

  20. Gas prices and price process

    International Nuclear Information System (INIS)

    Groenewegen, G.G.

    1992-01-01

    On a conference (Gas for Europe in the 1990's) during the Gasexpo '91 the author held a speech of which the Dutch text is presented here. Attention is paid to the current European pricing methods (prices based on the costs of buying, transporting and distributing the natural gas and prices based on the market value, which is deducted from the prices of alternative fuels), and the transparency of the prices (lack of information on the way the prices are determined). Also attention is paid to the market signal transparency and gas-gas competition, which means a more or less free market of gas distribution. The risks of gas-to-gas competition for a long term price stability, investment policies and security of supply are discussed. Opposition against the Third Party Access (TPA), which is the program to implement gas-to-gas competition, is caused by the fear of natural gas companies for lower gas prices and lower profits. Finally attention is paid to government regulation and the activities of the European Commission (EC) in this matter. 1 fig., 6 ills., 1 tab

  1. Cloud Computing Task Scheduling Based on Cultural Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Li Jian-Wen

    2016-01-01

    Full Text Available The task scheduling strategy based on cultural genetic algorithm(CGA is proposed in order to improve the efficiency of task scheduling in the cloud computing platform, which targets at minimizing the total time and cost of task scheduling. The improved genetic algorithm is used to construct the main population space and knowledge space under cultural framework which get independent parallel evolution, forming a mechanism of mutual promotion to dispatch the cloud task. Simultaneously, in order to prevent the defects of the genetic algorithm which is easy to fall into local optimum, the non-uniform mutation operator is introduced to improve the search performance of the algorithm. The experimental results show that CGA reduces the total time and lowers the cost of the scheduling, which is an effective algorithm for the cloud task scheduling.

  2. Multiprocessor Global Scheduling on Frame-Based DVFS Systems

    OpenAIRE

    Berten, Vandy; Goossens, Joël

    2008-01-01

    International audience; In this work, we are interested in multiprocessor energy efficient systems where task durations are not known in advance but are known stochastically. More precisely we consider global scheduling algorithms for frame-based multiprocessor stochastic DVFS (Dynamic Voltage and Frequency Scaling) systems. Moreover we consider processors with a discrete set of available frequencies. We provide a global scheduling algorithm, and formally show that no deadline will ever be mi...

  3. NASA policy on pricing shuttle launch services

    Science.gov (United States)

    Smith, J. M.

    1977-01-01

    The paper explains the rationale behind key elements of the pricing policy for STS, the major features of the non-government user policy, and some of the stimulating features of the policy which will open space to a wide range of new users. Attention is given to such major policy features as payment schedule, cost and standard services, the two phase pricing structure, optional services, shared flights, cancellation and postponement, and earnest money.

  4. Workflow as a Service in the Cloud: Architecture and Scheduling Algorithms

    Science.gov (United States)

    Wang, Jianwu; Korambath, Prakashan; Altintas, Ilkay; Davis, Jim; Crawl, Daniel

    2017-01-01

    With more and more workflow systems adopting cloud as their execution environment, it becomes increasingly challenging on how to efficiently manage various workflows, virtual machines (VMs) and workflow execution on VM instances. To make the system scalable and easy-to-extend, we design a Workflow as a Service (WFaaS) architecture with independent services. A core part of the architecture is how to efficiently respond continuous workflow requests from users and schedule their executions in the cloud. Based on different targets, we propose four heuristic workflow scheduling algorithms for the WFaaS architecture, and analyze the differences and best usages of the algorithms in terms of performance, cost and the price/performance ratio via experimental studies. PMID:29399237

  5. Workflow as a Service in the Cloud: Architecture and Scheduling Algorithms.

    Science.gov (United States)

    Wang, Jianwu; Korambath, Prakashan; Altintas, Ilkay; Davis, Jim; Crawl, Daniel

    2014-01-01

    With more and more workflow systems adopting cloud as their execution environment, it becomes increasingly challenging on how to efficiently manage various workflows, virtual machines (VMs) and workflow execution on VM instances. To make the system scalable and easy-to-extend, we design a Workflow as a Service (WFaaS) architecture with independent services. A core part of the architecture is how to efficiently respond continuous workflow requests from users and schedule their executions in the cloud. Based on different targets, we propose four heuristic workflow scheduling algorithms for the WFaaS architecture, and analyze the differences and best usages of the algorithms in terms of performance, cost and the price/performance ratio via experimental studies.

  6. [The price-based certainty of purchase influences consumer behavior for discount].

    Science.gov (United States)

    Arihara, Katsuhiko; Ariga, Atsunori; Furuya, Takeshi

    2016-04-01

    Tversky & Kahneman (1981) reported that most participants decided to drive when they could save money on a low-price good as compared to when they could save on a high-price good, even though the discount prices were same. Although this irrational decision making has been interpreted as a rate-dependent estimation of value (prospect theory), this study newly proposes that it can be explained by the certainty of purchase based on the price of goods. Experiment 1 replicated the previously reported difference in decision making, and additionally demonstrated that participants' certainty of purchase was lower for a high- than a low-price good. When it was emphasized that participants' intention to purchase high- and low-price goods were equally sure, decision making did not significantly differ (Experiment 2). Furthermore, decision making differed based only on the certainty of purchase even,when prices of goods were-same (Experiment 3). Consumers' decision making may be rather rational, depending straightforwardly on the certainty of purchase that is susceptible to price.

  7. Schedule Risk Analysis Of Southern Mainway Construction In Jember Regency

    Science.gov (United States)

    Susilo, K.; Wiguna, I. P. A.; Adi, T. J. W.

    2017-11-01

    In Jember Regency, it has been built Southern Cross Road (JLS) as part of regional project. On the implementation of previous construction, there were still some events which gave negative impact to the project. The purpose of this research is to analyze risk and its effect on schedule at the construction phase of JLS at Jember Regency. Risk identification process is carried out by site survey, literature studies and supporting data. The use of Probability and Impact Matrix were aimed to obtain the level of risk. Based on the analysis, it was obtained six highest risk that could affecting schedule, such as difficult access locations, heavy rains, increases of material price, broken road pavement work, change order, and work accident. Risk responses were proposed by applying agreement to guarantee stock and price of materials, prioritized drainage, and constructing bridge to solve difficult access. An intense coordination in the site, routine checks of quality, manufacturing of retailing walls were also needed to reduce possibility of distruption to pavement work. To avoid work accident, it is needed to socialize about harsh terrain condition, mutual allertness among supervisor, worker and the others, and also all personals must comply with savety rules.

  8. Cbs (Contrastrain Based Schedulling Adalah Faktor Penentu Keberhasilan Perusahanan Printing

    Directory of Open Access Journals (Sweden)

    Hendra Achmadi

    2010-06-01

    Full Text Available In a highly competitive industry faces today ranging from small or home-based printing to using machine that can print offset a hundred thousand copies per hour. But, the increasing competition resulted in requiring a faster production time from order entry, print proff until the production process to delivery to customers. Often times in case of orders which will result in the concurrent PPIC will experience vertigo in the setting of production schedules which have concurrent delivery time. Often will end up with no receipt of orders due to difficulties in the production schedule, especially if the orders require the same offset machine and cylinder wear the same length, while the number of cylinders is limited. Therefore, the printing company should be able to do so in the conduct of a penetration timing of production can easily be simulated and implemented on the ground. CBS (Base Constraint scheduling is a technique to do the scheduling of production so that production can be carried out smoothly and quickly that fulfill the promise made to customers. In scheduling, there are several techniques that can be used are: FCFS (First Came First Serve, EDD (Earliest Date, and LCLS (Last Came Last Serve. So, it is required to be able to do way better scheduling to get results quickly in this fast changing schedules.

  9. Flexible Demand Management under Time-Varying Prices

    Science.gov (United States)

    Liang, Yong

    In this dissertation, the problem of flexible demand management under time-varying prices is studied. This generic problem has many applications, which usually have multiple periods in which decisions on satisfying demand need to be made, and prices in these periods are time-varying. Examples of such applications include multi-period procurement problem, operating room scheduling, and user-end demand scheduling in the Smart Grid, where the last application is used as the main motivating story throughout the dissertation. The current grid is experiencing an upgrade with lots of new designs. What is of particular interest is the idea of passing time-varying prices that reflect electricity market conditions to end users as incentives for load shifting. One key component, consequently, is the demand management system at the user-end. The objective of the system is to find the optimal trade-off between cost saving and discomfort increment resulted from load shifting. In this dissertation, we approach this problem from the following aspects: (1) construct a generic model, solve for Pareto optimal solutions, and analyze the robust solution that optimizes the worst-case payoffs, (2) extend to a distribution-free model for multiple types of demand (appliances), for which an approximate dynamic programming (ADP) approach is developed, and (3) design other efficient algorithms for practical purposes of the flexible demand management system. We first construct a novel multi-objective flexible demand management model, in which there are a finite number of periods with time-varying prices, and demand arrives in each period. In each period, the decision maker chooses to either satisfy or defer outstanding demand to minimize costs and discomfort over a certain number of periods. We consider both the deterministic model, models with stochastic demand or prices, and when only partial information about the stochastic demand or prices is known. We first analyze the stochastic

  10. Optimal Scheduling of Railway Track Possessions in Large-Scale Projects with Multiple Construction Works

    DEFF Research Database (Denmark)

    Li, Rui; Roberti, Roberto

    2017-01-01

    satisfying different operational constraints and minimizing the total construction cost. To find an optimal solution of the RTPSP, this paper proposes an approach that, first, transfers the nominal market prices into track-possession-based real prices, and then generates a schedule of the construction works...... by solving a mixed-integer linear-programming model for the given track blocking proposal. The proposed approach is tested on a real-life case study from the Danish railway infrastructure manager. The results show that, in 2 h of computing time, the approach is able to provide solutions that are within 0...

  11. Toward Value-Based Pricing to Boost Cancer Research and Innovation.

    Science.gov (United States)

    Ocana, Alberto; Amir, Eitan; Tannock, Ian F

    2016-06-01

    The high market price of new anticancer agents has stimulated debate about the long-term sustainability of healthcare systems and whether these new agents can continue to be supported by public healthcare or by private insurers. In addition, some drugs have been approved with limited clinical benefit, raising concerns about setting a minimum requirement for medical benefit. Options to resolve these problems include raising the bar for approval of new drugs and/or pricing of new agents based on the medical benefit that they offer to patients. In this commentary, we suggest that new agents should be marketed in a two-step process that would include first the approval of the new drug by the regulatory agencies and second the introduction of a market price based on the medical benefit that the new intervention offers to patients. Introduction of value-based pricing would maintain the sustainability of health care systems and would improve drug development, as it would pressure pharmaceutical companies to become more innovative and avoid the development of compounds with limited benefit. Value-based pricing could also stimulate the funding of research directed to development of new anticancer drugs with novel mechanisms of action. Cancer Res; 76(11); 3127-9. ©2016 AACR. ©2016 American Association for Cancer Research.

  12. Opportunistic splitting for scheduling using a score-based approach

    KAUST Repository

    Rashid, Faraan

    2012-06-01

    We consider the problem of scheduling a user in a multi-user wireless environment in a distributed manner. The opportunistic splitting algorithm is applied to find the best group of users without reporting the channel state information to the centralized scheduler. The users find the best among themselves while requiring just a ternary feedback from the common receiver at the end of each mini-slot. The original splitting algorithm is modified to handle users with asymmetric channel conditions. We use a score-based approach with the splitting algorithm to introduce time and throughput fairness while exploiting the multi-user diversity of the network. Analytical and simulation results are given to show that the modified score-based splitting algorithm works well as a fair scheduling scheme with good spectral efficiency and reduced feedback. © 2012 IEEE.

  13. Convergence of decision rules for value-based pricing of new innovative drugs.

    Science.gov (United States)

    Gandjour, Afschin

    2015-04-01

    Given the high costs of innovative new drugs, most European countries have introduced policies for price control, in particular value-based pricing (VBP) and international reference pricing. The purpose of this study is to describe how profit-maximizing manufacturers would optimally adjust their launch sequence to these policies and how VBP countries may best respond. To decide about the launching sequence, a manufacturer must consider a tradeoff between price and sales volume in any given country as well as the effect of price in a VBP country on the price in international reference pricing countries. Based on the manufacturer's rationale, it is best for VBP countries in Europe to implicitly collude in the long term and set cost-effectiveness thresholds at the level of the lowest acceptable VBP country. This way, international reference pricing countries would also converge towards the lowest acceptable threshold in Europe.

  14. The role of demand response in single and multi-objective wind-thermal generation scheduling: A stochastic programming

    International Nuclear Information System (INIS)

    Falsafi, Hananeh; Zakariazadeh, Alireza; Jadid, Shahram

    2014-01-01

    This paper focuses on using DR (Demand Response) as a means to provide reserve in order to cover uncertainty in wind power forecasting in SG (Smart Grid) environment. The proposed stochastic model schedules energy and reserves provided by both of generating units and responsive loads in power systems with high penetration of wind power. This model is formulated as a two-stage stochastic programming, where first-stage is associated with electricity market, its rules and constraints and the second-stage is related to actual operation of the power system and its physical limitations in each scenario. The discrete retail customer responses to incentive-based DR programs are aggregated by DRPs (Demand Response Providers) and are submitted as a load change price and amount offer package to ISO (Independent System Operator). Also, price-based DR program behavior and random nature of wind power are modeled by price elasticity concept of the demand and normal probability distribution function, respectively. In the proposed model, DRPs can participate in energy market as well as reserve market and submit their offers to the wholesale electricity market. This approach is implemented on a modified IEEE 30-bus test system over a daily time horizon. The simulation results are analyzed in six different case studies. The cost, emission and multiobjective functions are optimized in both without and with DR cases. The multiobjective generation scheduling model is solved using augmented epsilon constraint method and the best solution can be chosen by Entropy and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methods. The results indicate demand side participation in energy and reserve scheduling reduces the total operation costs and emissions. - Highlights: • Simultaneous participation of loads in both energy and reserve scheduling. • Environmental/economical scheduling of energy and reserve. • Using demand response for covering wind generation forecast

  15. Residential Consumption Scheduling Based on Dynamic User Profiling

    Science.gov (United States)

    Mangiatordi, Federica; Pallotti, Emiliano; Del Vecchio, Paolo; Capodiferro, Licia

    Deployment of household appliances and of electric vehicles raises the electricity demand in the residential areas and the impact of the building's electrical power. The variations of electricity consumption across the day, may affect both the design of the electrical generation facilities and the electricity bill, mainly when a dynamic pricing is applied. This paper focuses on an energy management system able to control the day-ahead electricity demand in a residential area, taking into account both the variability of the energy production costs and the profiling of the users. The user's behavior is dynamically profiled on the basis of the tasks performed during the previous days and of the tasks foreseen for the current day. Depending on the size and on the flexibility in time of the user tasks, home inhabitants are grouped in, one over N, energy profiles, using a k-means algorithm. For a fixed energy generation cost, each energy profile is associated to a different hourly energy cost. The goal is to identify any bad user profile and to make it pay a highest bill. A bad profile example is when a user applies a lot of consumption tasks and low flexibility in task reallocation time. The proposed energy management system automatically schedules the tasks, solving a multi-objective optimization problem based on an MPSO strategy. The goals, when identifying bad users profiles, are to reduce the peak to average ratio in energy demand, and to minimize the energy costs, promoting virtuous behaviors.

  16. Geometric Distribution-Based Readers Scheduling Optimization Algorithm Using Artificial Immune System

    Directory of Open Access Journals (Sweden)

    Litian Duan

    2016-11-01

    Full Text Available In the multiple-reader environment (MRE of radio frequency identification (RFID system, multiple readers are often scheduled to interrogate the randomized tags via operating at different time slots or frequency channels to decrease the signal interferences. Based on this, a Geometric Distribution-based Multiple-reader Scheduling Optimization Algorithm using Artificial Immune System (GD-MRSOA-AIS is proposed to fairly and optimally schedule the readers operating from the viewpoint of resource allocations. GD-MRSOA-AIS is composed of two parts, where a geometric distribution function combined with the fairness consideration is first introduced to generate the feasible scheduling schemes for reader operation. After that, artificial immune system (including immune clone, immune mutation and immune suppression quickly optimize these feasible ones as the optimal scheduling scheme to ensure that readers are fairly operating with larger effective interrogation range and lower interferences. Compared with the state-of-the-art algorithm, the simulation results indicate that GD-MRSOA-AIS could efficiently schedules the multiple readers operating with a fairer resource allocation scheme, performing in larger effective interrogation range.

  17. Cost savings of unit-based pricing of household waste; the case of the Netherlands

    NARCIS (Netherlands)

    E. Dijkgraaf (Elbert); R.H.J.M. Gradus (Raymond)

    2003-01-01

    textabstractUsing a panel data set for Dutch municipalities we estimate effects for weight-based, bag-based, frequency-based and volume-based pricing of household waste collection. Unit-based pricing shows to be effective in reducing solid and compostable and increasing recyclable waste. Pricing has

  18. Computer-based irrigation scheduling for cotton crop

    International Nuclear Information System (INIS)

    Laghari, K.Q.; Memon, H.M.

    2008-01-01

    In this study a real time irrigation schedule for cotton crop has been tested using mehran model, a computer-based DDS (Decision Support System). The irrigation schedule was set on selected MAD (Management Allowable Depletion) and the current root depth position. The total 451 mm irrigation water applied to the crop field. The seasonal computed crop ET (Evapotranspiration) was estimated 421.32 mm and actual (ET/sub ca/) observed was 413 mm. The model over-estimated seasonal ET by only 1.94. WUE (Water Use Efficiency) for seed-cotton achieved 6.59 Kg (ha mm)/sup -1/. The statistical analysis (R/sup 2/=0.96, ARE%=2.00, T-1.17 and F=550.57) showed good performance of the model in simulated and observed ET values. The designed Mehran model is designed quite versatile for irrigation scheduling and can be successfully used as irrigation DSS tool for various crop types. (author)

  19. The impact of exposure to shift-based schedules on medical students

    Directory of Open Access Journals (Sweden)

    David A. Williams

    2015-06-01

    Full Text Available Background: With new resident duty-hour regulations, resident work schedules have progressively transitioned towards shift-based systems, sometimes resulting in increased team fragmentation. We hypothesized that exposure to shift-based schedules and subsequent team fragmentation would negatively affect medical student experiences during their third-year internal medicine clerkship. Design: As part of a larger national study on duty-hour reform, 67 of 150 eligible third-year medical students completed surveys about career choice, teaching and supervision, assessment, patient care, well-being, and attractiveness of a career in internal medicine after completing their internal medicine clerkship. Students who rotated to hospitals with shift-based systems were compared to those who did not. Non-demographic variables used a five-point Likert scale. Chi-squared and Fisher's exact tests were used to assess the relationships between exposure to shift-based schedules and student responses. Questions with univariate p≤0.1 were included in multivariable logistic regression models. Results: Thirty-six students (54% were exposed to shift-based schedules. Students exposed to shift-based schedules were less likely to perceive that their attendings were committed to teaching (odds ratio [OR] 0.35, 95% confidence interval [CI]: 0.13–0.90, p=0.01 or perceive that residents had sufficient exposure to assess their performance (OR 0.29, 95% CI: 0.09–0.91, p=0.03. However, those students were more likely to feel their interns were able to observe them at the bedside (OR 1.89, 95% CI: 1.08–3.13, p=0.02 and had sufficient exposure to assess their performance (OR 3.00, 95% CI: 1.01–8.86, p=0.05. Conclusions: These findings suggest that shift-based schedules designed in response to duty-hour reform may have important broader implications for the teaching environment.

  20. The impact of exposure to shift-based schedules on medical students.

    Science.gov (United States)

    Williams, David A; Kogan, Jennifer R; Hauer, Karen E; Yamashita, Traci; Aagaard, Eva M

    2015-01-01

    With new resident duty-hour regulations, resident work schedules have progressively transitioned towards shift-based systems, sometimes resulting in increased team fragmentation. We hypothesized that exposure to shift-based schedules and subsequent team fragmentation would negatively affect medical student experiences during their third-year internal medicine clerkship. As part of a larger national study on duty-hour reform, 67 of 150 eligible third-year medical students completed surveys about career choice, teaching and supervision, assessment, patient care, well-being, and attractiveness of a career in internal medicine after completing their internal medicine clerkship. Students who rotated to hospitals with shift-based systems were compared to those who did not. Non-demographic variables used a five-point Likert scale. Chi-squared and Fisher's exact tests were used to assess the relationships between exposure to shift-based schedules and student responses. Questions with univariate p ≤ 0.1 were included in multivariable logistic regression models. Thirty-six students (54%) were exposed to shift-based schedules. Students exposed to shift-based schedules were less likely to perceive that their attendings were committed to teaching (odds ratio [OR] 0.35, 95% confidence interval [CI]: 0.13-0.90, p = 0.01) or perceive that residents had sufficient exposure to assess their performance (OR 0.29, 95% CI: 0.09-0.91, p = 0.03). However, those students were more likely to feel their interns were able to observe them at the bedside (OR 1.89, 95% CI: 1.08-3.13, p = 0.02) and had sufficient exposure to assess their performance (OR 3.00, 95% CI: 1.01-8.86, p = 0.05). These findings suggest that shift-based schedules designed in response to duty-hour reform may have important broader implications for the teaching environment.

  1. Price-based control of electrical power systems

    NARCIS (Netherlands)

    Jokic, A.; Lazar, M.; Bosch, van den P.P.J.; Negenborn, R.R.; Lukszo, Z.; Hellendorn, H.

    2010-01-01

    In this chapter we present the price-based control as a suitable approach to solve some of the challenging problems facing future, market-based power sys tems. On the example of economically optimal power balance and transmission network congestion control, we present how global objectives and

  2. Linear triangular optimization technique and pricing scheme in residential energy management systems

    Science.gov (United States)

    Anees, Amir; Hussain, Iqtadar; AlKhaldi, Ali Hussain; Aslam, Muhammad

    2018-06-01

    This paper presents a new linear optimization algorithm for power scheduling of electric appliances. The proposed system is applied in a smart home community, in which community controller acts as a virtual distribution company for the end consumers. We also present a pricing scheme between community controller and its residential users based on real-time pricing and likely block rates. The results of the proposed optimization algorithm demonstrate that by applying the anticipated technique, not only end users can minimise the consumption cost, but it can also reduce the power peak to an average ratio which will be beneficial for the utilities as well.

  3. A Personalized Rolling Optimal Charging Schedule for Plug-In Hybrid Electric Vehicle Based on Statistical Energy Demand Analysis and Heuristic Algorithm

    DEFF Research Database (Denmark)

    Kong, Fanrong; Jiang, Jianhui; Ding, Zhigang

    2017-01-01

    To alleviate the emission of greenhouse gas and the dependence on fossil fuel, Plug-in Hybrid Electrical Vehicles (PHEVs) have gained an increasing popularity in current decades. Due to the fluctuating electricity prices in the power market, a charging schedule is very influential to driving cost...

  4. Performance Evaluation of Bidding-Based Multi-Agent Scheduling Algorithms for Manufacturing Systems

    Directory of Open Access Journals (Sweden)

    Antonio Gordillo

    2014-10-01

    Full Text Available Artificial Intelligence techniques have being applied to many problems in manufacturing systems in recent years. In the specific field of manufacturing scheduling many studies have been published trying to cope with the complexity of the manufacturing environment. One of the most utilized approaches is (multi agent-based scheduling. Nevertheless, despite the large list of studies reported in this field, there is no resource or scientific study on the performance measure of this type of approach under very common and critical execution situations. This paper focuses on multi-agent systems (MAS based algorithms for task allocation, particularly in manufacturing applications. The goal is to provide a mechanism to measure the performance of agent-based scheduling approaches for manufacturing systems under key critical situations such as: dynamic environment, rescheduling, and priority change. With this mechanism it will be possible to simulate critical situations and to stress the system in order to measure the performance of a given agent-based scheduling method. The proposed mechanism is a pioneering approach for performance evaluation of bidding-based MAS approaches for manufacturing scheduling. The proposed method and evaluation methodology can be used to run tests in different manufacturing floors since it is independent of the workshop configuration. Moreover, the evaluation results presented in this paper show the key factors and scenarios that most affect the market-like MAS approaches for manufacturing scheduling.

  5. Financing Target and Resale Pricing in Reward-Based Crowdfunding

    Directory of Open Access Journals (Sweden)

    Lei Xu

    2018-04-01

    Full Text Available Resale is an effective tool for reward-based crowdfunding creators to make more profit after crowdfunding successfully. On the one hand, funds raised during the crowdfunding affect the resale pricing as a capital constraint; on the other hand, backers’ strategic purchasing behavior in the resale stage can also disturb the creator’s financing target decision-making through affecting resale pricing. In view of this, this paper builds a two-stage crowdfunding model to examine the interaction between the financing target and resale pricing in the presence of strategic backers. The results show that a lower financing amount leads to higher prices in the resale stage due to the rationing effect, and suppresses price volatility due to strategic purchasing behavior. In contrast, a higher financing amount enables the creator to build a large capacity, which does not restrict the resale prices and profit. Besides, in the context of high unit production cost or high backer patience level, there is no need for the creator to set a high financing target at the risk of crowdfunding failure.

  6. Can and should value-based pricing be applied to molecular diagnostics?

    Science.gov (United States)

    Garau, Martina; Towse, Adrian; Garrison, Louis; Housman, Laura; Ossa, Diego

    2013-01-01

    Current pricing and reimbursement systems for diagnostics are not efficient. Prices for diagnostics are often driven by administrative practices and expected production cost. The purpose of the paper is to discuss how a value-based pricing framework being used to ensure efficient use and price of medicines could also be applied to diagnostics. Diagnostics not only facilitates health gain and cost savings, but also information to guide patients' decisions on interventions and their future 'behaviors'. For value assessment processes we recommend a two-part approach. Companion diagnostics introduced at the launch of the drug should be assessed through new drug assessment processes considering a broad range of value elements and a balanced analysis of diagnostic impacts. A separate diagnostic-dedicated committee using value-based pricing principles should review other diagnostics lying outside the companion diagnostics-and-drug 'at-launch' situation.

  7. Effects of unit-based garbage pricing : A differences-in-differences approach

    NARCIS (Netherlands)

    Allers, Maarten A.; Hoeben, Corine

    Using a unique 10-year dataset of all 458 Dutch municipalities, we apply a differences-in-differences approach to estimate the effect of unit-based pricing on household waste quantities and recycling. Community-level studies of unit-based pricing typically do not include fixed effects at the local

  8. Electricity transmission pricing: Tracing based point-of-connection tariff

    International Nuclear Information System (INIS)

    Abhyankar, A.R.; Khaparde, S.A.

    2009-01-01

    Point-of-connection (POC) scheme of transmission pricing in decentralized markets charges the participants a single rate per MW depending on their point-of-connection. Use of grossly aggregated postage stamp rates as POC charges fails to provide appropriate price signals. The POC tariff based on distribution of network sunk costs by employing conventional tracing assures recovery of sunk costs based on extent of use of network by participants. However, the POC tariff by this method does not accommodate economically efficient price signals which correspond to marginal costs. On the other hand, the POC tariff, if made proportional to marginal costs alone, fails to account for sunk costs and extent of use of network. This paper overcomes these lacunae by combining the above stated desired objectives under the recently proposed optimal tracing framework. Since real power tracing problem is amenable to multiple solutions, it is formulated as linearly constrained optimization problem. By employing this methodology, consideration of extent of network use and sunk cost recovery are guaranteed, while objective function is designed such that the spatial pattern of price signals closely follows the pattern of scaled locational marginal prices. The methodology is tested on IEEE 30 bus system, wherein average power flow pattern is established by running various simulation states on congested and un-congested network conditions. (author)

  9. Impact of interference on the performance of selection based parallel multiuser scheduling

    KAUST Repository

    Nam, Sungsik

    2012-02-01

    In conventional multiuser parallel scheduling schemes, every scheduled user is interfering with every other scheduled user, which limits the capacity and performance of multiuser systems, and the level of interference becomes substantial as the number of scheduled users increases. Based on the above observations, we investigate the trade-off between the system throughput and the number of scheduled users through the exact analysis of the total average sum rate capacity and the average spectral efficiency. Our analytical results can help the system designer to carefully select the appropriate number of scheduled users to maximize the overall throughput while maintaining an acceptable quality of service under certain channel conditions. © 2012 IEEE.

  10. Optimal charging schedule of an electric vehicle fleet

    DEFF Research Database (Denmark)

    Hu, Junjie; You, Shi; Østergaard, Jacob

    2011-01-01

    In this paper, we propose an approach to optimize the charging schedule of an Electric Vehicle (EV) fleet both taking into account spot price and individual EV driving requirement with the goal of minimizing charging costs. A flexible and suitable mathematic model is introduced to characterize...

  11. HOLD MODE BASED DYNAMIC PRIORITY LOAD ADAPTIVE INTERPICONET SCHEDULING FOR BLUETOOTH SCATTERNETS

    Directory of Open Access Journals (Sweden)

    G.S. Mahalakshmi

    2011-09-01

    Full Text Available Scheduling in piconets has emerged as a challenging research area. Interpiconet scheduling focuses on when a bridge is switched among various piconets and how a bridge node communicates with the masters in different piconets. This paper proposes an interpiconet scheduling algorithm named, hold mode based dynamic traffic priority load adaptive scheduling. The bridges are adaptively switched between the piconets according to various traffic loads. The main goal is to maximize the utilization of the bridge by reducing the bridge switch wastes, utilize intelligent decision making algorithm, resolve conflict between the masters, and allow negotiation for bridge utilization in HDPLIS using bridge failure-bridge repair procedure . The Hold mode - dynamic traffic - priority based - load adaptive scheduling reduces the number of bridge switch wastes and hence increases the efficiency of the bridge which results in increased performance of the system.

  12. Stittco Utilities Man Ltd. application for an interim ex parte order under section 45 of the Public Utilities Board Act for the approval of a change to its schedule of rates

    Energy Technology Data Exchange (ETDEWEB)

    1990-11-15

    Stittco Utilities, a company distributing propane in Manitoba, applied to the Manitoba Public Utilities Board for an interim order authorizing an increase in rates for all domestic and commercial customers in 3 Manitoba localities. The rate increase requested is based on the increase in the commodity price of propane and related changes in freight rates. If approved, the average rate will increase by ca 28% for residential customers and 27% for commercial customers. With the expectation that the price of propane would decrease in the near future, Stittco proposed to base its rates on a propane price lower than the current market price, in an effort to retain existing customers. Stittco also proposed to establish a variance account, in which the difference between the cost of propane built into the rates and the actual market price would be accumulated. From time to time Stittco would apply to adjust the rate schedule to refund overages or collect shortfalls contained in this variance account. It is Stittco's intention to cancel its new propane supply contract when propane prices stabilize and enter into a new fixed-price contract. Stittco would then apply for a new rate schedule based on the long-term price of propane. Based on the evidence, the Board decided that a prima facie case has been made showing a 105% increase in Stittco's cost of product and delivery, and that this increase should be passed through to Stittco customers effective November 16, 1990. Status reports were required for the variance account starting December 1990.

  13. A supply and demand based volatility model for energy prices

    International Nuclear Information System (INIS)

    Kanamura, Takashi

    2009-01-01

    This paper proposes a new volatility model for energy prices using the supply-demand relationship, which we call a supply and demand based volatility model. We show that the supply curve shape in the model determines the characteristics of the volatility in energy prices. It is found that the inverse Box-Cox transformation supply curve reflecting energy markets causes the inverse leverage effect, i.e., positive correlation between energy prices and volatility. The model is also used to show that an existing (G)ARCH-M model has the foundations on the supply-demand relationship. Additionally, we conduct the empirical studies analyzing the volatility in the U.S. natural gas prices. (author)

  14. A supply and demand based volatility model for energy prices

    Energy Technology Data Exchange (ETDEWEB)

    Kanamura, Takashi [J-POWER, 15-1, Ginza 6-Chome, Chuo-ku, Tokyo 104-8165 (Japan)

    2009-09-15

    This paper proposes a new volatility model for energy prices using the supply-demand relationship, which we call a supply and demand based volatility model. We show that the supply curve shape in the model determines the characteristics of the volatility in energy prices. It is found that the inverse Box-Cox transformation supply curve reflecting energy markets causes the inverse leverage effect, i.e., positive correlation between energy prices and volatility. The model is also used to show that an existing (G)ARCH-M model has the foundations on the supply-demand relationship. Additionally, we conduct the empirical studies analyzing the volatility in the U.S. natural gas prices. (author)

  15. PRACTICAL IMPLICATIONS OF LOCATION-BASED SCHEDULING

    DEFF Research Database (Denmark)

    Andersson, Niclas; Christensen, Knud

    2007-01-01

    The traditional method for planning, scheduling and controlling activities and resources in construction projects is the CPM-scheduling, which has been the predominant scheduling method since its introduction in the late 1950s. Over the years, CPM has proven to be a very powerful technique...... that will be used in this study. LBS is a scheduling method that rests upon the theories of line-of-balance and which uses the graphic representation of a flowline chart. As such, LBS is adapted for planning and management of workflows and, thus, may provide a solution to the identified shortcomings of CPM. Even...

  16. Real-time electricity pricing mechanism in China based on system dynamics

    International Nuclear Information System (INIS)

    He, Yongxiu; Zhang, Jixiang

    2015-01-01

    Highlights: • The system dynamics is used to research the real-time electricity pricing mechanism. • Four kinds of the real-time electricity pricing models are carried out and simulated. • It analysed the electricity price, the user satisfaction and the social benefits under the different models. • Market pricing is the trend of the real-time electricity pricing mechanism. • Initial development path of the real-time price mechanism for China is designed between 2015 and 2030. - Abstract: As an important means of demand-side response, the reasonable formulation of the electricity price mechanism will have an important impact on the balance between the supply and demand of electric power. With the introduction of Chinese intelligence apparatus and the rapid development of smart grids, real-time electricity pricing, as the frontier electricity pricing mechanism in the smart grid, will have great significance on the promotion of energy conservation and the improvement of the total social surplus. From the perspective of system dynamics, this paper studies different real-time electricity pricing mechanisms based on load structure, cost structure and bidding and analyses the situation of user satisfaction and the total social surplus under different pricing mechanisms. Finally, through the comparative analysis of examples under different real-time pricing scenarios, this paper aims to explore and design the future dynamic real-time electricity pricing mechanism in China, predicts the dynamic real-time pricing level and provides a reference for real-time electricity price promotion in the future

  17. A real-time Excel-based scheduling solution for nursing staff reallocation.

    Science.gov (United States)

    Tuominen, Outi Anneli; Lundgren-Laine, Heljä; Kauppila, Wiveka; Hupli, Maija; Salanterä, Sanna

    2016-09-30

    Aim This article describes the development and testing of an Excel-based scheduling solution for the flexible allocation and reallocation of nurses to cover sudden, unplanned absences among permanent nursing staff. Method A quasi-experimental, one group, pre- and post-test study design was used ( Box 1 ) with total sampling. Participants (n=17) were selected purposefully by including all ward managers (n=8) and assistant ward managers (n=9) from one university hospital department. The number of sudden absences among the nursing staff was identified during two 4-week data collection periods (pre- and post-test). Results During the use of the paper-based scheduling system, 121 absences were identified; during the use of the Excel-based system, 106 were identified. The main reasons for the use of flexible 'floating' nurses were sick leave (n=66) and workload (n=31). Other reasons (n=29) included patient transfer to another hospital, scheduling errors and the start or end of employment. Conclusion The Excel-based scheduling solution offered better support in obtaining substitute labour inside the organisation, with smaller employment costs. It also reduced the number of tasks ward managers had to carry out during the process of reallocating staff.

  18. Excel-based scheduling for reallocation of nursing staff.

    Science.gov (United States)

    2016-10-19

    Outi Annelli Tuominen and colleagues write in Nursing Management about the use of an Excel-based scheduling system for reallocation of nursing staff, which was trialled on ward managers and assistant ward managers.

  19. Rule-Based and Case-Based Reasoning in Housing Prices

    OpenAIRE

    Gabrielle Gayer; Itzhak Gilboa; Offer Lieberman

    2004-01-01

    People reason about real-estate prices both in terms of general rules and in terms of analogies to similar cases. We propose to empirically test which mode of reasoning fits the data better. To this end, we develop the statistical techniques required for the estimation of the case-based model. It is hypothesized that case-based reasoning will have relatively more explanatory power in databases of rental apartments, whereas rule-based reasoning will have a relative advantage in sales data. We ...

  20. Compositional schedulability analysis of real-time actor-based systems.

    Science.gov (United States)

    Jaghoori, Mohammad Mahdi; de Boer, Frank; Longuet, Delphine; Chothia, Tom; Sirjani, Marjan

    2017-01-01

    We present an extension of the actor model with real-time, including deadlines associated with messages, and explicit application-level scheduling policies, e.g.,"earliest deadline first" which can be associated with individual actors. Schedulability analysis in this setting amounts to checking whether, given a scheduling policy for each actor, every task is processed within its designated deadline. To check schedulability, we introduce a compositional automata-theoretic approach, based on maximal use of model checking combined with testing. Behavioral interfaces define what an actor expects from the environment, and the deadlines for messages given these assumptions. We use model checking to verify that actors match their behavioral interfaces. We extend timed automata refinement with the notion of deadlines and use it to define compatibility of actor environments with the behavioral interfaces. Model checking of compatibility is computationally hard, so we propose a special testing process. We show that the analyses are decidable and automate the process using the Uppaal model checker.

  1. Habit-based Asset Pricing with Limited Participation Consumption

    DEFF Research Database (Denmark)

    Bach, Christian; Møller, Stig Vinther

    We calibrate and estimate a consumption-based asset pricing model with habit formation using limited participation consumption data. Based on survey data of a representative sample of American households, we distinguish between assetholder and non-assetholder consumption, as well as the standard...

  2. Habit-based asset pricing with limited participation consumption

    DEFF Research Database (Denmark)

    Møller, Stig Vinther; Bach, Christian

    2011-01-01

    We calibrate and estimate a consumption-based asset pricing model with habit formation using limited participation consumption data. Based on survey data of a representative sample of American households, we distinguish between assetholder and non-assetholder consumption, as well as the standard...

  3. Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm

    International Nuclear Information System (INIS)

    Yu, Lean; Wang, Shouyang; Lai, Kin Keung

    2008-01-01

    In this study, an empirical mode decomposition (EMD) based neural network ensemble learning paradigm is proposed for world crude oil spot price forecasting. For this purpose, the original crude oil spot price series were first decomposed into a finite, and often small, number of intrinsic mode functions (IMFs). Then a three-layer feed-forward neural network (FNN) model was used to model each of the extracted IMFs, so that the tendencies of these IMFs could be accurately predicted. Finally, the prediction results of all IMFs are combined with an adaptive linear neural network (ALNN), to formulate an ensemble output for the original crude oil price series. For verification and testing, two main crude oil price series, West Texas Intermediate (WTI) crude oil spot price and Brent crude oil spot price, are used to test the effectiveness of the proposed EMD-based neural network ensemble learning methodology. Empirical results obtained demonstrate attractiveness of the proposed EMD-based neural network ensemble learning paradigm. (author)

  4. Western Australian Public Opinions of a Minimum Pricing Policy for Alcohol: Study Protocol.

    Science.gov (United States)

    Keatley, David A; Carragher, Natacha; Chikritzhs, Tanya; Daube, Mike; Hardcastle, Sarah J; Hagger, Martin S

    2015-11-18

    Excessive alcohol consumption has significant adverse economic, social, and health outcomes. Recent estimates suggest that the annual economic costs of alcohol in Australia are up to AUD $36 billion. Policies influencing price have been demonstrated to be very effective in reducing alcohol consumption and alcohol-related harms. Interest in minimum pricing has gained traction in recent years. However, there has been little research investigating the level of support for the public interest case of minimum pricing in Australia. This article describes protocol for a study exploring Western Australian (WA) public knowledge, understanding, and reaction to a proposed minimum price policy per standard drink. The study will employ a qualitative methodological design. Participants will be recruited from a wide variety of backgrounds, including ethnic minorities, blue and white collar workers, unemployed, students, and elderly/retired populations to participate in focus groups. Focus group participants will be asked about their knowledge of, and initial reactions to, the proposed policy and encouraged to discuss how such a proposal may affect their own alcohol use and alcohol consumption at the population level. Participants will also be asked to discuss potential avenues for increasing acceptability of the policy. The focus groups will adopt a semi-structured, open-ended approach guided by a question schedule. The schedule will be based on feedback from pilot samples, previous research, and a steering group comprising experts in alcohol policy and pricing. The study is expected to take approximately 14 months to complete. The findings will be of considerable interest and relevance to government officials, policy makers, researchers, advocacy groups, alcohol retail and licensed establishments and organizations, city and town planners, police, and other stakeholder organizations.

  5. Analysis of Issues for Project Scheduling by Multiple, Dispersed Schedulers (distributed Scheduling) and Requirements for Manual Protocols and Computer-based Support

    Science.gov (United States)

    Richards, Stephen F.

    1991-01-01

    Although computerized operations have significant gains realized in many areas, one area, scheduling, has enjoyed few benefits from automation. The traditional methods of industrial engineering and operations research have not proven robust enough to handle the complexities associated with the scheduling of realistic problems. To address this need, NASA has developed the computer-aided scheduling system (COMPASS), a sophisticated, interactive scheduling tool that is in wide-spread use within NASA and the contractor community. Therefore, COMPASS provides no explicit support for the large class of problems in which several people, perhaps at various locations, build separate schedules that share a common pool of resources. This research examines the issue of distributing scheduling, as applied to application domains characterized by the partial ordering of tasks, limited resources, and time restrictions. The focus of this research is on identifying issues related to distributed scheduling, locating applicable problem domains within NASA, and suggesting areas for ongoing research. The issues that this research identifies are goals, rescheduling requirements, database support, the need for communication and coordination among individual schedulers, the potential for expert system support for scheduling, and the possibility of integrating artificially intelligent schedulers into a network of human schedulers.

  6. Orderly Discharging Strategy for Electric Vehicles at Workplace Based on Time-of-Use Price

    Directory of Open Access Journals (Sweden)

    Lixing Chen

    2016-01-01

    Full Text Available According to the parking features of electric vehicles (EVs and load of production unit, a power supply system including EVs charging station was established, and an orderly discharging strategy for EVs was proposed as well to reduce the basic tariff of producer and improve the total benefits of EV discharging. Based on the target of maximizing the annual income of producer, considering the total benefits of EV discharging, the electric vehicle aggregator (EVA and time-of-use (TOU price were introduced to establish the optimization scheduling model of EVs discharging. Furthermore, an improved artificial fish swarm algorithm (IAFSA combined with the penalty function methods was applied to solve the model. It can be shown from the simulation results that the optimal solution obtained by IAFSA is regarded as the orderly discharging strategy for EVs, which could reduce the basic tariff of producer and improve the total benefits of EV discharging.

  7. Optimal RTP Based Power Scheduling for Residential Load in Smart Grid

    Science.gov (United States)

    Joshi, Hemant I.; Pandya, Vivek J.

    2015-12-01

    To match supply and demand, shifting of load from peak period to off-peak period is one of the effective solutions. Presently flat rate tariff is used in major part of the world. This type of tariff doesn't give incentives to the customers if they use electrical energy during off-peak period. If real time pricing (RTP) tariff is used, consumers can be encouraged to use energy during off-peak period. Due to advancement in information and communication technology, two-way communications is possible between consumers and utility. To implement this technique in smart grid, home energy controller (HEC), smart meters, home area network (HAN) and communication link between consumers and utility are required. HEC interacts automatically by running an algorithm to find optimal energy consumption schedule for each consumer. However, all the consumers are not allowed to shift their load simultaneously during off-peak period to avoid rebound peak condition. Peak to average ratio (PAR) is considered while carrying out minimization problem. Linear programming problem (LPP) method is used for minimization. The simulation results of this work show the effectiveness of the minimization method adopted. The hardware work is in progress and the program based on the method described here will be made to solve real problem.

  8. Flexible job-shop scheduling based on genetic algorithm and simulation validation

    Directory of Open Access Journals (Sweden)

    Zhou Erming

    2017-01-01

    Full Text Available This paper selects flexible job-shop scheduling problem as the research object, and Constructs mathematical model aimed at minimizing the maximum makespan. Taking the transmission reverse gear production line of a transmission corporation as an example, genetic algorithm is applied for flexible jobshop scheduling problem to get the specific optimal scheduling results with MATLAB. DELMIA/QUEST based on 3D discrete event simulation is applied to construct the physical model of the production workshop. On the basis of the optimal scheduling results, the logical link of the physical model for the production workshop is established, besides, importing the appropriate process parameters to make virtual simulation on the production workshop. Finally, through analyzing the simulated results, it shows that the scheduling results are effective and reasonable.

  9. Priced Timed Automata

    DEFF Research Database (Denmark)

    Behrmann, Gerd; Larsen, Kim Guldstrand; Rasmussen, Jacob Illum

    2004-01-01

    This contribution reports on the considerable effort made recently towards extending and applying well-established timed automata technology to optimal scheduling and planning problems. The effort of the authors in this direction has to a large extent been carried out as part of the European...... projects VHS [22] and AMETIST [17] and are available in the recently released UPPAAL CORA [12], a variant of the real-time verification tool UPPAAL [20,5] specialized for cost-optimal reachability for the extended model of priced timed automata....

  10. Risk-constrained dynamic self-scheduling of a pumped-storage plant in the energy and ancillary service markets

    International Nuclear Information System (INIS)

    Kazempour, S. Jalal; Moghaddam, M. Parsa; Haghifam, M.R.; Yousefi, G.R.

    2009-01-01

    This work addresses a new framework for self-scheduling of an individual price-taker pumped-storage plant in a day-ahead (DA) market. The goal is achieving the best trade-off between the expected profit and the risks when the plant participates in DA energy, spinning reserve and regulation markets. In this paper, a set of uncertainties including price forecasting errors and also the uncertainty of power delivery requests in the ancillary service markets are contemplated. Considering these uncertainties, a new approach is proposed which is called dynamic self-scheduling (DSS). This risk-constrained dynamic self-scheduling problem is therefore formulated and solved as a mixed integer programming (MIP) problem. Numerical results for a case study are discussed. (author)

  11. Application of the Price-Volume Approach in Cases of Innovative Drugs Where Value-Based Pricing is Inadequate: Description of Real Experiences in Italy.

    Science.gov (United States)

    Messori, Andrea

    2016-08-01

    Several cases of expensive drugs designed for large patient populations (e.g. sofosbuvir) have raised a complex question in terms of drug pricing. Even assuming value-based pricing, the treatment with these drugs of all eligible patients would have an immense budgetary impact, which is unsustainable also for the richest countries. This raises the need to reduce the prices of these agents in comparison with those suggested by the value-based approach and to devise new pricing methods that can achieve this goal. The present study discusses in detail the following two methods: (i) The approach based on setting nation-wide budget thresholds for individual innovative agents in which a fixed proportion of the historical pharmaceutical expenditure represents the maximum budget attributable to an innovative treatment; (ii) The approach based on nation-wide price-volume agreements in which drug prices are progressively reduced as more patients receive the treatment. The first approach has been developed in the USA by the Institute for Clinical and Economic Review and has been applied to PCSK9 inhibitors (alirocumab and evolocumab). The second approach has been designed for the Italian market and has found a systematic application to manage the price of ranibizumab, sofosbuvir, and PCSK9 inhibitors. While, in the past, price-volume agreements have been applied only on an empirical basis (i.e. in the absence of any quantitative theoretical rule), more recently some explicit mathematical models have been described. The performance of these models is now being evaluated on the basis of the real-world experiences conducted in some European countries, especially Italy.

  12. HOROPLAN: computer-assisted nurse scheduling using constraint-based programming.

    Science.gov (United States)

    Darmoni, S J; Fajner, A; Mahé, N; Leforestier, A; Vondracek, M; Stelian, O; Baldenweck, M

    1995-01-01

    Nurse scheduling is a difficult and time consuming task. The schedule has to determine the day to day shift assignments of each nurse for a specified period of time in a way that satisfies the given requirements as much as possible, taking into account the wishes of nurses as closely as possible. This paper presents a constraint-based, artificial intelligence approach by describing a prototype implementation developed with the Charme language and the first results of its use in the Rouen University Hospital. Horoplan implements a non-cyclical constraint-based scheduling, using some heuristics. Four levels of constraints were defined to give a maximum of flexibility: French level (e.g. number of worked hours in a year), hospital level (e.g. specific day-off), department level (e.g. specific shift) and care unit level (e.g. specific pattern for week-ends). Some constraints must always be verified and can not be overruled and some constraints can be overruled at a certain cost. Rescheduling is possible at any time specially in case of an unscheduled absence.

  13. Optimal scheduling of coproduction with a storage

    International Nuclear Information System (INIS)

    Ravn, H.F.; Rygard, J.M.

    1993-02-01

    We consider the problem of optimal scheduling of a system with combined heat and heat (CHP) units and a heat storege. The purpose of the heat storage is to permit a partial decoupling of the variations in the demand for heat and electrical power. We formulate the problem of optimal scheduling as that of minimizing the total costs over the planning period. The heat demand from the district heating system and the ''shadow prices'' for the electrical power system are taken as externally given parameters. The resulting model is solved by dynamic programming. We describe implementation details and we give examples of result of the optimization. (au) (12 refs.)

  14. Flow-based market coupling. Stepping stone towards nodal pricing?

    International Nuclear Information System (INIS)

    Van der Welle, A.J.

    2012-07-01

    For achieving one internal energy market for electricity by 2014, market coupling is deployed to integrate national markets into regional markets and ultimately one European electricity market. The extent to which markets can be coupled depends on the available transmission capacities between countries. Since interconnections are congested from time to time, congestion management methods are deployed to divide the scarce available transmission capacities over market participants. For further optimization of the use of available transmission capacities while maintaining current security of supply levels, flow-based market coupling (FBMC) will be implemented in the CWE region by 2013. Although this is an important step forward, important hurdles for efficient congestion management remain. Hence, flow based market coupling is compared to nodal pricing, which is often considered as the most optimal solution from theoretical perspective. In the context of decarbonised power systems it is concluded that advantages of nodal pricing are likely to exceed its disadvantages, warranting further development of FBMC in the direction of nodal pricing.

  15. 78 FR 10579 - TRICARE Revision to CHAMPUS DRG-Based Payment System, Pricing of Hospital Claims

    Science.gov (United States)

    2013-02-14

    ... 0720-AB58 TRICARE Revision to CHAMPUS DRG-Based Payment System, Pricing of Hospital Claims AGENCY... change TRICARE's current regulatory provision for hospital claims priced under the DRG-based payment... under the DRG- based payment system from the beneficiary's date of admission, to pricing such claims...

  16. Project Scheduling Heuristics-Based Standard PSO for Task-Resource Assignment in Heterogeneous Grid

    OpenAIRE

    Chen, Ruey-Maw; Wang, Chuin-Mu

    2011-01-01

    The task scheduling problem has been widely studied for assigning resources to tasks in heterogeneous grid environment. Effective task scheduling is an important issue for the performance of grid computing. Meanwhile, the task scheduling problem is an NP-complete problem. Hence, this investigation introduces a named “standard“ particle swarm optimization (PSO) metaheuristic approach to efficiently solve the task scheduling problems in grid. Meanwhile, two promising heuristics based on multimo...

  17. Robust Optimization of the Self- scheduling and Market Involvement for an Electricity Producer

    KAUST Repository

    Lima, Ricardo

    2015-01-01

    This work address the optimization under uncertainty of the self-scheduling, forward contracting, and pool involvement of an electricity producer operating a mixed power generation station, which combines thermal, hydro and wind sources, and uses a two-stage adaptive robust optimization approach. In this problem the wind power production and the electricity pool price are considered to be uncertain, and are described by uncertainty convex sets. Two variants of a constraint generation algorithm are proposed, namely a primal and dual version, and they are used to solve two case studies based on two different producers. Their market strategies are investigated for three different scenarios, corresponding to as many instances of electricity price forecasts. The effect of the producers’ approach, whether conservative or more risk prone, is also investigated by solving each instance for multiple values of the so-called budget parameter. It was possible to conclude that this parameter influences markedly the producers’ strategy, in terms of scheduling, profit, forward contracting, and pool involvement. Regarding the computational results, these show that for some instances, the two variants of the algorithms have a similar performance, while for a particular subset of them one variant has a clear superiority

  18. Robust Optimization of the Self- scheduling and Market Involvement for an Electricity Producer

    KAUST Repository

    Lima, Ricardo

    2015-01-07

    This work address the optimization under uncertainty of the self-scheduling, forward contracting, and pool involvement of an electricity producer operating a mixed power generation station, which combines thermal, hydro and wind sources, and uses a two-stage adaptive robust optimization approach. In this problem the wind power production and the electricity pool price are considered to be uncertain, and are described by uncertainty convex sets. Two variants of a constraint generation algorithm are proposed, namely a primal and dual version, and they are used to solve two case studies based on two different producers. Their market strategies are investigated for three different scenarios, corresponding to as many instances of electricity price forecasts. The effect of the producers’ approach, whether conservative or more risk prone, is also investigated by solving each instance for multiple values of the so-called budget parameter. It was possible to conclude that this parameter influences markedly the producers’ strategy, in terms of scheduling, profit, forward contracting, and pool involvement. Regarding the computational results, these show that for some instances, the two variants of the algorithms have a similar performance, while for a particular subset of them one variant has a clear superiority

  19. Analytics for vaccine economics and pricing: insights and observations.

    Science.gov (United States)

    Robbins, Matthew J; Jacobson, Sheldon H

    2015-04-01

    Pediatric immunization programs in the USA are a successful and cost-effective public health endeavor, profoundly reducing mortalities caused by infectious diseases. Two important issues relate to the success of the immunization programs, the selection of cost-effective vaccines and the appropriate pricing of vaccines. The recommended childhood immunization schedule, published annually by the CDC, continues to expand with respect to the number of injections required and the number of vaccines available for selection. The advent of new vaccines to meet the growing requirements of the schedule results: in a large, combinatorial number of possible vaccine formularies. The expansion of the schedule and the increase in the number of available vaccines constitutes a challenge for state health departments, large city immunization programs, private practices and other vaccine purchasers, as a cost-effective vaccine formulary must be selected from an increasingly large set of possible vaccine combinations to satisfy the schedule. The pediatric vaccine industry consists of a relatively small number of pharmaceutical firms engaged in the research, development, manufacture and distribution of pediatric vaccines. The number of vaccine manufacturers has dramatically decreased in the past few decades for a myriad of reasons, most notably due to low profitability. The contraction of the industry negatively impacts the reliable provision of pediatric vaccines. The determination of appropriate vaccine prices is an important issue and influences a vaccine manufacturer's decision to remain in the market. Operations research is a discipline that applies advanced analytical methods to improve decision making; analytics is the application of operations research to a particular problem using pertinent data to provide a practical result. Analytics provides a mechanism to resolve the challenges facing stakeholders in the vaccine development and delivery system, in particular, the selection

  20. Stochastic risk-constrained short-term scheduling of industrial cogeneration systems in the presence of demand response programs

    International Nuclear Information System (INIS)

    Alipour, Manijeh; Mohammadi-Ivatloo, Behnam; Zare, Kazem

    2014-01-01

    Highlights: • Short-term self-scheduling problem of customers with CHP units is conducted. • Power demand and pool prices are forecasted using ARIMA models. • Risk management problem is conducted by implementing CVaR methodology. • The demand response program is implemented in self-scheduling problem of CHP units. • Non-convex feasible operation region in different types of CHP units is modeled. - Abstract: This paper presents a stochastic programming framework for solving the scheduling problem faced by an industrial customer with cogeneration facilities, conventional power production system, and heat only units. The power and heat demands of the customer are supplied considering demand response (DR) programs. In the proposed DR program, the responsive load can vary in different time intervals. In the paper, the heat-power dual dependency characteristic in different types of CHP units is taken into account. In addition, a heat buffer tank, with the ability of heat storage, has been incorporated in the proposed framework. The impact of the market and load uncertainties on the scheduling problem is characterized through a stochastic programming formulation. Autoregressive integrated moving average (ARIMA) technique is used to generate the electricity price and the customer demand scenarios. The daily and weekly seasonalities of demand and market prices are taken into account in the scenario generation procedure. The conditional value-at-risk (CVaR) methodology is implemented in order to limit the risk of expected profit due to market price and load forecast volatilities

  1. Option pricing: Stock price, stock velocity and the acceleration Lagrangian

    Science.gov (United States)

    Baaquie, Belal E.; Du, Xin; Bhanap, Jitendra

    2014-12-01

    The industry standard Black-Scholes option pricing formula is based on the current value of the underlying security and other fixed parameters of the model. The Black-Scholes formula, with a fixed volatility, cannot match the market's option price; instead, it has come to be used as a formula for generating the option price, once the so called implied volatility of the option is provided as additional input. The implied volatility not only is an entire surface, depending on the strike price and maturity of the option, but also depends on calendar time, changing from day to day. The point of view adopted in this paper is that the instantaneous rate of return of the security carries part of the information that is provided by implied volatility, and with a few (time-independent) parameters required for a complete pricing formula. An option pricing formula is developed that is based on knowing the value of both the current price and rate of return of the underlying security which in physics is called velocity. Using an acceleration Lagrangian model based on the formalism of quantum mathematics, we derive the pricing formula for European call options. The implied volatility of the market can be generated by our pricing formula. Our option price is applied to foreign exchange rates and equities and the accuracy is compared with Black-Scholes pricing formula and with the market price.

  2. Estimating demand schedules in hedonic analysis

    DEFF Research Database (Denmark)

    Panduro, Toke Emil; Jensen, Cathrine Ulla; Lundhede, Thomas

    The hedonic pricing method has been used extensively to obtain implicit prices for availability of urban green space, but few hedonic studies have obtained households’ preference parameters. We estimate willingness to pay functions for park availability in Copenhagen using an approach that places...... identifying restrictions on the utility function. We do this for two different measures of park availability. We apply our results to a policy scenario and show how estimates of aggregate welfare changes are highly sensitive to the measure of park availability applied. Thus, the approach in this study applies...... an alternative path for estimation of demand schedules for public goods using hedonic data. The findings also stress the importance of paying attention to how public goods are defined when undertaking welfare economic policy analyses....

  3. Refinery scheduling

    Energy Technology Data Exchange (ETDEWEB)

    Magalhaes, Marcus V.; Fraga, Eder T. [PETROBRAS, Rio de Janeiro, RJ (Brazil); Shah, Nilay [Imperial College, London (United Kingdom)

    2004-07-01

    This work addresses the refinery scheduling problem using mathematical programming techniques. The solution adopted was to decompose the entire refinery model into a crude oil scheduling and a product scheduling problem. The envelope for the crude oil scheduling problem is composed of a terminal, a pipeline and the crude area of a refinery, including the crude distillation units. The solution method adopted includes a decomposition technique based on the topology of the system. The envelope for the product scheduling comprises all tanks, process units and products found in a refinery. Once crude scheduling decisions are Also available the product scheduling is solved using a rolling horizon algorithm. All models were tested with real data from PETROBRAS' REFAP refinery, located in Canoas, Southern Brazil. (author)

  4. Development of an irrigation scheduling software based on model predicted crop water stress

    Science.gov (United States)

    Modern irrigation scheduling methods are generally based on sensor-monitored soil moisture regimes rather than crop water stress which is difficult to measure in real-time, but can be computed using agricultural system models. In this study, an irrigation scheduling software based on RZWQM2 model pr...

  5. 73 Activity Based Costing and Product Pricing Decision: the Nigerian Case

    Directory of Open Access Journals (Sweden)

    Ebipanipre Gabriel Mieseigha

    2014-06-01

    Full Text Available This paper examined activity based costing and product pricing decisions in Nigeria so as to ascertain whether activity based costing have the ability to enhance profitability and control cost of manufacturing firms. Towards this end, a multiple correlation and regression estimation technique was used in analyzing the data obtained in the study. The study found that activity based costing affects product costing and pricing decision. In addition, the results showed that improved profitability and cost control can be achieved by implementing activity based costing approach by manufacturing firms. The implication is that traditional costing approach fails in many pricing situations by arbitrarily allocating indirect cost and activity based costing helps in allocating indirect cost accurately. Thus, it was recommended amongst others that activity based costing need to be practiced, maintained and implemented by manufacturing firms since it has a broad range of uses for a wide variety of company functions and operations in the area of process analysis, strategy support, time-based accounting, monitoring wastage, as well as quality and productivity management.

  6. Western Australian Public Opinions of a Minimum Pricing Policy for Alcohol: Study Protocol

    Science.gov (United States)

    Keatley, David A; Daube, Mike; Hardcastle, Sarah J

    2015-01-01

    Background Excessive alcohol consumption has significant adverse economic, social, and health outcomes. Recent estimates suggest that the annual economic costs of alcohol in Australia are up to AUD $36 billion. Policies influencing price have been demonstrated to be very effective in reducing alcohol consumption and alcohol-related harms. Interest in minimum pricing has gained traction in recent years. However, there has been little research investigating the level of support for the public interest case of minimum pricing in Australia. Objective This article describes protocol for a study exploring Western Australian (WA) public knowledge, understanding, and reaction to a proposed minimum price policy per standard drink. Methods The study will employ a qualitative methodological design. Participants will be recruited from a wide variety of backgrounds, including ethnic minorities, blue and white collar workers, unemployed, students, and elderly/retired populations to participate in focus groups. Focus group participants will be asked about their knowledge of, and initial reactions to, the proposed policy and encouraged to discuss how such a proposal may affect their own alcohol use and alcohol consumption at the population level. Participants will also be asked to discuss potential avenues for increasing acceptability of the policy. The focus groups will adopt a semi-structured, open-ended approach guided by a question schedule. The schedule will be based on feedback from pilot samples, previous research, and a steering group comprising experts in alcohol policy and pricing. Results The study is expected to take approximately 14 months to complete. Conclusions The findings will be of considerable interest and relevance to government officials, policy makers, researchers, advocacy groups, alcohol retail and licensed establishments and organizations, city and town planners, police, and other stakeholder organizations. PMID:26582408

  7. Risk Based Milk Pricing Model at Dairy Farmers Level

    Directory of Open Access Journals (Sweden)

    W. Septiani

    2017-12-01

    Full Text Available The milk price from a cooperative institution to farmer does not fully cover the production cost. Though, dairy farmers encounter various risks and uncertainties in conducting their business. The highest risk in milk supply lies in the activities at the farm. This study was designed to formulate a model for calculating milk price at farmer’s level based on risk. Risks that occur on farms include the risk of cow breeding, sanitation, health care, cattle feed management, milking and milk sales. This research used the location of the farm in West Java region. There were five main stages in the preparation of this model, (1 identification and analysis of influential factors, (2 development of a conceptual model, (3 structural analysis and the amount of production costs, (4 model calculation of production cost with risk factors, and (5 risk based milk pricing model. This research built a relationship between risks on smallholder dairy farms with the production costs to be incurred by the farmers. It was also obtained the formulation of risk adjustment factor calculation for the variable costs of production in dairy cattle farm. The difference in production costs with risk and the total production cost without risk was about 8% to 10%. It could be concluded that the basic price of milk proposed based on the research was around IDR 4,250-IDR 4,350/L for 3 to 4 cows ownership. Increasing farmer income was expected to be obtained by entering the value of this risk in the calculation of production costs. 

  8. Estimating the Own-Price Elasticity for Irrigation Water in the Musi Catchment of India

    NARCIS (Netherlands)

    Hellegers, P.J.G.J.; Davidson, B.

    2011-01-01

    As irrigation water is an input into a production process, its demand must be ‘derived’. According to theory, a derived demand schedule should be downward sloping and dependent on the outputs produced from it, the prices of other inputs and the price of the water itself. Problems arise when an

  9. An electricity price model with consideration to load and gas price effects.

    Science.gov (United States)

    Huang, Min-xiang; Tao, Xiao-hu; Han, Zhen-xiang

    2003-01-01

    Some characteristics of the electricity load and prices are studied, and the relationship between electricity prices and gas (fuel) prices is analyzed in this paper. Because electricity prices are strongly dependent on load and gas prices, the authors constructed a model for electricity prices based on the effects of these two factors; and used the Geometric Mean Reversion Brownian Motion (GMRBM) model to describe the electricity load process, and a Geometric Brownian Motion(GBM) model to describe the gas prices; deduced the price stochastic process model based on the above load model and gas price model. This paper also presents methods for parameters estimation, and proposes some methods to solve the model.

  10. The Home Care Crew Scheduling Problem

    DEFF Research Database (Denmark)

    Rasmussen, Matias Sevel; Justesen, Tor

    In the Home Care Crew Scheduling Problem (HCCSP) a staff of caretakers has to be assigned a number of visits, such that the total number of assigned visits is maximised. The visits have different locations and positions in time, and travelling time and time windows must be respected. The challenge...... when assigning visits to caretakers lies in the existence of soft constraints and indeed also in temporal dependencies between the starting times of visits. Most former approaches to solving the HCCSP involve the use of heuristic methods. Here we develop an exact branch-and-price algorithm that uses...... clustering of the visits based on the problem structure. The algorithm is tested on real-life problem instances and we obtain solutions that are better than current practice in all cases....

  11. A Simple Operating Strategy of Small-Scale Battery Energy Storages for Energy Arbitrage under Dynamic Pricing Tariffs

    Directory of Open Access Journals (Sweden)

    Enrico Telaretti

    2015-12-01

    Full Text Available Price arbitrage involves taking advantage of an electricity price difference, storing electricity during low-prices times, and selling it back to the grid during high-prices periods. This strategy can be exploited by customers in presence of dynamic pricing schemes, such as hourly electricity prices, where the customer electricity cost may vary at any hour of day, and power consumption can be managed in a more flexible and economical manner, taking advantage of the price differential. Instead of modifying their energy consumption, customers can install storage systems to reduce their electricity bill, shifting the energy consumption from on-peak to off-peak hours. This paper develops a detailed storage model linking together technical, economic and electricity market parameters. The proposed operating strategy aims to maximize the profit of the storage owner (electricity customer under simplifying assumptions, by determining the optimal charge/discharge schedule. The model can be applied to several kinds of storages, although the simulations refer to three kinds of batteries: lead-acid, lithium-ion (Li-ion and sodium-sulfur (NaS batteries. Unlike literature reviews, often requiring an estimate of the end-user load profile, the proposed operation strategy is able to properly identify the battery-charging schedule, relying only on the hourly price profile, regardless of the specific facility’s consumption, thanks to some simplifying assumptions in the sizing and the operation of the battery. This could be particularly useful when the customer load profile cannot be scheduled with sufficient reliability, because of the uncertainty inherent in load forecasting. The motivation behind this research is that storage devices can help to lower the average electricity prices, increasing flexibility and fostering the integration of renewable sources into the power system.

  12. NASA scheduling technologies

    Science.gov (United States)

    Adair, Jerry R.

    1994-01-01

    This paper is a consolidated report on ten major planning and scheduling systems that have been developed by the National Aeronautics and Space Administration (NASA). A description of each system, its components, and how it could be potentially used in private industry is provided in this paper. The planning and scheduling technology represented by the systems ranges from activity based scheduling employing artificial intelligence (AI) techniques to constraint based, iterative repair scheduling. The space related application domains in which the systems have been deployed vary from Space Shuttle monitoring during launch countdown to long term Hubble Space Telescope (HST) scheduling. This paper also describes any correlation that may exist between the work done on different planning and scheduling systems. Finally, this paper documents the lessons learned from the work and research performed in planning and scheduling technology and describes the areas where future work will be conducted.

  13. Drug Pricing Reforms

    DEFF Research Database (Denmark)

    Kaiser, Ulrich; Mendez, Susan J.; Rønde, Thomas

    2015-01-01

    Reference price systems for prescription drugs have found widespread use as cost containment tools. Under such regulatory regimes, patients co-pay a fraction of the difference between pharmacy retail price of the drug and a reference price. Reference prices are either externally (based on drug...... prices in other countries) or internally (based on domestic drug prices) determined. In a recent study, we analysed the effects of a change from external to internal reference pricing in Denmark in 2005, finding that the reform led to substantial reductions in prices, producer revenues, and expenditures...... for patients and the health insurance system. We also estimated an increase in consumer welfare but the size effect depends on whether or not perceived quality differences between branded and other drugs are taken into account....

  14. Stochastic profit-based scheduling of industrial virtual power plant using the best demand response strategy

    International Nuclear Information System (INIS)

    Nosratabadi, Seyyed Mostafa; Hooshmand, Rahmat-Allah; Gholipour, Eskandar

    2016-01-01

    Highlights: • VPPs and IVPPs are defined for energy management of aggregated generations. • IVPP can manage industrial microgrid containing some relevant load and generation. • A stochastic modeling is proposed to schedule optimal generations in competition market. • Wind generation and day-ahead and spot market prices are considered to be stochastic. • A new DRL program selection scheme is presented in the scheduling procedure. - Abstract: One of the main classified microgrids in a power system is the industrial microgrid. Due to its behaviors and the heavy loads, its energy management is challengeable. Virtual Power Plant (VPP) can be an important concept in managing such problems in this kind of grids. Here, a transmission power system is considered as a Regional Electric Company (REC) and the VPPs comprising Distributed Generation (DG) units and Demand Response Loads (DRLs) are determined in this system. This paper focuses on Industrial VPP (IVPP) and its management. An IVPP can be determined as a management unit comprising generations and loads in an industrial microgrid. Since the scheduling procedure for these units is very important for their participation in a short-term electric market, a stochastic formulation is proposed for power scheduling in VPPs especially in IVPPs in this paper. By introducing the DRL programs and using the proposed modeling, the operator can select the best DRL program for each VPP in a scheduling procedure. In this regard, a suitable approach is presented to determine the proposed formulation and its solution in a Mixed Integer Non-Linear Programming (MINLP). To validate the performance of the proposed method, the IEEE Reliability Test System (IEEE-RTS) is considered to apply the method on it, while some challenging aspects are presented.

  15. Agent-based scheduling for aircraft deicing

    NARCIS (Netherlands)

    Mao, X.; Ter Mors, A.W.; Roos, N.; Witteveen, C.

    2006-01-01

    The planning and scheduling of the deicing and anti-icing activities is an important and challenging part of airport departure planning. Deicing planning has to be done in a highly dynamic environment involving several autonomous and self-interested parties. Traditional centralized scheduling

  16. Wireless-Uplinks-Based Energy-Efficient Scheduling in Mobile Cloud Computing

    Directory of Open Access Journals (Sweden)

    Xing Liu

    2015-01-01

    Full Text Available Mobile cloud computing (MCC combines cloud computing and mobile internet to improve the computational capabilities of resource-constrained mobile devices (MDs. In MCC, mobile users could not only improve the computational capability of MDs but also save operation consumption by offloading the mobile applications to the cloud. However, MCC faces the problem of energy efficiency because of time-varying channels when the offloading is being executed. In this paper, we address the issue of energy-efficient scheduling for wireless uplink in MCC. By introducing Lyapunov optimization, we first propose a scheduling algorithm that can dynamically choose channel to transmit data based on queue backlog and channel statistics. Then, we show that the proposed scheduling algorithm can make a tradeoff between queue backlog and energy consumption in a channel-aware MCC system. Simulation results show that the proposed scheduling algorithm can reduce the time average energy consumption for offloading compared to the existing algorithm.

  17. Price fairness

    OpenAIRE

    Diller, Hermann

    2013-01-01

    Purpose – The purpose of this article is to integrate the various strands of fair price research into a concise conceptual model. Design/methodology/approach – The proposed price fairness model is based on a review of the fair pricing literature, incorporating research reported in not only English but also German. Findings – The proposed fair price model depicts seven components of a fair price: distributive fairness, consistent behaviour, personal respect and regard for the partner, fair dea...

  18. Finding the multipath propagation of multivariable crude oil prices using a wavelet-based network approach

    Science.gov (United States)

    Jia, Xiaoliang; An, Haizhong; Sun, Xiaoqi; Huang, Xuan; Gao, Xiangyun

    2016-04-01

    The globalization and regionalization of crude oil trade inevitably give rise to the difference of crude oil prices. The understanding of the pattern of the crude oil prices' mutual propagation is essential for analyzing the development of global oil trade. Previous research has focused mainly on the fuzzy long- or short-term one-to-one propagation of bivariate oil prices, generally ignoring various patterns of periodical multivariate propagation. This study presents a wavelet-based network approach to help uncover the multipath propagation of multivariable crude oil prices in a joint time-frequency period. The weekly oil spot prices of the OPEC member states from June 1999 to March 2011 are adopted as the sample data. First, we used wavelet analysis to find different subseries based on an optimal decomposing scale to describe the periodical feature of the original oil price time series. Second, a complex network model was constructed based on an optimal threshold selection to describe the structural feature of multivariable oil prices. Third, Bayesian network analysis (BNA) was conducted to find the probability causal relationship based on periodical structural features to describe the various patterns of periodical multivariable propagation. Finally, the significance of the leading and intermediary oil prices is discussed. These findings are beneficial for the implementation of periodical target-oriented pricing policies and investment strategies.

  19. Model-based schedulability analysis of safety critical hard real-time Java programs

    DEFF Research Database (Denmark)

    Bøgholm, Thomas; Kragh-Hansen, Henrik; Olsen, Petur

    2008-01-01

    verifiable by the Uppaal model checker [23]. Schedulability analysis is reduced to a simple reachability question, checking for deadlock freedom. Model-based schedulability analysis has been developed by Amnell et al. [2], but has so far only been applied to high level specifications, not actual...

  20. Scheduling algorithm for data relay satellite optical communication based on artificial intelligent optimization

    Science.gov (United States)

    Zhao, Wei-hu; Zhao, Jing; Zhao, Shang-hong; Li, Yong-jun; Wang, Xiang; Dong, Yi; Dong, Chen

    2013-08-01

    Optical satellite communication with the advantages of broadband, large capacity and low power consuming broke the bottleneck of the traditional microwave satellite communication. The formation of the Space-based Information System with the technology of high performance optical inter-satellite communication and the realization of global seamless coverage and mobile terminal accessing are the necessary trend of the development of optical satellite communication. Considering the resources, missions and restraints of Data Relay Satellite Optical Communication System, a model of optical communication resources scheduling is established and a scheduling algorithm based on artificial intelligent optimization is put forwarded. According to the multi-relay-satellite, multi-user-satellite, multi-optical-antenna and multi-mission with several priority weights, the resources are scheduled reasonable by the operation: "Ascertain Current Mission Scheduling Time" and "Refresh Latter Mission Time-Window". The priority weight is considered as the parameter of the fitness function and the scheduling project is optimized by the Genetic Algorithm. The simulation scenarios including 3 relay satellites with 6 optical antennas, 12 user satellites and 30 missions, the simulation result reveals that the algorithm obtain satisfactory results in both efficiency and performance and resources scheduling model and the optimization algorithm are suitable in multi-relay-satellite, multi-user-satellite, and multi-optical-antenna recourses scheduling problem.

  1. EV Charging Algorithm Implementation with User Price Preference

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Bin; Hu, Boyang; Qiu, Charlie; Chu, Peter; Gadh, Rajit

    2015-02-17

    in this paper, we propose and implement a smart Electric Vehicle (EV) charging algorithm to control the EV charging infrastructures according to users’ price preferences. EVSE (Electric Vehicle Supply Equipment), equipped with bidirectional communication devices and smart meters, can be remotely monitored by the proposed charging algorithm applied to EV control center and mobile app. On the server side, ARIMA model is utilized to fit historical charging load data and perform day-ahead prediction. A pricing strategy with energy bidding policy is proposed and implemented to generate a charging price list to be broadcasted to EV users through mobile app. On the user side, EV drivers can submit their price preferences and daily travel schedules to negotiate with Control Center to consume the expected energy and minimize charging cost simultaneously. The proposed algorithm is tested and validated through the experimental implementations in UCLA parking lots.

  2. The Earnings/Price Risk Factor in Capital Asset Pricing Models

    Directory of Open Access Journals (Sweden)

    Rafael Falcão Noda

    2015-01-01

    Full Text Available This article integrates the ideas from two major lines of research on cost of equity and asset pricing: multi-factor models and ex ante accounting models. The earnings/price ratio is used as a proxy for the ex ante cost of equity, in order to explain realized returns of Brazilian companies within the period from 1995 to 2013. The initial finding was that stocks with high (low earnings/price ratios have higher (lower risk-adjusted realized returns, already controlled by the capital asset pricing model's beta. The results show that selecting stocks based on high earnings/price ratios has led to significantly higher risk-adjusted returns in the Brazilian market, with average abnormal returns close to 1.3% per month. We design asset pricing models including an earnings/price risk factor, i.e. high earnings minus low earnings, based on the Fama and French three-factor model. We conclude that such a risk factor is significant to explain returns on portfolios, even when controlled by size and market/book ratios. Models including the high earnings minus low earnings risk factor were better to explain stock returns in Brazil when compared to the capital asset pricing model and to the Fama and French three-factor model, having the lowest number of significant intercepts. These findings may be due to the impact of historically high inflation rates, which reduce the information content of book values, thus making the models based on earnings/price ratios better than those based on market/book ratios. Such results are different from those obtained in more developed markets and the superiority of the earnings/price ratio for asset pricing may also exist in other emerging markets.

  3. Deadline based scheduling for data-intensive applications in clouds

    Institute of Scientific and Technical Information of China (English)

    Fu Xiong; Cang Yeliang; Zhu Lipeng; Hu Bin; Deng Song; Wang Dong

    2016-01-01

    Cloud computing emerges as a new computing pattern that can provide elastic services for any users around the world.It provides good chances to solve large scale scientific problems with fewer efforts.Application deployment remains an important issue in clouds.Appropriate scheduling mechanisms can shorten the total completion time of an application and therefore improve the quality of service (QoS) for cloud users.Unlike current scheduling algorithms which mostly focus on single task allocation,we propose a deadline based scheduling approach for data-intensive applications in clouds.It does not simply consider the total completion time of an application as the sum of all its subtasks' completion time.Not only the computation capacity of virtual machine (VM) is considered,but also the communication delay and data access latencies are taken into account.Simulations show that our proposed approach has a decided advantage over the two other algorithms.

  4. Information pricing based on trusted system

    Science.gov (United States)

    Liu, Zehua; Zhang, Nan; Han, Hongfeng

    2018-05-01

    Personal information has become a valuable commodity in today's society. So our goal aims to develop a price point and a pricing system to be realistic. First of all, we improve the existing BLP system to prevent cascading incidents, design a 7-layer model. Through the cost of encryption in each layer, we develop PI price points. Besides, we use association rules mining algorithms in data mining algorithms to calculate the importance of information in order to optimize informational hierarchies of different attribute types when located within a multi-level trusted system. Finally, we use normal distribution model to predict encryption level distribution for users in different classes and then calculate information prices through a linear programming model with the help of encryption level distribution above.

  5. The effects of residential real-time pricing contracts on transco loads, pricing, and profitability: Simulations using the N-ABLE trademark agent-based model

    International Nuclear Information System (INIS)

    Ehlen, Mark A.; Scholand, Andrew J.; Stamber, Kevin L.

    2007-01-01

    An agent-based model is constructed in which a demand aggregator sells both uniform-price and real-time price (RTP) contracts to households as means for adding price elasticity in residential power use sectors, particularly during peak-price hours of the day. Simulations suggest that RTP contracts help a demand aggregator (1) shift its long-term contracts toward off-peak hours, thereby reducing its cost of power and (2) increase its short-run profits if it is one of the first aggregators to have large numbers of RTP contracts; but (3) create susceptibilities to short-term market demand and price volatilities. (author)

  6. Project Scheduling Heuristics-Based Standard PSO for Task-Resource Assignment in Heterogeneous Grid

    Directory of Open Access Journals (Sweden)

    Ruey-Maw Chen

    2011-01-01

    Full Text Available The task scheduling problem has been widely studied for assigning resources to tasks in heterogeneous grid environment. Effective task scheduling is an important issue for the performance of grid computing. Meanwhile, the task scheduling problem is an NP-complete problem. Hence, this investigation introduces a named “standard“ particle swarm optimization (PSO metaheuristic approach to efficiently solve the task scheduling problems in grid. Meanwhile, two promising heuristics based on multimode project scheduling are proposed to help in solving interesting scheduling problems. They are the best performance resource heuristic and the latest finish time heuristic. These two heuristics applied to the PSO scheme are for speeding up the search of the particle and improving the capability of finding a sound schedule. Moreover, both global communication topology and local ring communication topology are also investigated for efficient study of proposed scheme. Simulation results demonstrate that the proposed approach in this investigation can successfully solve the task-resource assignment problems in grid computing and similar scheduling problems.

  7. A new approach for crude oil price prediction based on stream learning

    Directory of Open Access Journals (Sweden)

    Shuang Gao

    2017-01-01

    Full Text Available Crude oil is the world's leading fuel, and its prices have a big impact on the global environment, economy as well as oil exploration and exploitation activities. Oil price forecasts are very useful to industries, governments and individuals. Although many methods have been developed for predicting oil prices, it remains one of the most challenging forecasting problems due to the high volatility of oil prices. In this paper, we propose a novel approach for crude oil price prediction based on a new machine learning paradigm called stream learning. The main advantage of our stream learning approach is that the prediction model can capture the changing pattern of oil prices since the model is continuously updated whenever new oil price data are available, with very small constant overhead. To evaluate the forecasting ability of our stream learning model, we compare it with three other popular oil price prediction models. The experiment results show that our stream learning model achieves the highest accuracy in terms of both mean squared prediction error and directional accuracy ratio over a variety of forecast time horizons.

  8. Political Economy and Irrigation Technology Adoption Implications of Water Pricing under Asymmetric Information

    OpenAIRE

    Dridi, Chokri; Khanna, Madhu

    2005-01-01

    We analyze the design of water pricing rules emerging from farmers' lobbying and their implications for the size of the lobby, water use, profits and social welfare. The lobbying groups are the adopters of modern irrigation technology and the non-adopters. The pricing rules are designed to meet budget balance of water provision; we considered (i) a two-part tariff composed of a mandatory per-acre fee plus a volumetric charge and (ii) a nonlinear pricing schedule. Our results show that under e...

  9. Technology Timing and Pricing In the Presence of an Installed Base

    OpenAIRE

    Qiu_Hong Wang; Kai-Lung Hui

    2005-01-01

    This paper studies a vendor.s timing and pricing strategies to tackle its own installed base when selling a newly improved product. We characterize the market with either a partly- or fully- covered installed base, consumers. relative willingness to pay for the newly improved version of the product, and their relative payoffs from delayed purchase. Instead of using the conventional assumption of constant consumer reservation price, we propose that if consumers already own an existing (old) ve...

  10. Optimal Electricity Charge Strategy Based on Price Elasticity of Demand for Users

    Science.gov (United States)

    Li, Xin; Xu, Daidai; Zang, Chuanzhi

    The price elasticity is very important for the prediction of electricity demand. This paper mainly establishes the price elasticity coefficient for electricity in single period and inter-temporal. Then, a charging strategy is established based on these coefficients. To evaluate the strategy proposed, simulations of the two elastic coefficients are carried out based on the history data of a certain region.

  11. Wavelet-based prediction of oil prices

    International Nuclear Information System (INIS)

    Yousefi, Shahriar; Weinreich, Ilona; Reinarz, Dominik

    2005-01-01

    This paper illustrates an application of wavelets as a possible vehicle for investigating the issue of market efficiency in futures markets for oil. The paper provides a short introduction to the wavelets and a few interesting wavelet-based contributions in economics and finance are briefly reviewed. A wavelet-based prediction procedure is introduced and market data on crude oil is used to provide forecasts over different forecasting horizons. The results are compared with data from futures markets for oil and the relative performance of this procedure is used to investigate whether futures markets are efficiently priced

  12. Tramp ship routing and scheduling with integrated bunker optimization

    DEFF Research Database (Denmark)

    Vilhelmsen, Charlotte; Lusby, Richard Martin; Larsen, Jesper

    2014-01-01

    is referred to as bunker and bunker costs constitute a significant part of the daily operating costs. There can be great variations in bunker prices across bunker ports so it is important to carefully plan bunkering for each ship. As ships operate 24 hours a day, they must refuel during operations. Therefore...... and scheduling phase and present a mixed integer programming formulation for the integrated problem of optimally routing, scheduling and bunkering a tramp fleet. Aside from the integration of bunker, this model also extends standard tramp formulations by using load dependent costs, speed and bunker consumption...

  13. Value-based pricing: A success factor in the competitive struggle

    Directory of Open Access Journals (Sweden)

    Netseva-Porcheva Tatyana

    2011-01-01

    Full Text Available Over the past decade, the view that the main purpose of market oriented organizations is not to satisfy the consumer, but to create values has dominated. Exactly the values, their creation, retention and increase, are the main sources of competitive advantage of the company. The purpose of the present report is to present the price formation, based on product value, as a source of competitive advantage. In connection with the so-defined objective, the value and the product price for the customer are derived as key factors for success of the company in the competitive struggle; the role of the value of the product in the marketing and pricing is revealed; and theory clarifies the two basic approaches for determining the price of the product on the basis of value - customer value modeling (CVM and economic value modeling (EVM, their nature, scope of application, advantages and disadvantages.

  14. T-L Plane Abstraction-Based Energy-Efficient Real-Time Scheduling for Multi-Core Wireless Sensors

    Directory of Open Access Journals (Sweden)

    Youngmin Kim

    2016-07-01

    Full Text Available Energy efficiency is considered as a critical requirement for wireless sensor networks. As more wireless sensor nodes are equipped with multi-cores, there are emerging needs for energy-efficient real-time scheduling algorithms. The T-L plane-based scheme is known to be an optimal global scheduling technique for periodic real-time tasks on multi-cores. Unfortunately, there has been a scarcity of studies on extending T-L plane-based scheduling algorithms to exploit energy-saving techniques. In this paper, we propose a new T-L plane-based algorithm enabling energy-efficient real-time scheduling on multi-core sensor nodes with dynamic power management (DPM. Our approach addresses the overhead of processor mode transitions and reduces fragmentations of the idle time, which are inherent in T-L plane-based algorithms. Our experimental results show the effectiveness of the proposed algorithm compared to other energy-aware scheduling methods on T-L plane abstraction.

  15. Applying Activity Based Costing (ABC) Method to Calculate Cost Price in Hospital and Remedy Services.

    Science.gov (United States)

    Rajabi, A; Dabiri, A

    2012-01-01

    Activity Based Costing (ABC) is one of the new methods began appearing as a costing methodology in the 1990's. It calculates cost price by determining the usage of resources. In this study, ABC method was used for calculating cost price of remedial services in hospitals. To apply ABC method, Shahid Faghihi Hospital was selected. First, hospital units were divided into three main departments: administrative, diagnostic, and hospitalized. Second, activity centers were defined by the activity analysis method. Third, costs of administrative activity centers were allocated into diagnostic and operational departments based on the cost driver. Finally, with regard to the usage of cost objectives from services of activity centers, the cost price of medical services was calculated. The cost price from ABC method significantly differs from tariff method. In addition, high amount of indirect costs in the hospital indicates that capacities of resources are not used properly. Cost price of remedial services with tariff method is not properly calculated when compared with ABC method. ABC calculates cost price by applying suitable mechanisms but tariff method is based on the fixed price. In addition, ABC represents useful information about the amount and combination of cost price services.

  16. Enhanced round robin CPU scheduling with burst time based time quantum

    Science.gov (United States)

    Indusree, J. R.; Prabadevi, B.

    2017-11-01

    Process scheduling is a very important functionality of Operating system. The main-known process-scheduling algorithms are First Come First Serve (FCFS) algorithm, Round Robin (RR) algorithm, Priority scheduling algorithm and Shortest Job First (SJF) algorithm. Compared to its peers, Round Robin (RR) algorithm has the advantage that it gives fair share of CPU to the processes which are already in the ready-queue. The effectiveness of the RR algorithm greatly depends on chosen time quantum value. Through this research paper, we are proposing an enhanced algorithm called Enhanced Round Robin with Burst-time based Time Quantum (ERRBTQ) process scheduling algorithm which calculates time quantum as per the burst-time of processes already in ready queue. The experimental results and analysis of ERRBTQ algorithm clearly indicates the improved performance when compared with conventional RR and its variants.

  17. Web-Based Requesting and Scheduling Use of Facilities

    Science.gov (United States)

    Yeager, Carolyn M.

    2010-01-01

    Automated User's Training Operations Facility Utilization Request (AutoFUR) is prototype software that administers a Web-based system for requesting and allocating facilities and equipment for astronaut-training classes in conjunction with scheduling the classes. AutoFUR also has potential for similar use in such applications as scheduling flight-simulation equipment and instructors in commercial airplane-pilot training, managing preventive- maintenance facilities, and scheduling operating rooms, doctors, nurses, and medical equipment for surgery. Whereas requesting and allocation of facilities was previously a manual process that entailed examination of documents (including paper drawings) from different sources, AutoFUR partly automates the process and makes all of the relevant information available via the requester s computer. By use of AutoFUR, an instructor can fill out a facility-utilization request (FUR) form on line, consult the applicable flight manifest(s) to determine what equipment is needed and where it should be placed in the training facility, reserve the corresponding hardware listed in a training-hardware inventory database, search for alternative hardware if necessary, submit the FUR for processing, and cause paper forms to be printed. Auto-FUR also maintains a searchable archive of prior FURs.

  18. New market based price regulation on combined heat and power in Denmark

    International Nuclear Information System (INIS)

    Koch, Jesper; Nielsen, Marianne; Hansen, Anders B.; Lawaetz, Henrik

    2003-01-01

    Major economic risks can become reality when local co-generation plants (L-CHP ) meet the full market penetration with new market based price regulation. Co-generation produces more than 50% of the national electricity consumption and half of the production is generated from L-CHP. The new price regulation is assumed to take action in 2004. The paper will present an analysis of a market based price regulation on the L-CHP-sector. The paper will spotlight on L-CHP in district heating systems supplying heat for domestic purposes. When smaller and medium sized CHP sell electricity they are paid an average price of 46 Euro per MWh. The return of selling electricity shall primarily cover the expenditure of buying gas for electricity production and writing off investments cost of a CHP-plant. With the framework of today it is a fact that the plants (in average) are only slightly competitive compared to individual heat production plants. When CHP meet market conditions there is a high risk that electricity prices will be reduced significantly (prices of 20 - 30 Euro per MWh) for a longer period. Significantly reduced electricity prices will result in dramatically increased heat prices. If no action is taken there will be a potential risk that heat consumers in the smaller and medium sized cities together must pay an extra bill of 200 million Euro each year. It corresponds to an average increase of the heating bill of 300 - 500 Euro per year for an average house. This is far from acceptable. There will also be a high risk that companies with industrial CHP will permanently convert to heat only boiler and only use their CHP occasionally because CHP plants might not be cost-effective when electricity prices are low. These effects can cause a significant increase of the national CO 2 emission

  19. Financial sustainability for a lignocellulosic biorefinery under carbon constraints and price downside risk

    International Nuclear Information System (INIS)

    Cheng, Lingfeng; Anderson, C. Lindsay

    2016-01-01

    Highlights: • Stochastic program determines production, risk management strategy for biorefinery. • Scheduled production commitment decreases as tiered carbon tax rate increases. • Risk averse producers prefer the forward contract as a mode of product sales. • Time varying forward prices and inventory enable producers to increase profits. • Inventory is beneficial to producers, below the threshold for inventory costs. - Abstract: The development of an environmentally sustainable and financially viable replacement for fossil fuels continues to elude industry investors even though the benefits of replacing them is undisputed. Biofuels are among the promising replacements for fossil fuels. However, the development and production process for bio-based fuels creates uncertainty for industry investors. In order to increase process profitability, financial tools can be implemented with current technology. This paper proposes the use of forward contracts to mitigate risk, and it also considers the impact of carbon tax constraints and price uncertainty. Specifically, a stochastic optimization approach is implemented to develop strategies, which increases the net present value (NPV) of a production facility through determination of an optimal production schedule, as well as the creation of a portfolio of forward contracts to reduce product price risk. Results of numerical case studies show that if the policymaker is risk averse, production is higher in the early planning period rather than the later period. This paper also investigates the ability to maintain inventory in order to create additional financial benefit.

  20. Short-term electricity price forecast based on the improved hybrid model

    International Nuclear Information System (INIS)

    Dong Yao; Wang Jianzhou; Jiang He; Wu Jie

    2011-01-01

    Highlights: → The proposed models can detach high volatility and daily seasonality of electricity price. → The improved hybrid forecast models can make full use of the advantages of individual models. → The proposed models create commendable improvements that are relatively satisfactorily for current research. → The proposed models do not require making complicated decisions about the explicit form. - Abstract: Half-hourly electricity price in power system are volatile, electricity price forecast is significant information which can help market managers and participants involved in electricity market to prepare their corresponding bidding strategies to maximize their benefits and utilities. However, the fluctuation of electricity price depends on the common effect of many factors and there is a very complicated random in its evolution process. Therefore, it is difficult to forecast half-hourly prices with traditional only one model for different behaviors of half-hourly prices. This paper proposes the improved forecasting model that detaches high volatility and daily seasonality for electricity price of New South Wales in Australia based on Empirical Mode Decomposition, Seasonal Adjustment and Autoregressive Integrated Moving Average. The prediction errors are analyzed and compared with the ones obtained from the traditional Seasonal Autoregressive Integrated Moving Average model. The comparisons demonstrate that the proposed model can improve the prediction accuracy noticeably.

  1. Short-term electricity price forecast based on the improved hybrid model

    Energy Technology Data Exchange (ETDEWEB)

    Dong Yao, E-mail: dongyao20051987@yahoo.cn [School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000 (China); Wang Jianzhou, E-mail: wjz@lzu.edu.cn [School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000 (China); Jiang He; Wu Jie [School of Mathematics and Statistics, Lanzhou University, Lanzhou 730000 (China)

    2011-08-15

    Highlights: {yields} The proposed models can detach high volatility and daily seasonality of electricity price. {yields} The improved hybrid forecast models can make full use of the advantages of individual models. {yields} The proposed models create commendable improvements that are relatively satisfactorily for current research. {yields} The proposed models do not require making complicated decisions about the explicit form. - Abstract: Half-hourly electricity price in power system are volatile, electricity price forecast is significant information which can help market managers and participants involved in electricity market to prepare their corresponding bidding strategies to maximize their benefits and utilities. However, the fluctuation of electricity price depends on the common effect of many factors and there is a very complicated random in its evolution process. Therefore, it is difficult to forecast half-hourly prices with traditional only one model for different behaviors of half-hourly prices. This paper proposes the improved forecasting model that detaches high volatility and daily seasonality for electricity price of New South Wales in Australia based on Empirical Mode Decomposition, Seasonal Adjustment and Autoregressive Integrated Moving Average. The prediction errors are analyzed and compared with the ones obtained from the traditional Seasonal Autoregressive Integrated Moving Average model. The comparisons demonstrate that the proposed model can improve the prediction accuracy noticeably.

  2. A multi-group and preemptable scheduling of cloud resource based on HTCondor

    Science.gov (United States)

    Jiang, Xiaowei; Zou, Jiaheng; Cheng, Yaodong; Shi, Jingyan

    2017-10-01

    Due to the features of virtual machine-flexibility, easy controlling and various system environments, more and more fields utilize the virtualization technology to construct the distributed system with the virtual resources, also including high energy physics. This paper introduce a method used in high energy physics that supports multiple resource group and preemptable cloud resource scheduling, combining virtual machine with HTCondor (a batch system). It makes resource controlling more flexible and more efficient and makes resource scheduling independent of job scheduling. Firstly, the resources belong to different experiment-groups, and the type of user-groups mapping to resource-groups(same as experiment-group) is one-to-one or many-to-one. In order to make the confused group simply to be managed, we designed the permission controlling component to ensure that the different resource-groups can get the suitable jobs. Secondly, for the purpose of elastically allocating resources for suitable resource-group, it is necessary to schedule resources like scheduling jobs. So this paper designs the cloud resource scheduling to maintain a resource queue and allocate an appropriate amount of virtual resources to the request resource-group. Thirdly, in some kind of situations, because of the resource occupied for a long time, resources need to be preempted. This paper adds the preemption function for the resource scheduling that implement resource preemption based on the group priority. Additionally, the way to preempting is soft that when virtual resources are preempted, jobs will not be killed but also be held and rematched later. It is implemented with the help of HTCondor, storing the held job information in scheduler, releasing the job to idle status and doing second matcher. In IHEP (institute of high energy physics), we have built a batch system based on HTCondor with a virtual resources pool based on Openstack. And this paper will show some cases of experiment JUNO

  3. Nonlinear Pricing of Information Goods

    OpenAIRE

    Arun Sundararajan

    2003-01-01

    This paper analyzes optimal pricing for information goods under incomplete information, when both unlimited-usage (fixed-fee) pricing and usage-based pricing are feasible, and administering usage-based pricing may involve transaction costs. It is shown that offering fixed- fee pricing in addition to a non-linear usage-based pricing scheme is always profit-improving in the presence of any non-zero transaction costs, and there may be markets in which a pure fixed-fee is optimal. This implies th...

  4. Option-Based Estimation of the Price of Co-Skewness and Co-Kurtosis Risk

    DEFF Research Database (Denmark)

    Christoffersen, Peter; Fournier, Mathieu; Fournier, Mathieu

    -neutral second moments, and the price of co-kurtosis risk corresponds to the spread between the physical and the risk-neutral third moments. The option-based estimates of the prices of risk lead to reasonable values of the associated risk premia. An out-of-sample analysis of factor models with co-skewness and co......We show that the prices of risk for factors that are nonlinear in the market return are readily obtained using index option prices. We apply this insight to the price of co-skewness and co-kurtosis risk. The price of co-skewness risk corresponds to the spread between the physical and the risk......-kurtosis risk indicates that the new estimates of the price of risk improve the models performance. Models with higher-order market moments also robustly outperform standard competitors such as the CAPM and the Fama-French model....

  5. Option-Based Estimation of the Price of Co-Skewness and Co-Kurtosis Risk

    DEFF Research Database (Denmark)

    Christoffersen, Peter; Fournier, Mathieu; Jacobs, Kris

    -neutral second moments, and the price of co-kurtosis risk corresponds to the spread between the physical and the risk-neutral third moments. The option-based estimates of the prices of risk lead to reasonable values of the associated risk premia. An out-of-sample analysis of factor models with co-skewness and co......We show that the prices of risk for factors that are nonlinear in the market return are readily obtained using index option prices. We apply this insight to the price of co-skewness and co-kurtosis risk. The price of co-skewness risk corresponds to the spread between the physical and the risk......-kurtosis risk indicates that the new estimates of the price of risk improve the models' performance. Models with higher-order market moments also robustly outperform standard competitors such as the CAPM and the Fama-French model....

  6. Consensus based scheduling of storage capacities in a virtual microgrid

    DEFF Research Database (Denmark)

    Brehm, Robert; Top, Søren; Mátéfi-Tempfli, Stefan

    2017-01-01

    We present a distributed, decentralized method for coordinated scheduling of charge/discharge intervals of storage capacities in a utility grid integrated microgrid. The decentralized algorithm is based on a consensus scheme and solves an optimisation problem with the objective of minimising......, by use of storage capacities, the power flow over a transformer substation from/to the utility grid integrated microgrid. It is shown that when using this coordinated scheduling algorithm, load profile flattening (peak-shaving) for the utility grid is achieved. Additionally, mutual charge...

  7. Price adjustment for traditional Chinese medicine procedures: Based on a standardized value parity model.

    Science.gov (United States)

    Wang, Haiyin; Jin, Chunlin; Jiang, Qingwu

    2017-11-20

    Traditional Chinese medicine (TCM) is an important part of China's medical system. Due to the prolonged low price of TCM procedures and the lack of an effective mechanism for dynamic price adjustment, the development of TCM has markedly lagged behind Western medicine. The World Health Organization (WHO) has emphasized the need to enhance the development of alternative and traditional medicine when creating national health care systems. The establishment of scientific and appropriate mechanisms to adjust the price of medical procedures in TCM is crucial to promoting the development of TCM. This study has examined incorporating value indicators and data on basic manpower expended, time spent, technical difficulty, and the degree of risk in the latest standards for the price of medical procedures in China, and this study also offers a price adjustment model with the relative price ratio as a key index. This study examined 144 TCM procedures and found that prices of TCM procedures were mainly based on the value of medical care provided; on average, medical care provided accounted for 89% of the price. Current price levels were generally low and the current price accounted for 56% of the standardized value of a procedure, on average. Current price levels accounted for a markedly lower standardized value of acupuncture, moxibustion, special treatment with TCM, and comprehensive TCM procedures. This study selected a total of 79 procedures and adjusted them by priority. The relationship between the price of TCM procedures and the suggested price was significantly optimized (p based on a standardized value parity model is a scientific and suitable method of price adjustment that can serve as a reference for other provinces and municipalities in China and other countries and regions that mainly have fee-for-service (FFS) medical care.

  8. 2007 Wholesale Power Rate Schedules : 2007 General Rate Schedule Provisions.

    Energy Technology Data Exchange (ETDEWEB)

    United States. Bonneville Power Administration.

    2006-11-01

    This schedule is available for the contract purchase of Firm Power to be used within the Pacific Northwest (PNW). Priority Firm (PF) Power may be purchased by public bodies, cooperatives, and Federal agencies for resale to ultimate consumers, for direct consumption, and for Construction, Test and Start-Up, and Station Service. Rates in this schedule are in effect beginning October 1, 2006, and apply to purchases under requirements Firm Power sales contracts for a three-year period. The Slice Product is only available for public bodies and cooperatives who have signed Slice contracts for the FY 2002-2011 period. Utilities participating in the Residential Exchange Program (REP) under Section 5(c) of the Northwest Power Act may purchase Priority Firm Power pursuant to the Residential Exchange Program. Rates under contracts that contain charges that escalate based on BPA's Priority Firm Power rates shall be based on the three-year rates listed in this rate schedule in addition to applicable transmission charges. This rate schedule supersedes the PF-02 rate schedule, which went into effect October 1, 2001. Sales under the PF-07 rate schedule are subject to BPA's 2007 General Rate Schedule Provisions (2007 GRSPs). Products available under this rate schedule are defined in the 2007 GRSPs. For sales under this rate schedule, bills shall be rendered and payments due pursuant to BPA's 2007 GRSPs and billing process.

  9. Research on information models for the construction schedule management based on the IFC standard

    Directory of Open Access Journals (Sweden)

    Weirui Xue

    2015-05-01

    Full Text Available Purpose: The purpose of this article is to study the description and extension of the Industry Foundation Classes (IFC standard in construction schedule management, which achieves the information exchange and sharing among the different information systems and stakeholders, and facilitates the collaborative construction in the construction projects. Design/methodology/approach: The schedule information processing and coordination are difficult in the complex construction project. Building Information Modeling (BIM provides the platform for exchanging and sharing information among information systems and stakeholders based on the IFC standard. Through analyzing the schedule plan, implementing, check and control, the information flow in the schedule management is reflected based on the IDEF. According to the IFC4, the information model for the schedule management is established, which not only includes the each aspect of the schedule management, but also includes the cost management, the resource management, the quality management and the risk management. Findings: The information requirement for the construction schedule management can be summarized into three aspects: the schedule plan information, the implementing information and the check and control information. The three aspects can be described through the existing and extended entities of IFC4, and the information models are established. Originality/value: The main contribution of the article is to establish the construction schedule management information model, which achieves the information exchange and share in the construction project, and facilitates the development of the application software to meet the requirements of the construction project.

  10. Modeling the relationship between the oil price and global food prices

    International Nuclear Information System (INIS)

    Chen, Sheng-Tung; Kuo, Hsiao-I; Chen, Chi-Chung

    2010-01-01

    The growth of corn-based ethanol production and soybean-based bio-diesel production following the increase in the oil prices have significantly affect the world agricultural grain productions and its prices. The main purpose of this paper is to investigate the relationships between the crude oil price and the global grain prices for corn, soybean, and wheat. The empirical results show that the change in each grain price is significantly influenced by the changes in the crude oil price and other grain prices during the period extending from the 3rd week in 2005 to the 20th week in 2008 which implies that grain commodities are competing with the derived demand for bio-fuels by using soybean or corn to produce ethanol or bio-diesel during the period of higher crude oil prices in these recent years. The subsidy policies in relation to the bio-fuel industries in some nations engaging in bio-fuel production should be considered to avoid the consequences resulting from high oil prices. (author)

  11. North American natural gas storage, market and price outlook

    International Nuclear Information System (INIS)

    George, R.

    1999-01-01

    A series of overhead viewgraphs accompanied this presentation which dealt with the fundamental factors and short-term considerations that will impact Canadian and U.S. natural gas pricing. The short-term pricing outlook and some transportation issues were also highlighted. The major transportation issues for 1999/2000 are: (1) Nova tolling, (2) incentive tolling and negotiations, (3) decontracting, (4) pipeline project schedules, and (5) land use and environmental considerations. The major supply issues are: (1) impact of oil prices on gas drilling and production, (2) impact of merger and acquisition activity, and (3) land use and environmental considerations. The major demand issues for the same time period are: (1) greenhouse gas emissions, (2) electricity restructuring, and (3) new end-use technologies. 3 tabs., 21 figs

  12. Reference-based pricing: an evidence-based solution for lab services shopping.

    Science.gov (United States)

    Melton, L Doug; Bradley, Kent; Fu, Patricia Lin; Armata, Raegan; Parr, James B

    2014-01-01

    To determine the effect of reference-based pricing (RBP) on the percentage of lab services utilized by members that were at or below the reference price. Retrospective, quasi-experimental, matched, case-control pilot evaluation of an RBP benefit for lab services. The study group included employees of a multinational grocery chain covered by a national health insurance carrier and subject to RBP for lab services; it had access to an online lab shopping tool and was informed about the RBP benefit through employer communications. The reference group was covered by the same insurance carrier but not subject to RBP. The primary end point was lab compliance, defined as the percentage of lab claims with total charges at or below the reference price. Difference-in-difference regression estimation evaluated changes in lab compliance between the 2 groups. Higher compliance per lab claim was evident for the study group compared with the reference group (69% vs 57%; Ponline shopping tool was used by 7% of the matched-adjusted study group prior to obtaining lab services. Lab compliance was 76% for study group members using the online tool compared with 68% among nonusers who were subject to RBP (P<.01). RBP can promote cost-conscious selection of lab services. Access to facilities that offer services below the reference price and education about RBP improve compliance. Evaluation of the effect of RBP on higher-cost medical services, including radiology, outpatient specialty, and elective inpatient procedures, is needed.

  13. A Scheduling Algorithm for Cloud Computing System Based on the Driver of Dynamic Essential Path.

    Science.gov (United States)

    Xie, Zhiqiang; Shao, Xia; Xin, Yu

    2016-01-01

    To solve the problem of task scheduling in the cloud computing system, this paper proposes a scheduling algorithm for cloud computing based on the driver of dynamic essential path (DDEP). This algorithm applies a predecessor-task layer priority strategy to solve the problem of constraint relations among task nodes. The strategy assigns different priority values to every task node based on the scheduling order of task node as affected by the constraint relations among task nodes, and the task node list is generated by the different priority value. To address the scheduling order problem in which task nodes have the same priority value, the dynamic essential long path strategy is proposed. This strategy computes the dynamic essential path of the pre-scheduling task nodes based on the actual computation cost and communication cost of task node in the scheduling process. The task node that has the longest dynamic essential path is scheduled first as the completion time of task graph is indirectly influenced by the finishing time of task nodes in the longest dynamic essential path. Finally, we demonstrate the proposed algorithm via simulation experiments using Matlab tools. The experimental results indicate that the proposed algorithm can effectively reduce the task Makespan in most cases and meet a high quality performance objective.

  14. Entropy-based financial asset pricing.

    Directory of Open Access Journals (Sweden)

    Mihály Ormos

    Full Text Available We investigate entropy as a financial risk measure. Entropy explains the equity premium of securities and portfolios in a simpler way and, at the same time, with higher explanatory power than the beta parameter of the capital asset pricing model. For asset pricing we define the continuous entropy as an alternative measure of risk. Our results show that entropy decreases in the function of the number of securities involved in a portfolio in a similar way to the standard deviation, and that efficient portfolios are situated on a hyperbola in the expected return-entropy system. For empirical investigation we use daily returns of 150 randomly selected securities for a period of 27 years. Our regression results show that entropy has a higher explanatory power for the expected return than the capital asset pricing model beta. Furthermore we show the time varying behavior of the beta along with entropy.

  15. Entropy-based financial asset pricing.

    Science.gov (United States)

    Ormos, Mihály; Zibriczky, Dávid

    2014-01-01

    We investigate entropy as a financial risk measure. Entropy explains the equity premium of securities and portfolios in a simpler way and, at the same time, with higher explanatory power than the beta parameter of the capital asset pricing model. For asset pricing we define the continuous entropy as an alternative measure of risk. Our results show that entropy decreases in the function of the number of securities involved in a portfolio in a similar way to the standard deviation, and that efficient portfolios are situated on a hyperbola in the expected return-entropy system. For empirical investigation we use daily returns of 150 randomly selected securities for a period of 27 years. Our regression results show that entropy has a higher explanatory power for the expected return than the capital asset pricing model beta. Furthermore we show the time varying behavior of the beta along with entropy.

  16. An Application-Level QoS Control Method Based on Local Bandwidth Scheduling

    Directory of Open Access Journals (Sweden)

    Yong Wang

    2018-01-01

    Full Text Available Quality of service (QoS is an important performance indicator for Web applications and bandwidth is a key factor affecting QoS. Current methods use network protocols or ports to schedule bandwidth, which require tedious manual configurations or modifications of the underlying network. Some applications use dynamic ports and the traditional port-based bandwidth control methods cannot deal with them. A new QoS control method based on local bandwidth scheduling is proposed, which can schedule bandwidth at application level in a user-transparent way and it does not require tedious manual configurations. Experimental results indicate that the new method can effectively improve the QoS for applications, and it can be easily integrated into current Web applications without the need to modify the underlying network.

  17. An efficient schedule based data aggregation using node mobility for wireless sensor network

    DEFF Research Database (Denmark)

    Dnyaneshwar, Mantri; Pawar, Pranav M.; Prasad, Neeli R.

    2014-01-01

    In the Wireless Sensor Networks, (WSNs) a key challenge is to schedule the activities of the mobile node for improvement in throughput, energy consumption and delay. This paper proposes efficient schedule based data aggregation algorithm using node mobility (SDNM). It considers the cluster...

  18. Ice Storage Air-Conditioning System Simulation with Dynamic Electricity Pricing: A Demand Response Study

    Directory of Open Access Journals (Sweden)

    Chi-Chun Lo

    2016-02-01

    Full Text Available This paper presents an optimal dispatch model of an ice storage air-conditioning system for participants to quickly and accurately perform energy saving and demand response, and to avoid the over contact with electricity price peak. The schedule planning for an ice storage air-conditioning system of demand response is mainly to transfer energy consumption from the peak load to the partial-peak or off-peak load. Least Squares Regression (LSR is used to obtain the polynomial function for the cooling capacity and the cost of power consumption with a real ice storage air-conditioning system. Based on the dynamic electricity pricing, the requirements of cooling loads, and all technical constraints, the dispatch model of the ice-storage air-conditioning system is formulated to minimize the operation cost. The Improved Ripple Bee Swarm Optimization (IRBSO algorithm is proposed to solve the dispatch model of the ice storage air-conditioning system in a daily schedule on summer. Simulation results indicate that reasonable solutions provide a practical and flexible framework allowing the demand response of ice storage air-conditioning systems to demonstrate the optimization of its energy savings and operational efficiency and offering greater energy efficiency.

  19. Distributed, price-based control approach to market-based operation of future power systems

    NARCIS (Netherlands)

    Jokic, A.; Bosch, van den P.P.J.; Hermans, R.M.

    2009-01-01

    In this paper we present, discuss and illustrate on examples the price-based control paradigm as a suitable approach to solve some of the challenging problems facing future, market-based power systems. It is illustrated how global objectives and constraints are optimally translated into time-varying

  20. Metaheuristic Based Scheduling Meta-Tasks in Distributed Heterogeneous Computing Systems

    Directory of Open Access Journals (Sweden)

    Hesam Izakian

    2009-07-01

    Full Text Available Scheduling is a key problem in distributed heterogeneous computing systems in order to benefit from the large computing capacity of such systems and is an NP-complete problem. In this paper, we present a metaheuristic technique, namely the Particle Swarm Optimization (PSO algorithm, for this problem. PSO is a population-based search algorithm based on the simulation of the social behavior of bird flocking and fish schooling. Particles fly in problem search space to find optimal or near-optimal solutions. The scheduler aims at minimizing makespan, which is the time when finishes the latest task. Experimental studies show that the proposed method is more efficient and surpasses those of reported PSO and GA approaches for this problem.

  1. TTSA: An Effective Scheduling Approach for Delay Bounded Tasks in Hybrid Clouds.

    Science.gov (United States)

    Yuan, Haitao; Bi, Jing; Tan, Wei; Zhou, MengChu; Li, Bo Hu; Li, Jianqiang

    2017-11-01

    The economy of scale provided by cloud attracts a growing number of organizations and industrial companies to deploy their applications in cloud data centers (CDCs) and to provide services to users around the world. The uncertainty of arriving tasks makes it a big challenge for private CDC to cost-effectively schedule delay bounded tasks without exceeding their delay bounds. Unlike previous studies, this paper takes into account the cost minimization problem for private CDC in hybrid clouds, where the energy price of private CDC and execution price of public clouds both show the temporal diversity. Then, this paper proposes a temporal task scheduling algorithm (TTSA) to effectively dispatch all arriving tasks to private CDC and public clouds. In each iteration of TTSA, the cost minimization problem is modeled as a mixed integer linear program and solved by a hybrid simulated-annealing particle-swarm-optimization. The experimental results demonstrate that compared with the existing methods, the optimal or suboptimal scheduling strategy produced by TTSA can efficiently increase the throughput and reduce the cost of private CDC while meeting the delay bounds of all the tasks.

  2. The effects of the vegetable prices insurance on the fluctuation of price: Based on Shanghai evidences

    Science.gov (United States)

    Qu, Chunhong; Li, Huishang; Hao, Shuai; Zhang, Xuebiao; Yang, Wei

    2017-10-01

    Taking Shanghai as an example, the influence of the vegetable price insurance on the fluctuation of prices was analyzed in the article. It was found that the sequence of seasonal fluctuations characteristics of leafy vegetable prices was changed by the vegetable cost-price insurance, the period of price fluctuation was elongated from 12-to-18 months to 37 months, and the influence of random factors on the price fluctuations was reduced in some degree. There was still great space for innovation of the vegetable prices insurance system in Shanghai. Some countermeasures would be suggested to develop the insurance system to better to play the role of insurance and promote the market running more smoothly in Shanghai such as prolonging the insurance cycle, improving the price information monitoring mechanism and innovating income insurance products and so on.

  3. Two pricing methods for solving an integrated commercial fishery ...

    African Journals Online (AJOL)

    In this paper, we develop two novel pricing methods for solving an integer program. We demonstrate the methods by solving an integrated commercial fishery planning model (IFPM). In this problem, a fishery manager must schedule fishing trawlers (determine when and where the trawlers should go fishing, and when the ...

  4. Project Robust Scheduling Based on the Scattered Buffer Technology

    Directory of Open Access Journals (Sweden)

    Nansheng Pang

    2018-04-01

    Full Text Available The research object in this paper is the sub network formed by the predecessor’s affect on the solution activity. This paper is to study three types of influencing factors from the predecessors that lead to the delay of starting time of the solution activity on the longest path, and to analyze the influence degree on the delay of the solution activity’s starting time from different types of factors. On this basis, through the comprehensive analysis of various factors that influence the solution activity, this paper proposes a metric that is used to evaluate the solution robustness of the project scheduling, and this metric is taken as the optimization goal. This paper also adopts the iterative process to design a scattered buffer heuristics algorithm based on the robust scheduling of the time buffer. At the same time, the resource flow network is introduced in this algorithm, using the tabu search algorithm to solve baseline scheduling. For the generation of resource flow network in the baseline scheduling, this algorithm designs a resource allocation algorithm with the maximum use of the precedence relations. Finally, the algorithm proposed in this paper and some other algorithms in previous literature are taken into the simulation experiment; under the comparative analysis, the experimental results show that the algorithm proposed in this paper is reasonable and feasible.

  5. Adaptive Cost-Based Task Scheduling in Cloud Environment

    Directory of Open Access Journals (Sweden)

    Mohammed A. S. Mosleh

    2016-01-01

    Full Text Available Task execution in cloud computing requires obtaining stored data from remote data centers. Though this storage process reduces the memory constraints of the user’s computer, the time deadline is a serious concern. In this paper, Adaptive Cost-based Task Scheduling (ACTS is proposed to provide data access to the virtual machines (VMs within the deadline without increasing the cost. ACTS considers the data access completion time for selecting the cost effective path to access the data. To allocate data access paths, the data access completion time is computed by considering the mean and variance of the network service time and the arrival rate of network input/output requests. Then the task priority is assigned to the removed tasks based data access time. Finally, the cost of data paths are analyzed and allocated based on the task priority. Minimum cost path is allocated to the low priority tasks and fast access path are allocated to high priority tasks as to meet the time deadline. Thus efficient task scheduling can be achieved by using ACTS. The experimental results conducted in terms of execution time, computation cost, communication cost, bandwidth, and CPU utilization prove that the proposed algorithm provides better performance than the state-of-the-art methods.

  6. The development of a value based pricing index for new drugs in metastatic colorectal cancer

    OpenAIRE

    Lubbe, Martha Susanna; Dranitsaris, George; Truter, Ilse

    2011-01-01

    Background Worldwide, prices for cancer drugs have been under downward pressure where several governments have mandated price cuts of branded products. A better alternative to government mandated price cuts would be to estimate a final price based on drug performance, cost effectiveness and a country’s ability to pay. We developed a global pricing index for new cancer drugs in patients with metastatic colorectal cancer (mCRC) that encompasses all of these attributes. Methods ...

  7. Value-based pricing: A success factor in the competitive struggle

    OpenAIRE

    Netseva-Porcheva Tatyana

    2011-01-01

    Over the past decade, the view that the main purpose of market oriented organizations is not to satisfy the consumer, but to create values has dominated. Exactly the values, their creation, retention and increase, are the main sources of competitive advantage of the company. The purpose of the present report is to present the price formation, based on product value, as a source of competitive advantage. In connection with the so-defined objective, the value and the product price for the custo...

  8. A tree-based method to price American options in the Heston model

    NARCIS (Netherlands)

    Vellekoop, M.; Nieuwenhuis, H.

    2009-01-01

    We develop an algorithm to price American options on assets that follow the stochastic volatility model defined by Heston. We use an approach which is based on a modification of a combined tree for stock prices and volatilities, where the number of nodes grows quadratically in the number of time

  9. Influence of the Emissions Trading Scheme on generation scheduling

    International Nuclear Information System (INIS)

    Kockar, Ivana; McDonald, James R.; Conejo, Antonio J.

    2009-01-01

    The paper investigates the effects of emissions constraints and Emissions Trading Scheme (ETS) on the generation scheduling outcome. ETS is a cap-and-trade market mechanism that has been introduced in European Union in order to facilitate CO 2 emissions management. This scheme gives generators certain amount of CO 2 allowances which they can use to cover emissions produced during energy generation. In a current setting, most of the allowances are given for free. However, under ETS generators also have an opportunity to buy and sell CO 2 allowances on the market. Since generation power outputs are bounded by the amount of CO 2 emissions that they are allowed to produce over time, it is becoming increasingly important for generating units to manage their allocations in the most profitable way and decide when and how much of permissions to spent to produce electricity. The method proposed here allows for modeling of this new limitation by including costs of buying and selling of CO 2 allowance in the generation scheduling procedure. It also introduces additional emissions constraints in the problem formulation. Although CO 2 permissions and energy are traded in separate markets, the proposed formulation permits analysis on how emission caps and emission market prices can influence market outcome. The method is illustrated on a 5-unit system. Given examples compare (i) a base-case when all generators have made a decision to use portions of their total free allocations that do not cause any shortfall during the investigated time period; (ii) two cases when the least expensive generators' decisions on the amount of free allowances they are willing to use during the considered period are insufficient. In all cases generators also submit prices at which they expect to be able to ''top-up'' or sell allowances on the market, however, only in the second and third case the ''buying'' option becomes active and affects generation scheduling and total costs. In addition, the

  10. A price based automatic generation control using unscheduled ...

    African Journals Online (AJOL)

    In this paper, a model for price based automatic generation control is presented. A modified control scheme is proposed which will prevent unintended unscheduled interchanges among the participants. The proposed scheme is verified by simulating it on a model of isolated area system having four generators. It has been ...

  11. The study of the price of gold futures based on heterogeneous investors' overconfidence

    Institute of Scientific and Technical Information of China (English)

    Wei Jiang; Pupu Luan; Chunpeng Yang

    2014-01-01

    Purpose-The purpose of this paper is to research and analyze the price of gold futures based on heterogeneous investors' overconfidence.Design/methodology/approach-This paper divides the traders of gold futures market into two kinds:the speculators and arbitrageurs,and then constructs a market equilibrium model of futures pricing to analyze the behaviors of the two kinds of traders with overconfidence.After getting the decision-making function,the market equilibrium futures price is attained on the condition of market clearing.Then,this paper analyzes how the overconfidence impacts on futures price,volatility of the price of gold futures and the effects on individual utility.Findings-Under different market conditions,the overconfidence psychological impacts of heterogeneous investor on the price and volatility of futures are different,sometimes completely opposite.Originality/value-In the past literature,the relationships between overconfidence and the price or volatility are positive;however,the study shows that sometimes it is positive,and sometimes it is negative

  12. What is a new drug worth? An innovative model for performance-based pricing.

    Science.gov (United States)

    Dranitsaris, G; Dorward, K; Owens, R C; Schipper, H

    2015-05-01

    This article focuses on a novel method to derive prices for new pharmaceuticals by making price a function of drug performance. We briefly review current models for determining price for a new product and discuss alternatives that have historically been favoured by various funding bodies. The progressive approach to drug pricing, proposed herein, may better address the views and concerns of multiple stakeholders in a developed healthcare system by acknowledging and incorporating input from disparate parties via comprehensive and successive negotiation stages. In proposing a valid construct for performance-based pricing, the following model seeks to achieve several crucial objectives: earlier and wider access to new treatments; improved transparency in drug pricing; multi-stakeholder involvement through phased pricing negotiations; recognition of innovative product performance and latent changes in value; an earlier and more predictable return for developers without sacrificing total return on investment (ROI); more involved and informed risk sharing by the end-user. © 2014 John Wiley & Sons Ltd.

  13. Schedules of Controlled Substances: Temporary Placement of 4-Fluoroisobutyryl Fentanyl into Schedule I. Temporary scheduling order.

    Science.gov (United States)

    2017-05-03

    The Administrator of the Drug Enforcement Administration is issuing this temporary scheduling order to schedule the synthetic opioid, N-(4-fluorophenyl)-N-(1-phenethylpiperidin-4-yl)isobutyramide (4-fluoroisobutyryl fentanyl or para-fluoroisobutyryl fentanyl), and its isomers, esters, ethers, salts and salts of isomers, esters, and ethers, into schedule I pursuant to the temporary scheduling provisions of the Controlled Substances Act. This action is based on a finding by the Administrator that the placement of 4-fluoroisobutyryl fentanyl into schedule I of the Controlled Substances Act is necessary to avoid an imminent hazard to the public safety. As a result of this order, the regulatory controls and administrative, civil, and criminal sanctions applicable to schedule I controlled substances will be imposed on persons who handle (manufacture, distribute, reverse distribute, import, export, engage in research, conduct instructional activities or chemical analysis, or possess), or propose to handle, 4-fluoroisobutyryl fentanyl.

  14. Efficient operation scheduling for adsorption chillers using predictive optimization-based control methods

    Science.gov (United States)

    Bürger, Adrian; Sawant, Parantapa; Bohlayer, Markus; Altmann-Dieses, Angelika; Braun, Marco; Diehl, Moritz

    2017-10-01

    Within this work, the benefits of using predictive control methods for the operation of Adsorption Cooling Machines (ACMs) are shown on a simulation study. Since the internal control decisions of series-manufactured ACMs often cannot be influenced, the work focuses on optimized scheduling of an ACM considering its internal functioning as well as forecasts for load and driving energy occurrence. For illustration, an assumed solar thermal climate system is introduced and a system model suitable for use within gradient-based optimization methods is developed. The results of a system simulation using a conventional scheme for ACM scheduling are compared to the results of a predictive, optimization-based scheduling approach for the same exemplary scenario of load and driving energy occurrence. The benefits of the latter approach are shown and future actions for application of these methods for system control are addressed.

  15. Pricing of brand extensions based on perceptions of brand equity

    Directory of Open Access Journals (Sweden)

    Panagiotis Arsenos

    2018-04-01

    Full Text Available The paper explores the role of brand equity when pricing hypothetical brand extensions. Companies tend to use different pricing techniques for their products, and their pricing decisions are based on many factors, including image and category fit of the product with the existing image and products of the company. Brand extensions are usually investigated from a consumer perspective, focusing on the extension attitude, however, it is essential to understand the corporate decision-making process regarding pricing. Exploring this matter using quantitative research methods, the study provides empirical evidence that companies that have invested heavily in marketing actions in the past and have built strong brand equity over-time, show flexibility in the mark-up during the cost decision-making process of a hypothetical brand extensions. Variations in mark-up percentages are also observed when there is a difference in image and category fit of the extension to the original brand. However, companies characterized by greater brand equity exhibited greater flexibility in the mark-up percentages, even for low fit extensions.

  16. Gain Scheduling of Observer-Based Controllers with Integral Action

    DEFF Research Database (Denmark)

    Trangbæk, Klaus; Stoustrup, Jakob; Bendtsen, Jan Dimon

    2006-01-01

     This paper presents a method for continuous gain scheduling of  observer-based controllers with integral action. Given two stabilising controllers for a given system, explicit state space formulae are presented, allowing to change gradually from one  controller to the other while preserving...

  17. The development of a value based pricing index for new drugs in metastatic colorectal cancer.

    Science.gov (United States)

    Dranitsaris, George; Truter, Ilse; Lubbe, Martie S

    2011-06-01

    Worldwide, prices for cancer drugs have been under downward pressure where several governments have mandated price cuts of branded products. A better alternative to government mandated price cuts would be to estimate a final price based on drug performance, cost effectiveness and a country's ability to pay. We developed a global pricing index for new cancer drugs in patients with metastatic colorectal cancer (mCRC) that encompasses all of these attributes. A pharmacoeconomic model was developed to simulate mCRC patients receiving chemotherapy plus a 'new drug' that improves survival by 1.4, 3 and 6months, respectively. Cost and utility data were obtained from cancer centres and oncology nurses (n=112) in Canada, Spain, India, South Africa and Malaysia. Multivariable analysis was then used to develop the pricing index, which considers survival benefit, per capita GDP and income dispersion (as measured by the Gini coefficient) as predictor variables. Higher survival benefits were associated with elevated drug prices, especially in higher income countries such as Canada. For Argentina with a per capita GDP of $15,000 and a Gini coefficient of 51, the index estimated that for a drug which provides a 4month survival benefit in mCRC, the value based price would be $US 630 per dose. In contrast, the same drug in a wealthier country like Norway (per capita GDP=$50,000) could command a price of $US 2,775 per dose. The application of this index to estimate a price based on cost effectiveness and the wealth of a nation would be important for opening dialogue between the key stakeholders and a better alternative to government mandated price cuts. Copyright © 2011 Elsevier Ltd. All rights reserved.

  18. Combined Noncyclic Scheduling and Advanced Control for Continuous Chemical Processes

    Directory of Open Access Journals (Sweden)

    Damon Petersen

    2017-12-01

    Full Text Available A novel formulation for combined scheduling and control of multi-product, continuous chemical processes is introduced in which nonlinear model predictive control (NMPC and noncyclic continuous-time scheduling are efficiently combined. A decomposition into nonlinear programming (NLP dynamic optimization problems and mixed-integer linear programming (MILP problems, without iterative alternation, allows for computationally light solution. An iterative method is introduced to determine the number of production slots for a noncyclic schedule during a prediction horizon. A filter method is introduced to reduce the number of MILP problems required. The formulation’s closed-loop performance with both process disturbances and updated market conditions is demonstrated through multiple scenarios on a benchmark continuously stirred tank reactor (CSTR application with fluctuations in market demand and price for multiple products. Economic performance surpasses cyclic scheduling in all scenarios presented. Computational performance is sufficiently light to enable online operation in a dual-loop feedback structure.

  19. Improving the asset pricing ability of the Consumption-Capital Asset Pricing Model?

    DEFF Research Database (Denmark)

    Rasmussen, Anne-Sofie Reng

    This paper compares the asset pricing ability of the traditional consumption-based capital asset pricing model to models from two strands of literature attempting to improve on the poor empirical results of the C-CAPM. One strand is based on the intertemporal asset pricing model of Campbell (1993...... able to price assets conditionally as suggested by Cochrane (1996) and Lettau and Ludvigson (2001b). The unconditional C-CAPM is rewritten as a scaled factor model using the approximate log consumptionwealth ratio cay, developed by Lettau and Ludvigson (2001a), as scaling variable. The models...... and composite. Thus, there is no unambiguous solution to the pricing ability problems of the C-CAPM. Models from both the alternative literature strands are found to outperform the traditional C-CAPM on average pricing errors. However, when weighting pricing errors by the full variance-covariance matrix...

  20. A preliminary analysis of the reactor-based plutonium disposition alternative deployment schedules

    International Nuclear Information System (INIS)

    Zurn, R.M.

    1997-09-01

    This paper discusses the preliminary analysis of the implementation schedules of the reactor-based plutonium disposition alternatives. These schedule analyses are a part of a larger process to examine the nine decision criteria used to determine the most appropriate method of disposing of U.S. surplus weapons plutonium. The preliminary analysis indicates that the mission durations for the reactor-based alternatives range from eleven years to eighteen years and the initial mission fuel assemblies containing surplus weapons-usable plutonium could be loaded into the reactors between nine and fourteen years after the Record of Decision

  1. A Dynamic Pricing Reverse Auction-Based Resource Allocation Mechanism in Cloud Workflow Systems

    Directory of Open Access Journals (Sweden)

    Xuejun Li

    2016-01-01

    Full Text Available Market-oriented reverse auction is an efficient and cost-effective method for resource allocation in cloud workflow systems since it can dynamically allocate resources depending on the supply-demand relationship of the cloud market. However, during the auction the price of cloud resource is usually fixed, and the current resource allocation mechanisms cannot adapt to the changeable market properly which results in the low efficiency of resource utilization. To address such a problem, a dynamic pricing reverse auction-based resource allocation mechanism is proposed. During the auction, resource providers can change prices according to the trading situation so that our novel mechanism can increase the chances of making a deal and improve efficiency of resource utilization. In addition, resource providers can improve their competitiveness in the market by lowering prices, and thus users can obtain cheaper resources in shorter time which would decrease monetary cost and completion time for workflow execution. Experiments with different situations and problem sizes are conducted for dynamic pricing-based allocation mechanism (DPAM on resource utilization and the measurement of Time⁎Cost (TC. The results show that our DPAM can outperform its representative in resource utilization, monetary cost, and completion time and also obtain the optimal price reduction rates.

  2. THE IMPLEMENTATION OF ACTIVITY-BASED COSTING METHOD IN DETERMINING SELLING PRICES

    Directory of Open Access Journals (Sweden)

    Muhtarudin Muhtarudin

    2017-08-01

    Costing method. After applying the latter cost determining the method there turned out to be a significant difference in the shoe production cost resulted from the inaccurate price calculation in the former method, as here a selling price is fixed by marking-up efforts aiming to cover the production cost. Determining a selling price in this way causes the selling price to be too low; thus it cannot optimize the profit. Keywords: Activity-Based Costing; Production Cost; Selling Price

  3. Hydrothermal self-scheduling problem in a day-ahead electricity market

    International Nuclear Information System (INIS)

    Bisanovic, Smajo; Dlakic, Muris; Hajro, Mensur

    2008-01-01

    This paper addresses the self-scheduling problem of determining the unit commitment status for power generation companies before submitting the hourly bids in a day-ahead market. The hydrothermal model is formulated as a deterministic optimization problem where expected profit is maximized using the 0/1 mixed-integer linear programming technique. This approach allows precise modelling of non-convex variable cost functions and non-linear start-up cost functions of thermal units, non-concave power-discharge characteristics of hydro units, ramp rate limits of thermal units and minimum up and down time constraints for both hydro and thermal units. Model incorporates long-term bilateral contracts with contracted power and price patterns, as well as forecasted market hourly prices for day-ahead auction. Solution is achieved using the homogeneous interior point method for linear programming as state of the art technique, with a branch and bound optimizer for integer programming. The effectiveness of the proposed model in optimizing the generation schedule is demonstrated through the case studies and their analysis. (author)

  4. Applying the behavioral economics principle of unit price to DRO schedule thinning.

    Science.gov (United States)

    Roane, Henry S; Falcomata, Terry S; Fisher, Wayne W

    2007-01-01

    Within the context of behavioral economics, the ratio of response requirements to reinforcer magnitude is called unit price. In this investigation, we yoked increases in reinforcer magnitude with increases in intervals of differential reinforcement of other behavior (DRO) to thin DRO intervals to a terminal value.

  5. Rate adaptation in ad hoc networks based on pricing

    CSIR Research Space (South Africa)

    Awuor, F

    2011-09-01

    Full Text Available that incorporates penalty (pricing) obtruded to users’ choices of transmission parameters to curb the self-interest behaviour. Therefore users determine their data rates and transmit power based on the perceived coupled interference at the intended receiver...

  6. When to "Fire" Customers: Customer Cost-Based Pricing

    OpenAIRE

    Jiwoong Shin; K. Sudhir; Dae-Hee Yoon

    2012-01-01

    The widespread adoption of activity-based costing enables firms to allocate common service costs to each customer, allowing for precise measurement of both the cost to serve a particular customer and the customer's profitability. In this paper, we investigate how pricing strategies based on customer cost information affects a firm's customer acquisition and retention dynamics, and ultimately its profit, using a two-period monopoly model with high- and low-cost customer segments. Although past...

  7. Weight-based pricing in the collection of household waste. The Oostzaan case

    International Nuclear Information System (INIS)

    Linderhof, Vincent; Kooreman, Peter; Allers, Maarten; Wiersma, Doede

    2001-01-01

    This paper provides an empirical analysis of the effects of weight-based pricing in the collection of household waste. Using a comprehensive panel data set on all households in a Dutch municipality we estimate short-run as well as long-run price effects for the amounts of both compostable and non-recyclable household waste. We find significant and sizeable price effects, with the elasticity for compostable waste being four times as large as the elasticity for non-recyclable waste. Long-run elasticities are about 30% larger than short-run elasticities

  8. Pricing hospital care: Global budgets and marginal pricing strategies.

    Science.gov (United States)

    Sutherland, Jason M

    2015-08-01

    The Canadian province of British Columbia (BC) is adding financial incentives to increase the volume of surgeries provided by hospitals using a marginal pricing approach. The objective of this study is to calculate marginal costs of surgeries based on assumptions regarding hospitals' availability of labor and equipment. This study is based on observational clinical, administrative and financial data generated by hospitals. Hospital inpatient and outpatient discharge summaries from the province are linked with detailed activity-based costing information, stratified by assigned case mix categorizations. To reflect a range of operating constraints governing hospitals' ability to increase their volume of surgeries, a number of scenarios are proposed. Under these scenarios, estimated marginal costs are calculated and compared to prices being offered as incentives to hospitals. Existing data can be used to support alternative strategies for pricing hospital care. Prices for inpatient surgeries do not generate positive margins under a range of operating scenarios. Hip and knee surgeries generate surpluses for hospitals even under the most costly labor conditions and are expected to generate additional volume. In health systems that wish to fine-tune financial incentives, setting prices that create incentives for additional volume should reflect knowledge of hospitals' underlying cost structures. Possible implications of mis-pricing include no response to the incentives or uneven increases in supply. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  9. Research on logistics scheduling based on PSO

    Science.gov (United States)

    Bao, Huifang; Zhou, Linli; Liu, Lei

    2017-08-01

    With the rapid development of e-commerce based on the network, the logistics distribution support of e-commerce is becoming more and more obvious. The optimization of vehicle distribution routing can improve the economic benefit and realize the scientific of logistics [1]. Therefore, the study of logistics distribution vehicle routing optimization problem is not only of great theoretical significance, but also of considerable value of value. Particle swarm optimization algorithm is a kind of evolutionary algorithm, which is based on the random solution and the optimal solution by iteration, and the quality of the solution is evaluated through fitness. In order to obtain a more ideal logistics scheduling scheme, this paper proposes a logistics model based on particle swarm optimization algorithm.

  10. Designing of vague logic based multilevel feedback queue scheduler

    Directory of Open Access Journals (Sweden)

    Supriya Raheja

    2016-03-01

    Full Text Available Multilevel feedback queue scheduler suffers from major issues of scheduling such as starvation for long tasks, fixed number of queues, and static length of time quantum in each queue. These factors directly affect the performance of the scheduler. At many times impreciseness exists in attributes of tasks which make the performance even worse. In this paper, our intent is to improve the performance by providing a solution to these issues. We design a multilevel feedback queue scheduler using a vague set which we call as VMLFQ scheduler. VMLFQ scheduler intelligently handles the impreciseness and defines the optimum number of queues as well as the optimal size of time quantum for each queue. It also resolves the problem of starvation. This paper simulates and analyzes the performance of VMLFQ scheduler with the other multilevel feedback queue techniques using MatLab.

  11. Applying the Behavioral Economics Principle of Unit Price to DRO Schedule Thinning

    Science.gov (United States)

    Roane, Henry S.; Falcomata, Terry S.; Fisher, Wayne W.

    2007-01-01

    Within the context of behavioral economics, the ratio of response requirements to reinforcer magnitude is called "unit price." In this investigation, we yoked increases in reinforcer magnitude with increases in intervals of differential reinforcement of other behavior (DRO) to thin DRO intervals to a terminal value. (Contains 1 figure.)

  12. New plant construction cost and schedule

    International Nuclear Information System (INIS)

    Akins, M. J.

    2009-01-01

    The presentation covers the following topics: cost structure; capital costs; variation of capital costs; trends in power plant construction; studies of costs completion; periods and risks. Nuclear plant costs have recently risen so rapidly that vendors are not willing to publicly commit to cost estimates: ∼ $2000/Kw overnight costs in 2006 in the US market > $4000/Kw and in 2008 in the US market > $6000/Kw in 2008 in emerging markets. There is vendors pricing uncertainty. Current contract models may not apply. Current construction projects have problems: Olkiluoto-3 is reported to be 50% over budget and two years behind schedule, increasing perceptions that nuclear costs will continue to increase rapidly; Price of materials is a big volatile unknown, which may decrease Labor could become more available due to limited number of new projects; Lack of debt/credit to finance new project may decrease demand of new construction

  13. The price facade: Symbolic and behavioural price cues in service environments

    NARCIS (Netherlands)

    Verhoeven, J.W.M.; van Rompay, Thomas Johannes Lucas; Pruyn, Adriaan T.H.

    2009-01-01

    Although the role of price expectations in predicting consumer behavior has been widely acknowledged, little is known about the way in which price expectations depend on environmental elements in hospitality settings. We propose that restaurant guests base price expectations on (1) perceptions of

  14. Equilibrium prices supported by dual price functions in markets with non-convexities

    International Nuclear Information System (INIS)

    Bjoerndal, Mette; Joernsten, Kurt

    2004-06-01

    The issue of finding market clearing prices in markets with non-convexities has had a renewed interest due to the deregulation of the electricity sector. In the day-ahead electricity market, equilibrium prices are calculated based on bids from generators and consumers. In most of the existing markets, several generation technologies are present, some of which have considerable non-convexities, such as capacity limitations and large start up costs. In this paper we present equilibrium prices composed of a commodity price and an uplift charge. The prices are based on the generation of a separating valid inequality that supports the optimal resource allocation. In the case when the sub-problem generated as the integer variables are held fixed to their optimal values possess the integrality property, the generated prices are also supported by non-linear price-functions that are the basis for integer programming duality. (Author)

  15. Derivative pricing based on local utility maximization

    OpenAIRE

    Jan Kallsen

    2002-01-01

    This paper discusses a new approach to contingent claim valuation in general incomplete market models. We determine the neutral derivative price which occurs if investors maximize their local utility and if derivative demand and supply are balanced. We also introduce the sensitivity process of a contingent claim. This process quantifies the reliability of the neutral derivative price and it can be used to construct price bounds. Moreover, it allows to calibrate market models in order to be co...

  16. Multisensors Cooperative Detection Task Scheduling Algorithm Based on Hybrid Task Decomposition and MBPSO

    Directory of Open Access Journals (Sweden)

    Changyun Liu

    2017-01-01

    Full Text Available A multisensor scheduling algorithm based on the hybrid task decomposition and modified binary particle swarm optimization (MBPSO is proposed. Firstly, aiming at the complex relationship between sensor resources and tasks, a hybrid task decomposition method is presented, and the resource scheduling problem is decomposed into subtasks; then the sensor resource scheduling problem is changed into the match problem of sensors and subtasks. Secondly, the resource match optimization model based on the sensor resources and tasks is established, which considers several factors, such as the target priority, detecting benefit, handover times, and resource load. Finally, MBPSO algorithm is proposed to solve the match optimization model effectively, which is based on the improved updating means of particle’s velocity and position through the doubt factor and modified Sigmoid function. The experimental results show that the proposed algorithm is better in terms of convergence velocity, searching capability, solution accuracy, and efficiency.

  17. Auction development for the price-based electric power industry

    Science.gov (United States)

    Dekrajangpetch, Somgiat

    The restructuring of the electric power industry is to move away from the cost-based monopolistic environment of the past to the priced-based competitive environment. As the electric power industry is restructuring in many places, there are still many problems that need to be solved. The work in this dissertation contributes to solve some of the electric power auction problems. The majority of this work is aimed to help develop good markets. A LaGrangian relaxation (LR) Centralized Daily Commitment Auction (CDCA) has been implemented. It has been shown that the solution might not be optimal nor fair to some generation companies (GENCOs) when identical or similar generating units participate in a LR CDCA based auction. Supporting information for bidding strategies on how to change unit data to enhance the chances of bid acceptance has been developed. The majority of this work is based on Single Period Commodity Auction (SPCA). Alternative structures for the SPCA are outlined. Whether the optimal solution is degenerated is investigated. Good pricing criteria are summarized and the pricing method following good pricing criteria is developed. Electricity is generally considered as a homogeneous product. When availability level is used as additional characteristic to distinct electricity, electricity can be considered a heterogeneous product. The procedure to trade electricity as a heterogeneous product is developed. The SPCA is formulated as a linear program. The basic IPLP algorithm has been extended so that sensitivity analysis can be performed as in the simplex method. Sensitivity analysis is used to determine market reach. Additionally, sensitivity analysis is used in combination with the investigation of historical auction results to provide raw data for power system expansion. Market power is a critical issue in electric power deregulation. Firms with market power have an advantage over other competitor firms in terms of market reach. Various approaches to

  18. Simulation-Based Dynamic Passenger Flow Assignment Modelling for a Schedule-Based Transit Network

    Directory of Open Access Journals (Sweden)

    Xiangming Yao

    2017-01-01

    Full Text Available The online operation management and the offline policy evaluation in complex transit networks require an effective dynamic traffic assignment (DTA method that can capture the temporal-spatial nature of traffic flows. The objective of this work is to propose a simulation-based dynamic passenger assignment framework and models for such applications in the context of schedule-based rail transit systems. In the simulation framework, travellers are regarded as individual agents who are able to obtain complete information on the current traffic conditions. A combined route selection model integrated with pretrip route selection and entrip route switch is established for achieving the dynamic network flow equilibrium status. The train agent is operated strictly with the timetable and its capacity limitation is considered. A continuous time-driven simulator based on the proposed framework and models is developed, whose performance is illustrated through a large-scale network of Beijing subway. The results indicate that more than 0.8 million individual passengers and thousands of trains can be simulated simultaneously at a speed ten times faster than real time. This study provides an efficient approach to analyze the dynamic demand-supply relationship for large schedule-based transit networks.

  19. Cultural-Based Genetic Tabu Algorithm for Multiobjective Job Shop Scheduling

    Directory of Open Access Journals (Sweden)

    Yuzhen Yang

    2014-01-01

    Full Text Available The job shop scheduling problem, which has been dealt with by various traditional optimization methods over the decades, has proved to be an NP-hard problem and difficult in solving, especially in the multiobjective field. In this paper, we have proposed a novel quadspace cultural genetic tabu algorithm (QSCGTA to solve such problem. This algorithm provides a different structure from the original cultural algorithm in containing double brief spaces and population spaces. These spaces deal with different levels of populations globally and locally by applying genetic and tabu searches separately and exchange information regularly to make the process more effective towards promising areas, along with modified multiobjective domination and transform functions. Moreover, we have presented a bidirectional shifting for the decoding process of job shop scheduling. The computational results we presented significantly prove the effectiveness and efficiency of the cultural-based genetic tabu algorithm for the multiobjective job shop scheduling problem.

  20. Information Flow Scheduling in Concurrent Multi-Product Development Based on DSM

    Science.gov (United States)

    Sun, Qing-Chao; Huang, Wei-Qiang; Jiang, Ying-Jie; Sun, Wei

    2017-09-01

    Multi-product collaborative development is adopted widely in manufacturing enterprise, while the present multi-project planning models don't take technical/data interactions of multiple products into account. To decrease the influence of technical/data interactions on project progresses, the information flow scheduling models based on the extended DSM is presented. Firstly, information dependencies are divided into four types: series, parallel, coupling and similar. Secondly, different types of dependencies are expressed as DSM units, and the extended DSM model is brought forward, described as a block matrix. Furthermore, the information flow scheduling methods is proposed, which involves four types of operations, where partitioning and clustering algorithm are modified from DSM for ensuring progress of high-priority project, merging and converting is the specific computation of the extended DSM. Finally, the information flow scheduling of two machine tools development is analyzed with example, and different project priorities correspond to different task sequences and total coordination cost. The proposed methodology provides a detailed instruction for information flow scheduling in multi-product development, with specially concerning technical/data interactions.

  1. Proportional fair scheduling algorithm based on traffic in satellite communication system

    Science.gov (United States)

    Pan, Cheng-Sheng; Sui, Shi-Long; Liu, Chun-ling; Shi, Yu-Xin

    2018-02-01

    In the satellite communication network system, in order to solve the problem of low system capacity and user fairness in multi-user access to satellite communication network in the downlink, combined with the characteristics of user data service, an algorithm study on throughput capacity and user fairness scheduling is proposed - Proportional Fairness Algorithm Based on Traffic(B-PF). The algorithm is improved on the basis of the proportional fairness algorithm in the wireless communication system, taking into account the user channel condition and caching traffic information. The user outgoing traffic is considered as the adjustment factor of the scheduling priority and presents the concept of traffic satisfaction. Firstly,the algorithm calculates the priority of the user according to the scheduling algorithm and dispatches the users with the highest priority. Secondly, when a scheduled user is the business satisfied user, the system dispatches the next priority user. The simulation results show that compared with the PF algorithm, B-PF can improve the system throughput, the business satisfaction and fairness.

  2. An assessment of innovative pricing schemes for the communication of value: is price discrimination and two-part pricing a way forward?

    Science.gov (United States)

    Hertzman, Peter; Miller, Paul; Tolley, Keith

    2018-02-01

    With the introduction of new expensive medicines, traditional pricing schemes based on constructs such as price per pill/vial have been challenged. Potential innovative schemes could be either financial-based or performance-based. Within financial-based schemes the use of price discrimination is an emerging option, which we explore in this assessment. Areas covered: In the short term the price per indication approach is likely to become more prevalent for high cost, high benefit new pharmaceuticals, such as those emerging in oncology (e.g. new combination immunotherapies). 'Two-Part Pricing' (2PP) is a frequently used payment method in other industries, which consists of an Entry Fee, giving the buyer the right to use the product, and a Usage Price charged every time the product is purchased. Introducing 2PP into biopharma could have cross-stakeholder benefits including broader patient access, and improvement in budget/revenue predictability. A concern however is the potential complexity of the negotiation between manufacturer and payer. Expert commentary: We believe 'price discrimination' and 2PP in particular can be relevant for some new, expensive specialist medicines. A recommended first step would be to initiate pilots to test to what degree the 2PP approach meets stakeholder objectives and is practical to implement within specialty care.

  3. Energy Optimization in Smart Homes Using Customer Preference and Dynamic Pricing

    Directory of Open Access Journals (Sweden)

    Muhammad Babar Rasheed

    2016-07-01

    Full Text Available In this paper, we present an energy optimization technique to schedule three types of household appliances (user dependent, interactive schedulable and unschedulable in response to the dynamic behaviours of customers, electricity prices and weather conditions. Our optimization technique schedules household appliances in real time to optimally control their energy consumption, such that the electricity bills of end users are reduced while not compromising on user comfort. More specifically, we use the binary multiple knapsack problem formulation technique to design an objective function, which is solved via the constraint optimization technique. Simulation results show that average aggregated energy savings with and without considering the human presence control system are 11.77% and 5.91%, respectively.

  4. Project Scheduling Based on Risk of Gas Transmission Pipe

    Science.gov (United States)

    Silvianita; Nurbaity, A.; Mulyadi, Y.; Suntoyo; Chamelia, D. M.

    2018-03-01

    The planning of a project has a time limit on which must be completed before or right at a predetermined time. Thus, in a project planning, it is necessary to have scheduling management that is useful for completing a project to achieve maximum results by considering the constraints that will exists. Scheduling management is undertaken to deal with uncertainties and negative impacts of time and cost in project completion. This paper explains about scheduling management in gas transmission pipeline project Gresik-Semarang to find out which scheduling plan is most effectively used in accordance with its risk value. Scheduling management in this paper is assissted by Microsoft Project software to find the critical path of existing project scheduling planning data. Critical path is the longest scheduling path with the fastest completion time. The result is found a critical path on project scheduling with completion time is 152 days. Furthermore, the calculation of risk is done by using House of Risk (HOR) method and it is found that the critical path has a share of 40.98 percent of all causes of the occurence of risk events that will be experienced.

  5. Cuba's transition to market-based energy prices

    International Nuclear Information System (INIS)

    Perez-Lopez, J.F.

    1992-01-01

    Since 1960 the Soviet Union has been, for all practical purposes, Cuba's exclusive supplier of energy products. For certain time periods, Soviet sales of oil and oil products to Cuba were made at concessional prices; prior to 1991, they were priced using transferable rubles and were essentially bartered for Cuban goods, especially sugar. Effective January 1, 1991, the Soviet Union shifted to world market prices and convertible currency payments for all traded commodities, including energy products. The shift to market prices and convertible currencies in Cuban-Soviet energy trade has already brought - or is likely to bring - a number of adjustments in four areas: (1) the trade balance; (2) the ability to reexport oil and oil products; (3) energy consumption patterns; (4) and the structure of energy supplies. 33 refs., 8 tabs

  6. Theoretical and practical bases of transfer pricing formation at the microlevel in terms of national economy

    OpenAIRE

    Oksana Desyatniuk; Olga Cherevko

    2015-01-01

    The theoretical and methodological bases of transfer pricing formation at microlevel are studied. The factors acting upon transfer pricing are analysed and the algorithm to form transfer price at an enterprise is suggested. The model example to choose the method of transfer pricing and calculate the profitability interval meeting modern legal requirements is considered.

  7. TRICARE revision to CHAMPUS DRG-based payment system, pricing of hospital claims. Final rule.

    Science.gov (United States)

    2014-05-21

    This Final rule changes TRICARE's current regulatory provision for inpatient hospital claims priced under the DRG-based payment system. Claims are currently priced by using the rates and weights that are in effect on a beneficiary's date of admission. This Final rule changes that provision to price such claims by using the rates and weights that are in effect on a beneficiary's date of discharge.

  8. Analysis of Medicine Prices in New Zealand and 16 European Countries.

    Science.gov (United States)

    Vogler, Sabine; Kilpatrick, Kate; Babar, Zaheer-Ud-Din

    2015-06-01

    To compare prices of medicines, both originators and generics, in New Zealand and 16 European countries. Ex-factory price data as of December 2012 from New Zealand and 16 European countries were compared for a basket of 14 medicines, most of which were at least partially funded by the state in the 17 countries. Five medicines had, at least in some countries, generic versions on the market whose prices were also analyzed. Medicine price data for the 16 European countries were provided by the Pharma Price Information service. New Zealand medicine prices were retrieved from the New Zealand Pharmaceutical Schedule. Unit prices converted into euro were compared at the ex-factory price level. For the 14 medicines surveyed, considerable price differences at the ex-factory price level were identified. Within the European countries, prices in Greece, Portugal, the United Kingdom, and Spain ranked at the lower end, whereas prices in Switzerland, Germany, Denmark, and Sweden were at the upper end. The results for New Zealand compared with Europe were variable. New Zealand prices were found in the lowest quartile for five medicines and in the highest quartile for seven other products. Price differences between the originator products and generic versions ranged from 0% to 90% depending on the medicine and the country. Medicine prices varied considerably between European countries and New Zealand as well as among the European countries. These differences are likely to result from national pricing and reimbursement policies. Copyright © 2015 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  9. Cross-border electricity market effects due to price caps in an emission trading system: An agent-based approach

    International Nuclear Information System (INIS)

    Richstein, Jörn C.; Chappin, Emile J.L.; Vries, Laurens J. de

    2014-01-01

    The recent low CO 2 prices in the European Union Emission Trading Scheme (EU ETS) have triggered a discussion whether the EU ETS needs to be adjusted. We study the effects of CO 2 price floors and a price ceiling on the dynamic investment pathway of two interlinked electricity markets (loosely based on Great Britain, which already has introduced a price floor, and on Central Western Europe). Using an agent-based electricity market simulation with endogenous investment and a CO 2 market (including banking), we analyse the cross-border effects of national policies as well as system-wide policy options. A common, moderate CO 2 auction reserve price results in a more continuous decarbonisation pathway. This reduces CO 2 price volatility and the occurrence of carbon shortage price periods, as well as the average cost to consumers. A price ceiling can shield consumers from extreme price shocks. These price restrictions do not cause a large risk of an overall emissions overshoot in the long run. A national price floor lowers the cost to consumers in the other zone; the larger the zone with the price floor, the stronger the effect. Price floors that are too high lead to inefficiencies in investment choices and to higher consumer costs. - Highlights: • Cross-border effects of CO 2 policies were investigated with an agent-based model. • The current EU ETS might cause CO 2 price shocks and CO 2 price volatility. • A CO 2 auction reserve price does not lower welfare, but lowers CO 2 price volatility. • A national CO 2 price floor lowers consumer cost in the other countries. • A CO 2 price ceiling does not lead to an overshoot of emissions

  10. Stochastic multiobjective self-scheduling of a power producer in joint energy and reserves markets

    International Nuclear Information System (INIS)

    Vahidinasab, V.; Jadid, S.

    2010-01-01

    This paper presents a stochastic multiobjective model for self-scheduling of a power producer which participates in the day-ahead joint energy and reserves markets. The objective of a power producer is to compromise the conflicting objectives of payoff maximization and gaseous emissions minimization when committing its generation of thermal units. The proposed schedule will be used by the power producers to decide on emission quota arbitrage opportunities and for strategic bidding to the energy and reserves market. The paper analyzes a scenario-based multiobjective model in which random distributions, such as price forecasting inaccuracies as well as forced outage of generating units are modeled as scenarios tree using a combined fuzzy c-mean/Monte-Carlo simulation (FCM/MCS) method. With the above procedure the stochastic multiobjective self-scheduling problem is converted into corresponding deterministic problems. Then a multiobjective mathematical programming (MMP) approach based on ε-constraint method is implemented for each deterministic scenario. Piecewise linearized fuel and emission cost functions are applied for computational efficiency and the model is formulated as a mixed-integer programming (MIP) problem. Numerical simulations for a power producer with 21 thermal units are discussed to demonstrate the performance of the proposed approach in increasing expected payoffs by adjusting the emission quota arbitrage opportunities. (author)

  11. Regulation of Pharmaceutical Prices

    DEFF Research Database (Denmark)

    Kaiser, Ulrich; Mendez, Susan J.; Rønde, Thomas

    On April 1, 2005, Denmark changed the way references prices, a main determinant of reimbursements for pharmaceutical purchases, are calculated. The previous reference prices, which were based on average EU prices, were substituted to minimum domestic prices. Novel to the literature, we estimate...... the joint eects of this reform on prices and quantities. Prices decreased more than 26 percent due to the reform, which reduced patient and government expenditures by 3.0 percent and 5.6 percent, respectively, and producer revenues by 5.0 percent. The prices of expensive products decreased more than...

  12. On cost-informed pricing and customer value: a resource-advantage perspective on industrial innovation pricing practices

    OpenAIRE

    Ingenbleek, Paul; Debruyne, Marion; Frambach, Ruud T.

    2001-01-01

    By empirically testing a framework of pricing strategies and their determinants in an industrial setting, Noble and Gruca (1999a) help to overcome the lack of empirical validation of pricing theory. In a commentary to the article, Cressman (1999) (1) expresses worries about the high percentage of firms that engages in cost-based pricing; (2) raises a definition question on value-based pricing; and (3) stresses that empirical pricing literature does not provide ideas on successful pricing prac...

  13. How Do Drug Prices Respond to a Change from External to Internal Reference Pricing?

    DEFF Research Database (Denmark)

    Kaiser, Ulrich; Mendez, Susan J.

    (where they are based on the cheapest domestic substitute). We analyze three therapeutic classes with different treatment durations and show that the reform led to substantial price decreases for our lifelong treatment and to less substantial price reductions for our medium duration treatment while we do......We study the effects of a change in the way patient reimbursements are calculated on the prices of pharmaceuticals using quasi-experimental data for Denmark which switched from external (where reimbursements are based on prices of similar products in foreign countries) to internal reference pricing...

  14. Optimizing Human Diet Problem Based on Price and Taste Using

    Directory of Open Access Journals (Sweden)

    Hossein EGHBALI

    2012-07-01

    Full Text Available Low price and good taste of foods are regarded as two major factors for optimal human nutrition. Due to price fluctuations and taste diversity, these two factors cannot be certainly and determinately evaluated. This problem must be viewed from another perspective because of the uncertainty about the amount of nutrients per unit of foods and also diversity of people’s daily needs to receive them.This paper discusses human diet problem in fuzzy environment. The approach deals with multi-objective fuzzy linear programming problem using a fuzzy programming technique for its solution. By prescribing a diet merely based on crisp data, some ofthe realities are neglected. For the same reason, we dealt with human diet problem through fuzzy approach. Results indicated uncertainty about factors of nutrition diet -including taste and price, amount of nutrients and their intake- would affect diet quality, making the proposed diet more realistic.

  15. PRICE AND PRICING STRATEGIES

    OpenAIRE

    SUCIU Titus

    2013-01-01

    In individual companies, price is one significant factor in achieving marketing success. In many purchase situations, price can be of great importance to customers. Marketers must establish pricing strategies that are compatible with the rest of the marketing mix. Management should decide whether to charge the same price to all similar buyers of identical quantities of a product (a one-price strategy) or to set different prices (a flexible price strategy). Many organizations, especially retai...

  16. A Hybrid Node Scheduling Approach Based on Energy Efficient Chain Routing for WSN

    Directory of Open Access Journals (Sweden)

    Yimei Kang

    2014-04-01

    Full Text Available Energy efficiency is usually a significant goal in wireless sensor networks (WSNs. In this work, an energy efficient chain (EEC data routing approach is first presented. The coverage and connectivity of WSNs are discussed based on EEC. A hybrid node scheduling approach is then proposed. It includes sleep scheduling for cyclically monitoring regions of interest in time-driven modes and wakeup scheduling for tracking emergency events in event-driven modes. A failure rate is introduced to the sleep scheduling to improve the reliability of the system. A wakeup sensor threshold and a sleep time threshold are introduced in the wakeup scheduling to reduce the consumption of energy to the possible extent. The results of the simulation show that the proposed algorithm can extend the effective lifetime of the network to twice that of PEAS. In addition, the proposed methods are computing efficient because they are very simple to implement.

  17. A genetic algorithm-based job scheduling model for big data analytics.

    Science.gov (United States)

    Lu, Qinghua; Li, Shanshan; Zhang, Weishan; Zhang, Lei

    Big data analytics (BDA) applications are a new category of software applications that process large amounts of data using scalable parallel processing infrastructure to obtain hidden value. Hadoop is the most mature open-source big data analytics framework, which implements the MapReduce programming model to process big data with MapReduce jobs. Big data analytics jobs are often continuous and not mutually separated. The existing work mainly focuses on executing jobs in sequence, which are often inefficient and consume high energy. In this paper, we propose a genetic algorithm-based job scheduling model for big data analytics applications to improve the efficiency of big data analytics. To implement the job scheduling model, we leverage an estimation module to predict the performance of clusters when executing analytics jobs. We have evaluated the proposed job scheduling model in terms of feasibility and accuracy.

  18. Exploration of approaches to adjusting brand-name drug prices in Mainland of China: based on comparison and analysis of some brand-name drug prices of Mainland and Taiwan, China.

    Science.gov (United States)

    Weng, Geng; Han, Sheng; Pu, Run; Pan, Wynn H T; Shi, Luwen

    2014-01-01

    Under the circumstance of the New Medical Reform in Mainland of China, lowering drug prices has become an approach to relieving increase of medical expenses, and lowering brand-name medication price is a key strategy. This study, by comparing and analyzing brand-name medication prices between Mainland of China and Taiwan, explores how to adjust brand-name medication prices in Mainland of China in the consideration of the drug administrative strategies in Taiwan. By selecting brand-name drug with generic name and dose types matched in Mainland and Taiwan, calculate the average unit price and standard deviation and test it with the paired t-test. In the mean time, drug administrative strategies between Mainland and Taiwan are also compared systematically. Among the 70 brand-name medications with generic names and matched dose types, 54 are at higher prices in Mainland of China than Taiwan, which is statistically significant in t-test. Also, among the 47 medications with all of matched generic names, dose types, and manufacturing enterprises, 38 are at higher prices in Mainland than Taiwan, and the gap is also statistically significant in t-test. In Mainland of China, brand-name medication took cost-plus pricing and price-based price adjustment, while in Taiwan, brand-name medication took internal and external reference pricing and market-based price adjustment. Brand-name drug prices were higher in Mainland of China than in Taiwan. The adjustment strategies of drug prices are scientific in Taiwan and are worth reference by Mainland of China.

  19. Customizing Prices in Online Markets

    OpenAIRE

    Werner Reinartz

    2002-01-01

    Dynamic pricing is the dynamic adjustment of prices to consumers depending on the value these customers attribute to a good. Underlying the concept of dynamic pricing is what marketers call price customization. Price customization is the charging of different prices to end consumers based on a discriminatory variable. Internet technology will serve as a great enabling tool for making dynamic pricing accessible to many industries.

  20. Hypergraph+: An Improved Hypergraph-Based Task-Scheduling Algorithm for Massive Spatial Data Processing on Master-Slave Platforms

    Directory of Open Access Journals (Sweden)

    Bo Cheng

    2016-08-01

    Full Text Available Spatial data processing often requires massive datasets, and the task/data scheduling efficiency of these applications has an impact on the overall processing performance. Among the existing scheduling strategies, hypergraph-based algorithms capture the data sharing pattern in a global way and significantly reduce total communication volume. Due to heterogeneous processing platforms, however, single hypergraph partitioning for later scheduling may be not optimal. Moreover, these scheduling algorithms neglect the overlap between task execution and data transfer that could further decrease execution time. In order to address these problems, an extended hypergraph-based task-scheduling algorithm, named Hypergraph+, is proposed for massive spatial data processing. Hypergraph+ improves upon current hypergraph scheduling algorithms in two ways: (1 It takes platform heterogeneity into consideration offering a metric function to evaluate the partitioning quality in order to derive the best task/file schedule; and (2 It can maximize the overlap between communication and computation. The GridSim toolkit was used to evaluate Hypergraph+ in an IDW spatial interpolation application on heterogeneous master-slave platforms. Experiments illustrate that the proposed Hypergraph+ algorithm achieves on average a 43% smaller makespan than the original hypergraph scheduling algorithm but still preserves high scheduling efficiency.

  1. Multivariate EMD-Based Modeling and Forecasting of Crude Oil Price

    Directory of Open Access Journals (Sweden)

    Kaijian He

    2016-04-01

    Full Text Available Recent empirical studies reveal evidence of the co-existence of heterogeneous data characteristics distinguishable by time scale in the movement crude oil prices. In this paper we propose a new multivariate Empirical Mode Decomposition (EMD-based model to take advantage of these heterogeneous characteristics of the price movement and model them in the crude oil markets. Empirical studies in benchmark crude oil markets confirm that more diverse heterogeneous data characteristics can be revealed and modeled in the projected time delayed domain. The proposed model demonstrates the superior performance compared to the benchmark models.

  2. Trading network predicts stock price.

    Science.gov (United States)

    Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi

    2014-01-16

    Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading network. We then classify the nodes of trading network into three roles according to their connectivity pattern. Strong Granger causality is found between stock price and trading relationship indices, i.e., the fraction of trading relationship among nodes with different roles. We further predict stock price by incorporating these trading relationship indices into a neural network based on time series of stock price. Experimental results on 51 stocks in two Chinese Stock Exchanges demonstrate the accuracy of stock price prediction is significantly improved by the inclusion of trading relationship indices.

  3. STS pricing policy

    Science.gov (United States)

    Lee, C. M.; Stone, B.

    1982-01-01

    In 1977 NASA published Shuttle Reimbursement Policies for Civil U.S. Government, DOD and Commercial and Foreign Users. These policies were based on the principle of total cost recovery over a period of time with a fixed flat price for initial period to time to enhance transition. This fixed period was to be followed with annual adjustments thereafter, NASA is establishing a new price for 1986 and beyond. In order to recover costs, that price must be higher than the initial fixed price through FY 1985. NASA intends to remain competitive. Competitive posture includes not only price, but other factors such as assured launch, reliability, and unique services. NASA's pricing policy considers all these factors.

  4. Regulation of Pharmaceutical Prices

    DEFF Research Database (Denmark)

    Kaiser, Ulrich; Méndez, Susan J.; Rønde, Thomas

    2014-01-01

    Reference prices constitute a main determinant of patient health care reimbursement in many countries. We study the effects of a change from an "external" (based on a basket of prices in other countries) to an "internal" (based on comparable domestic products) reference price system. We find...... that while our estimated consumer compensating variation is small, the reform led to substantial reductions in list and reference prices as well as co-payments, and to sizeable decreases in overall producer revenues, health care expenditures, and co-payments. These effects differ markedly between branded...

  5. Regulation of Pharmaceutical Prices

    DEFF Research Database (Denmark)

    Kaiser, Ulrich; Méndez, Susan J.; Rønde, Thomas

    Reference prices constitute a main determinant of patient health care reimbursement in many countries. We study the effects of a change from an "external" (based on a basket of prices in other countries) to an "internal" (based on comparable domestic products) reference price system. We find...... that while our estimated consumer compensating variation is small, the reform led to substantial reductions in list and reference prices as well as co-payments, and to sizeable decreases in overall producer revenues, health care expenditures, and co-payments. These effects differ markedly between branded...

  6. Strategic Generation with Conjectured Transmission Price Responses in a Mixed Transmission Pricing System. Part 2. Application

    International Nuclear Information System (INIS)

    Wals, A.F.; Hobbs, B.F.; Rijkers, F.A.M.

    2004-05-01

    The conjectured transmission price response model presented in the first of this two-paper series considers the expectations of oligopolistic generators regarding how demands for transmission services affect the prices of those services. Here, the model is applied to northwest Europe, simulating a mixed transmission pricing system including export fees, a path-based auction system for between-country interfaces, and implicit congestion-based pricing of internal country constraints. The path-based system does not give credit for counterflows when calculating export capability. The application shows that this no-netting policy can exacerbate the economic inefficiencies caused by oligopolistic pricing by generators. The application also illustrates the effects of different generator conjectures regarding rival supply responses and transmission prices. If generators anticipate that their increased demand for transmission services will increase transmission prices, then competitive intensity diminishes and energy prices rise. In the example here, the effect of this anticipation is to double the price increase that results from oligopolistic (Cournot) competition among generators

  7. Heuristic algorithm for single resource constrained project scheduling problem based on the dynamic programming

    Directory of Open Access Journals (Sweden)

    Stanimirović Ivan

    2009-01-01

    Full Text Available We introduce a heuristic method for the single resource constrained project scheduling problem, based on the dynamic programming solution of the knapsack problem. This method schedules projects with one type of resources, in the non-preemptive case: once started an activity is not interrupted and runs to completion. We compare the implementation of this method with well-known heuristic scheduling method, called Minimum Slack First (known also as Gray-Kidd algorithm, as well as with Microsoft Project.

  8. Simulated Annealing-Based Ant Colony Algorithm for Tugboat Scheduling Optimization

    Directory of Open Access Journals (Sweden)

    Qi Xu

    2012-01-01

    Full Text Available As the “first service station” for ships in the whole port logistics system, the tugboat operation system is one of the most important systems in port logistics. This paper formulated the tugboat scheduling problem as a multiprocessor task scheduling problem (MTSP after analyzing the characteristics of tugboat operation. The model considers factors of multianchorage bases, different operation modes, and three stages of operations (berthing/shifting-berth/unberthing. The objective is to minimize the total operation times for all tugboats in a port. A hybrid simulated annealing-based ant colony algorithm is proposed to solve the addressed problem. By the numerical experiments without the shifting-berth operation, the effectiveness was verified, and the fact that more effective sailing may be possible if tugboats return to the anchorage base timely was pointed out; by the experiments with the shifting-berth operation, one can see that the objective is most sensitive to the proportion of the shifting-berth operation, influenced slightly by the tugboat deployment scheme, and not sensitive to the handling operation times.

  9. Study on Cloud Computing Resource Scheduling Strategy Based on the Ant Colony Optimization Algorithm

    OpenAIRE

    Lingna He; Qingshui Li; Linan Zhu

    2012-01-01

    In order to replace the traditional Internet software usage patterns and enterprise management mode, this paper proposes a new business calculation mode- cloud computing, resources scheduling strategy is the key technology in cloud computing, Based on the study of cloud computing system structure and the mode of operation, The key research for cloud computing the process of the work scheduling and resource allocation problems based on ant colony algorithm , Detailed analysis and design of the...

  10. Price performance following stock's IPO in different price limit systems

    Science.gov (United States)

    Wu, Ting; Wang, Yue; Li, Ming-Xia

    2018-01-01

    An IPO burst occurred in China's stock markets in 2015, while price limit trading rules usually help to reduce the short-term trading mania on individual stocks. It is interesting to make clear the function of the price limits after IPOs. We firstly make a statistical analysis based on all the IPO stocks listed from 1990 to 2015. A high dependency exists between the activities in stock's IPO and various market environment. We also focus on the price dynamics in the first 40 trading days after the stock listed. We find that price limit system will delay the price movement, especially for the up-trend movements, which may lead to longer continuous price limit hits. Similar to our previous work, many results such as ;W; shape can be also observed in the future daily return after the price limit open. At last, we find most IPO measures show evident correlations with the following price limit hits. IPO stocks with lower first-day turnover and earning per share will be followed with a longer continuous price limit hits and lower future daily return under the newest trading rules, which give us a good way to estimate the occurrence of price limit hits and the following price dynamics. Our analysis provides a better understanding of the price dynamics after IPO events and offers potential practical values for investors.

  11. Operationalizing value-based pricing of medicines : a taxonomy of approaches.

    Science.gov (United States)

    Sussex, Jon; Towse, Adrian; Devlin, Nancy

    2013-01-01

    The UK Government is proposing a novel form of price regulation for branded medicines, which it has dubbed 'value-based pricing' (VBP). The specifics of how VBP will work are unclear. We provide an account of the possible means by which VBP of medicines might be operationalized, and a taxonomy to describe and categorize the various approaches. We begin with a brief discussion of the UK Government's proposal for VBP and proceed to define a taxonomy of approaches to VBP. The taxonomy has five main dimensions: (1) what is identified as being of value, (2) how each element is measured, (3) how it is valued, (4) how the different elements of value are aggregated, and (5) how the result is then used to determine the price of a medicine. We take as our starting point that VBP will include a measure of health gain and that, as proposed by the UK Government, this will be built on the QALY. Our principal interest is in the way criteria other than QALYs are taken into account, including severity of illness, the extent of unmet need, and wider societal considerations such as impacts on carers. We set out to: (1) identify and describe the full range of alternative means by which 'value' might be measured and valued, (2) identify and describe the options available for aggregating the different components of value to establish a maximum price, and (3) note the challenges and relative advantages associated with these approaches. We review the means by which aspects of VBP are currently operationalized in a selection of countries and place these, and proposals for the UK, in the context of our taxonomy. Finally, we give an initial assessment of the challenges, pros and cons of each approach. We conclude that identifying where VBP should lie on each of the five dimensions entails value judgements: there are no simple 'right or wrong' solutions. If a wider definition of value than incremental QALYs gained is adopted, as is desirable, then a pragmatic way to aggregate the different

  12. Value-Based Pricing and Reimbursement in Personalised Healthcare: Introduction to the Basic Health Economics.

    Science.gov (United States)

    Garrison, Louis P; Towse, Adrian

    2017-09-04

    'Value-based' outcomes, pricing, and reimbursement are widely discussed as health sector reforms these days. In this paper, we discuss their meaning and relationship in the context of personalized healthcare, defined as receipt of care conditional on the results of a biomarker-based diagnostic test. We address the question: "What kinds of pricing and reimbursement models should be applied in personalized healthcare?" The simple answer is that competing innovators and technology adopters should have incentives that promote long-term dynamic efficiency. We argue that-to meet this social objective of optimal innovation in personalized healthcare-payers, as agents of their plan participants, should aim to send clear signals to their suppliers about what they value. We begin by revisiting the concept of value from an economic perspective, and argue that a broader concept of value is needed in the context of personalized healthcare. We discuss the market for personalized healthcare and the interplay between price and reimbursement. We close by emphasizing the potential barrier posed by inflexible or cost-based reimbursement systems, especially for biomarker-based predictive tests, and how these personalized technologies have global public goods characteristics that require global value-based differential pricing to achieve dynamic efficiency in terms of the optimal rate of innovation and adoption.

  13. Resource management and scheduling policy based on grid for AIoT

    Science.gov (United States)

    Zou, Yiqin; Quan, Li

    2017-07-01

    This paper has a research on resource management and scheduling policy based on grid technology for Agricultural Internet of Things (AIoT). Facing the situation of a variety of complex and heterogeneous agricultural resources in AIoT, it is difficult to represent them in a unified way. But from an abstract perspective, there are some common models which can express their characteristics and features. Based on this, we proposed a high-level model called Agricultural Resource Hierarchy Model (ARHM), which can be used for modeling various resources. It introduces the agricultural resource modeling method based on this model. Compared with traditional application-oriented three-layer model, ARHM can hide the differences of different applications and make all applications have a unified interface layer and be implemented without distinction. Furthermore, it proposes a Web Service Resource Framework (WSRF)-based resource management method and the encapsulation structure for it. Finally, it focuses on the discussion of multi-agent-based AG resource scheduler, which is a collaborative service provider pattern in multiple agricultural production domains.

  14. Prices and Price Setting

    NARCIS (Netherlands)

    R.P. Faber (Riemer)

    2010-01-01

    textabstractThis thesis studies price data and tries to unravel the underlying economic processes of why firms have chosen these prices. It focuses on three aspects of price setting. First, it studies whether the existence of a suggested price has a coordinating effect on the prices of firms.

  15. A cost-based empirical model of the aggregate price determination for the Turkish economy: A multivariate cointegration approach

    Directory of Open Access Journals (Sweden)

    Zeren Fatma

    2010-01-01

    Full Text Available This paper tries to examine the long run relationships between the aggregate consumer prices and some cost-based components for the Turkish economy. Based on a simple economic model of the macro-scaled price formation, multivariate cointegration techniques have been applied to test whether the real data support the a priori model construction. The results reveal that all of the factors, related to the price determination, have a positive impact on the consumer prices as expected. We find that the most significant component contributing to the price setting is the nominal exchange rate depreciation. We also cannot reject the linear homogeneity of the sum of all the price data as to the domestic inflation. The paper concludes that the Turkish consumer prices have in fact a strong cost-push component that contributes to the aggregate pricing.

  16. Optimal coordinated scheduling of combined heat and power fuel cell, wind, and photovoltaic units in micro grids considering uncertainties

    International Nuclear Information System (INIS)

    Bornapour, Mosayeb; Hooshmand, Rahmat-Allah; Khodabakhshian, Amin; Parastegari, Moein

    2016-01-01

    In this paper, a stochastic model is proposed for coordinated scheduling of combined heat and power units in micro grid considering wind turbine and photovoltaic units. Uncertainties of electrical market price; the speed of wind and solar radiation are considered using a scenario-based method. In the method, scenarios are generated using roulette wheel mechanism based on probability distribution functions of input random variables. Using this method, the probabilistic specifics of the problem are distributed and the problem is converted to a deterministic one. The type of the objective function, coordinated scheduling of combined heat and power, wind turbine, and photovoltaic units change this problem to a mixed integer nonlinear one. Therefore to solve this problem modified particle swarm optimization algorithm is employed. The mentioned uncertainties lead to an increase in profit. Moreover, the optimal coordinated scheduling of renewable energy resources and thermal units in micro grids increase the total profit. In order to evaluate the performance of the proposed method, its performance is executed on modified 33 bus distributed system as a micro grid. - Highlights: • Stochastic model is proposed for coordinated scheduling of renewable energy sources. • The effect of combined heat and power is considered. • Maximizing profits of micro grid is considered as objective function. • Considering the uncertainties of problem lead to profit increasing. • Optimal scheduling of renewable energy sources and thermal units increases profit.

  17. Automated Scheduling Via Artificial Intelligence

    Science.gov (United States)

    Biefeld, Eric W.; Cooper, Lynne P.

    1991-01-01

    Artificial-intelligence software that automates scheduling developed in Operations Mission Planner (OMP) research project. Software used in both generation of new schedules and modification of existing schedules in view of changes in tasks and/or available resources. Approach based on iterative refinement. Although project focused upon scheduling of operations of scientific instruments and other equipment aboard spacecraft, also applicable to such terrestrial problems as scheduling production in factory.

  18. Improved irrigation scheduling for pear-jujube trees based on trunk ...

    African Journals Online (AJOL)

    A suitable indicator for scheduling pear-jujube (Ziziphus jujuba Mill.) irrigation in China was developed based on trunk diameter fluctuations (TDF). Parameters derived from TDF responses to variations in soil matrix potential (Ψsoil) were compared under deficit and well irrigation. Maximum daily shrinkage (MDS) increased ...

  19. Saving-Based Asset Pricing

    DEFF Research Database (Denmark)

    Dreyer, Johannes Kabderian; Schneider, Johannes; T. Smith, William

    2013-01-01

    This paper explores the implications of a novel class of preferences for the behavior of asset prices. Following a suggestion by Marshall (1920), we entertain the possibility that people derive utility not only from consumption, but also from the very act of saving. These ‘‘saving-based’’ prefere...

  20. The value of innovation under value-based pricing

    Science.gov (United States)

    Moreno, Santiago G.; Ray, Joshua A.

    2016-01-01

    Objective The role of cost-effectiveness analysis (CEA) in incentivizing innovation is controversial. Critics of CEA argue that its use for pricing purposes disregards the ‘value of innovation’ reflected in new drug development, whereas supporters of CEA highlight that the value of innovation is already accounted for. Our objective in this article is to outline the limitations of the conventional CEA approach, while proposing an alternative method of evaluation that captures the value of innovation more accurately. Method The adoption of a new drug benefits present and future patients (with cost implications) for as long as the drug is part of clinical practice. Incidence patients and off-patent prices are identified as two key missing features preventing the conventional CEA approach from capturing 1) benefit to future patients and 2) future savings from off-patent prices. The proposed CEA approach incorporates these two features to derive the total lifetime value of an innovative drug (i.e., the value of innovation). Results The conventional CEA approach tends to underestimate the value of innovative drugs by disregarding the benefit to future patients and savings from off-patent prices. As a result, innovative drugs are underpriced, only allowing manufacturers to capture approximately 15% of the total value of innovation during the patent protection period. In addition to including the incidence population and off-patent price, the alternative approach proposes pricing new drugs by first negotiating the share of value of innovation to be appropriated by the manufacturer (>15%?) and payer (price that satisfies this condition. Conclusion We argue for a modification to the conventional CEA approach that integrates the total lifetime value of innovative drugs into CEA, by taking into account off-patent pricing and future patients. The proposed approach derives a price that allows manufacturers to capture an agreed share of this value, thereby incentivizing

  1. The value of innovation under value-based pricing.

    Science.gov (United States)

    Moreno, Santiago G; Ray, Joshua A

    2016-01-01

    The role of cost-effectiveness analysis (CEA) in incentivizing innovation is controversial. Critics of CEA argue that its use for pricing purposes disregards the 'value of innovation' reflected in new drug development, whereas supporters of CEA highlight that the value of innovation is already accounted for. Our objective in this article is to outline the limitations of the conventional CEA approach, while proposing an alternative method of evaluation that captures the value of innovation more accurately. The adoption of a new drug benefits present and future patients (with cost implications) for as long as the drug is part of clinical practice. Incidence patients and off-patent prices are identified as two key missing features preventing the conventional CEA approach from capturing 1) benefit to future patients and 2) future savings from off-patent prices. The proposed CEA approach incorporates these two features to derive the total lifetime value of an innovative drug (i.e., the value of innovation). The conventional CEA approach tends to underestimate the value of innovative drugs by disregarding the benefit to future patients and savings from off-patent prices. As a result, innovative drugs are underpriced, only allowing manufacturers to capture approximately 15% of the total value of innovation during the patent protection period. In addition to including the incidence population and off-patent price, the alternative approach proposes pricing new drugs by first negotiating the share of value of innovation to be appropriated by the manufacturer (>15%?) and payer (price that satisfies this condition. We argue for a modification to the conventional CEA approach that integrates the total lifetime value of innovative drugs into CEA, by taking into account off-patent pricing and future patients. The proposed approach derives a price that allows manufacturers to capture an agreed share of this value, thereby incentivizing innovation, while supporting health

  2. National contingency plan product schedule data base

    International Nuclear Information System (INIS)

    Putukian, J.; Hiltabrand, R.R.

    1993-01-01

    During oil spills there are always proposals by the technical community and industry to use chemical agents to help in oil spill cleanups. Federal Clean Water Act regulations require that any chemical agents that the federal on-scene coordinator (FOSC) wants to use for oil cleanup be listed on the US Environmental Protection Agency (EPA) National Contingency Plan (NCP) Product Schedule. Chemical countermeasures are among the most controversial, complex, and time-critical issues facing decision-making officials choosing response methods to use on coastal oil spills. There are situations in which dispersants are likely to be one of the most appropriate counter-measure strategies. Dispersants are most effective when applied to fresh oil, and their effectiveness dramatically decreases as the oil weathers, which can begin in as little as 24 hours. To logistically implement dispersant use, a decision would need to be made within roughly the first 4 hours after the release. Most of the information that the FOSC needs to make the determination to use a specific chemical agent exists in manuals, EPA bulletins, and the published literature. This information is not in an easy-to-use format under field emergency conditions. Hence the need to collect and disseminate the information in an automated data base. The sources for the information in this data base are the following. Published results of tests performed by Environment Canada; EPA bulletins associated with the NCP Product Schedule; Published results of tests by the chemical industry. The data base resides on a Macintosh computer and contains information about 70 NCP products, including dispersants, surface collecting agents, and biological additives. It contains information on physical properties, toxicity, heavy metal content, safety precautions, use conditions, etc

  3. Accounting for fuel price risk: Using forward natural gas prices instead of gas price forecasts to compare renewable to natural gas-fired generation

    Energy Technology Data Exchange (ETDEWEB)

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-08-13

    Against the backdrop of increasingly volatile natural gas prices, renewable energy resources, which by their nature are immune to natural gas fuel price risk, provide a real economic benefit. Unlike many contracts for natural gas-fired generation, renewable generation is typically sold under fixed-price contracts. Assuming that electricity consumers value long-term price stability, a utility or other retail electricity supplier that is looking to expand its resource portfolio (or a policymaker interested in evaluating different resource options) should therefore compare the cost of fixed-price renewable generation to the hedged or guaranteed cost of new natural gas-fired generation, rather than to projected costs based on uncertain gas price forecasts. To do otherwise would be to compare apples to oranges: by their nature, renewable resources carry no natural gas fuel price risk, and if the market values that attribute, then the most appropriate comparison is to the hedged cost of natural gas-fired generation. Nonetheless, utilities and others often compare the costs of renewable to gas-fired generation using as their fuel price input long-term gas price forecasts that are inherently uncertain, rather than long-term natural gas forward prices that can actually be locked in. This practice raises the critical question of how these two price streams compare. If they are similar, then one might conclude that forecast-based modeling and planning exercises are in fact approximating an apples-to-apples comparison, and no further consideration is necessary. If, however, natural gas forward prices systematically differ from price forecasts, then the use of such forecasts in planning and modeling exercises will yield results that are biased in favor of either renewable (if forwards < forecasts) or natural gas-fired generation (if forwards > forecasts). In this report we compare the cost of hedging natural gas price risk through traditional gas-based hedging instruments (e

  4. Decentralized Job Scheduling in the Cloud Based on a Spatially Generalized Prisoner’s Dilemma Game

    Directory of Open Access Journals (Sweden)

    Gąsior Jakub

    2015-12-01

    Full Text Available We present in this paper a novel distributed solution to a security-aware job scheduling problem in cloud computing infrastructures. We assume that the assignment of the available resources is governed exclusively by the specialized brokers assigned to individual users submitting their jobs to the system. The goal of this scheme is allocating a limited quantity of resources to a specific number of jobs minimizing their execution failure probability and total completion time. Our approach is based on the Pareto dominance relationship and implemented at an individual user level. To select the best scheduling strategies from the resulting Pareto frontiers and construct a global scheduling solution, we developed a decision-making mechanism based on the game-theoretic model of Spatial Prisoner’s Dilemma, realized by selfish agents operating in the two-dimensional cellular automata space. Their behavior is conditioned by the objectives of the various entities involved in the scheduling process and driven towards a Nash equilibrium solution by the employed social welfare criteria. The performance of the scheduler applied is verified by a number of numerical experiments. The related results show the effectiveness and scalability of the scheme in the presence of a large number of jobs and resources involved in the scheduling process.

  5. Crude oil price analysis and forecasting based on variational mode decomposition and independent component analysis

    Science.gov (United States)

    E, Jianwei; Bao, Yanling; Ye, Jimin

    2017-10-01

    As one of the most vital energy resources in the world, crude oil plays a significant role in international economic market. The fluctuation of crude oil price has attracted academic and commercial attention. There exist many methods in forecasting the trend of crude oil price. However, traditional models failed in predicting accurately. Based on this, a hybrid method will be proposed in this paper, which combines variational mode decomposition (VMD), independent component analysis (ICA) and autoregressive integrated moving average (ARIMA), called VMD-ICA-ARIMA. The purpose of this study is to analyze the influence factors of crude oil price and predict the future crude oil price. Major steps can be concluded as follows: Firstly, applying the VMD model on the original signal (crude oil price), the modes function can be decomposed adaptively. Secondly, independent components are separated by the ICA, and how the independent components affect the crude oil price is analyzed. Finally, forecasting the price of crude oil price by the ARIMA model, the forecasting trend demonstrates that crude oil price declines periodically. Comparing with benchmark ARIMA and EEMD-ICA-ARIMA, VMD-ICA-ARIMA can forecast the crude oil price more accurately.

  6. Marketing environment dynamics and implications for pricing strategies: the case of home health care.

    Science.gov (United States)

    Ponsford, B J; Barlow, D

    1999-01-01

    This research reviews the factors affecting the pricing or rate schedules of home health care agencies. A large number of factors affect costs and thus rate structures. The major factors include reimbursement structures with accompanying discount structures, administrative burdens, and risks. Channel issues include bargaining power, competition, and size. Staffing issues affect pricing and product through the provider level, productivity, and quality outcomes. Physician and patient issues include quality concerns and choices. These factors are discussed in light of overall marketing strategy and the interaction of pricing with other marketing controllables such as product, place/distribution, and promotion. Economic and accounting principles are also reviewed with consideration to understanding direct and indirect costs in order to enable negotiators to effectively price health care services.

  7. Hybrid LSA-ANN Based Home Energy Management Scheduling Controller for Residential Demand Response Strategy

    Directory of Open Access Journals (Sweden)

    Maytham S. Ahmed

    2016-09-01

    Full Text Available Demand response (DR program can shift peak time load to off-peak time, thereby reducing greenhouse gas emissions and allowing energy conservation. In this study, the home energy management scheduling controller of the residential DR strategy is proposed using the hybrid lightning search algorithm (LSA-based artificial neural network (ANN to predict the optimal ON/OFF status for home appliances. Consequently, the scheduled operation of several appliances is improved in terms of cost savings. In the proposed approach, a set of the most common residential appliances are modeled, and their activation is controlled by the hybrid LSA-ANN based home energy management scheduling controller. Four appliances, namely, air conditioner, water heater, refrigerator, and washing machine (WM, are developed by Matlab/Simulink according to customer preferences and priority of appliances. The ANN controller has to be tuned properly using suitable learning rate value and number of nodes in the hidden layers to schedule the appliances optimally. Given that finding proper ANN tuning parameters is difficult, the LSA optimization is hybridized with ANN to improve the ANN performances by selecting the optimum values of neurons in each hidden layer and learning rate. Therefore, the ON/OFF estimation accuracy by ANN can be improved. Results of the hybrid LSA-ANN are compared with those of hybrid particle swarm optimization (PSO based ANN to validate the developed algorithm. Results show that the hybrid LSA-ANN outperforms the hybrid PSO based ANN. The proposed scheduling algorithm can significantly reduce the peak-hour energy consumption during the DR event by up to 9.7138% considering four appliances per 7-h period.

  8. Paying more for faster care? Individuals' attitude toward price-based priority access in health care.

    Science.gov (United States)

    Benning, Tim M; Dellaert, Benedict G C

    2013-05-01

    Increased competition in the health care sector has led hospitals and other health care institutions to experiment with new access allocation policies that move away from traditional expert based allocation of care to price-based priority access (i.e., the option to pay more for faster care). To date, little is known about individuals' attitude toward price-based priority access and the evaluation process underlying this attitude. This paper addresses the role of individuals' evaluations of collective health outcomes as an important driver of their attitude toward (price-based) allocation policies in health care. The authors investigate how individuals evaluate price-based priority access by means of scenario-based survey data collected in a representative sample from the Dutch population (N = 1464). They find that (a) offering individuals the opportunity to pay for faster care negatively affects their evaluations of both the total and distributional collective health outcome achieved, (b) however, when health care supply is not restricted (i.e., when treatment can be offered outside versus within the regular working hours of the hospital) offering price-based priority access affects total collective health outcome evaluations positively instead of negatively, but it does not change distributional collective health outcome evaluations. Furthermore, (c) the type of health care treatment (i.e., life saving liver transplantation treatment vs. life improving cosmetic ear correction treatment - priced at the same level to the individual) moderates the effect of collective health outcome evaluations on individuals' attitude toward allocation policies. For policy makers and hospital managers the results presented in this article are helpful because they provide a better understanding of what drives individuals' preferences for health care allocation policies. In particular, the results show that policies based on the "paying more for faster care" principle are more

  9. Economic power schedule and transactive energy through an intelligent centralized energy management system for a DC residential distribution system

    DEFF Research Database (Denmark)

    Yue, Jingpeng; Hu, Zhijian; Li, Chendan

    2017-01-01

    and the demand side. The utilization of distributed generation (DG) requires an economic operation, stability, and an environmentally friendly approach in the whole DC system. This paper not only presents an optimization schedule and transactive energy (TE) approach through a centralized energy management system...... is aligned with the command of the unit power schedule. In this work, a DC RDS is used as a case study to demonstrate the process, the RDS is associated with unit economic models, and a cost minimization objective is proposed that is to be achieved based on the real-time electrical price. The results show...... that the proposed framework and methods will help the targeted DC residential system to reduce the total cost and reach stability and efficiency....

  10. The Interval Slope Method for Long-Term Forecasting of Stock Price Trends

    Directory of Open Access Journals (Sweden)

    Chun-xue Nie

    2016-01-01

    Full Text Available A stock price is a typical but complex type of time series data. We used the effective prediction of long-term time series data to schedule an investment strategy and obtain higher profit. Due to economic, environmental, and other factors, it is very difficult to obtain a precise long-term stock price prediction. The exponentially segmented pattern (ESP is introduced here and used to predict the fluctuation of different stock data over five future prediction intervals. The new feature of stock pricing during the subinterval, named the interval slope, can characterize fluctuations in stock price over specific periods. The cumulative distribution function (CDF of MSE was compared to those of MMSE-BC and SVR. We concluded that the interval slope developed here can capture more complex dynamics of stock price trends. The mean stock price can then be predicted over specific time intervals relatively accurately, in which multiple mean values over time intervals are used to express the time series in the long term. In this way, the prediction of long-term stock price can be more precise and prevent the development of cumulative errors.

  11. Value-Based Pricing and Reimbursement in Personalised Healthcare: Introduction to the Basic Health Economics

    Directory of Open Access Journals (Sweden)

    Louis P. Garrison

    2017-09-01

    Full Text Available ‘Value-based’ outcomes, pricing, and reimbursement are widely discussed as health sector reforms these days. In this paper, we discuss their meaning and relationship in the context of personalized healthcare, defined as receipt of care conditional on the results of a biomarker-based diagnostic test. We address the question: “What kinds of pricing and reimbursement models should be applied in personalized healthcare?” The simple answer is that competing innovators and technology adopters should have incentives that promote long-term dynamic efficiency. We argue that—to meet this social objective of optimal innovation in personalized healthcare—payers, as agents of their plan participants, should aim to send clear signals to their suppliers about what they value. We begin by revisiting the concept of value from an economic perspective, and argue that a broader concept of value is needed in the context of personalized healthcare. We discuss the market for personalized healthcare and the interplay between price and reimbursement. We close by emphasizing the potential barrier posed by inflexible or cost-based reimbursement systems, especially for biomarker-based predictive tests, and how these personalized technologies have global public goods characteristics that require global value-based differential pricing to achieve dynamic efficiency in terms of the optimal rate of innovation and adoption.

  12. Value-Based Pricing and Reimbursement in Personalised Healthcare: Introduction to the Basic Health Economics

    Science.gov (United States)

    Garrison, Louis P.; Towse, Adrian

    2017-01-01

    ‘Value-based’ outcomes, pricing, and reimbursement are widely discussed as health sector reforms these days. In this paper, we discuss their meaning and relationship in the context of personalized healthcare, defined as receipt of care conditional on the results of a biomarker-based diagnostic test. We address the question: “What kinds of pricing and reimbursement models should be applied in personalized healthcare?” The simple answer is that competing innovators and technology adopters should have incentives that promote long-term dynamic efficiency. We argue that—to meet this social objective of optimal innovation in personalized healthcare—payers, as agents of their plan participants, should aim to send clear signals to their suppliers about what they value. We begin by revisiting the concept of value from an economic perspective, and argue that a broader concept of value is needed in the context of personalized healthcare. We discuss the market for personalized healthcare and the interplay between price and reimbursement. We close by emphasizing the potential barrier posed by inflexible or cost-based reimbursement systems, especially for biomarker-based predictive tests, and how these personalized technologies have global public goods characteristics that require global value-based differential pricing to achieve dynamic efficiency in terms of the optimal rate of innovation and adoption. PMID:28869571

  13. PERFORMANCE ANALYSIS OF AI BASED QOS SCHEDULER FOR MOBILE WIMAX

    Directory of Open Access Journals (Sweden)

    D. David Neels Pon Kumar

    2012-09-01

    Full Text Available Interest in broadband wireless access (BWA has been growing due to increased user mobility and the need for data access at all times. IEEE 802.16e based WiMAX networks promise the best available quality of experience for mobile data service users. WiMAX networks incorporate several Quality of Service (QoS mechanisms at the Media Access Control (MAC level for guaranteed services for multimedia viz. data, voice and video. The problem of assuring QoS is how to allocate available resources among users to meet the QoS criteria such as delay, delay jitter, fairness and throughput requirements. IEEE standard does not include a standard scheduling mechanism and leaves it for various implementer differentiations. Although a lot of the real-time and non real-time packet scheduling schemes has been proposed, it needs to be modified to apply to Mobile WiMAX system that supports five kinds of service classes. In this paper, we propose a novel Priority based Scheduling scheme that uses Artificial Intelligence to support various services by considering the QoS constraints of each class. The simulation results show that slow mobility does not affect the performances and faster mobility and the increment in users beyond a particular load have their say in defining average throughput, average per user throughput, fairness index, average end to end delay and average delay jitter. Nevertheless the results are encouraging that the proposed scheme provides QoS support for each class efficiently.

  14. Feasibility and attractiveness of indication value-based pricing in key EU countries.

    Science.gov (United States)

    Flume, Mathias; Bardou, Marc; Capri, Stefano; Sola-Morales, Oriol; Cunningham, David; Levin, Lars-Ake; Touchot, Nicolas

    2016-01-01

    Indication value-based pricing (IBP) has been proposed in the United States as a tool to capture the differential value of drugs across indications or patient groups and is in the early phases of implementation. In Europe, no major country has experimented with IBP or is seriously discussing its use. We assessed how the reimbursement and pricing environment allows for IBP in seven European countries, evaluating both incentives and hurdles. In price setting countries such as France and Germany, the Health Technology Assessment and pricing process already accounts for differences of value across indications. In countries where differential value drives coverage decisions such as the United Kingdom and Sweden, IBP is likely to be used, at least partially, but not in the short-term. Italy is already achieving some form of differential value through managed entry agreements, whereas in Spain the electronic prescription system provides the infrastructure necessary for IBP but other hurdles exist.

  15. A Framework for Uplink Intercell Interference Modeling with Channel-Based Scheduling

    KAUST Repository

    Tabassum, Hina

    2012-12-29

    This paper presents a novel framework for modeling the uplink intercell interference(ICI) in a multiuser cellular network. The proposed framework assists in quantifying the impact of various fading channel models and state-of-the-art scheduling schemes on the uplink ICI. Firstly, we derive a semianalytical expression for the distribution of the location of the scheduled user in a given cell considering a wide range of scheduling schemes. Based on this, we derive the distribution and moment generating function (MGF) of the uplink ICI considering a single interfering cell. Consequently, we determine the MGF of the cumulative ICI observed from all interfering cells and derive explicit MGF expressions for three typical fading models. Finally, we utilize the obtained expressions to evaluate important network performance metrics such as the outage probability, ergodic capacity, and average fairness numerically. Monte-Carlo simulation results are provided to demonstrate the efficacy of the derived analytical expressions.

  16. Real-time-service-based Distributed Scheduling Scheme for IEEE 802.16j Networks

    OpenAIRE

    Kuo-Feng Huang; Shih-Jung Wu

    2013-01-01

    Supporting Quality of Service (QoS) guarantees for diverse multimedia services is the primary concern for IEEE802.16j networks. A scheduling scheme that satisfies the QoS requirements has become more important for wireless communications. We proposed an adaptive nontransparent-based distributed scheduling scheme (ANDS) for IEEE 802.16j networks. ANDS comprises three major components: Priority Assignment, Resource Allocation, Preserved Bandwidth Adjustment. Different service-type connections p...

  17. Distributional incidence of green electricity price subsidies in China

    International Nuclear Information System (INIS)

    Wang, Feng; Zhang, Bing

    2016-01-01

    Distributional incidences are fundamental to environmental and energy policies, a condition that has led to controversies on the equity of environmental and energy policy. Using data from China's Urban Household Income and Expenditure Survey data from 2007, this study quantified the distributional effects of the green electricity price subsidy policy among Chinese urban household and compared its effects by using lifetime income and annual income to classify households, respectively. The results show that total electricity subsidies are mainly driven by indirect electricity subsidies. By using lifetime income to classify households, subsidies to households in the poorest two groups accounted for less than 10.2% of the total subsidies, whereas money distributed to households in the top two deciles reached 35.4%. The comparison using annual income to group households also demonstrated the similar impact of the green electricity price subsidy policy. China’s future market reforms should allow electricity prices to reflect pollution abatement costs. Additionally, a multi-step block electricity price schedule can reduce the regressivity of the policy. - Highlights: • We quantified the distributional effects of the green electricity price subsidy. • The distributional effects of different income groups were compared. • The poorest two groups accounted for less than 10.2% of the total subsidies. • The green electricity price subsidy policy benefited the rich at household level.

  18. Scheduling the scheduling task : a time management perspective on scheduling

    NARCIS (Netherlands)

    Larco Martinelli, J.A.; Wiers, V.C.S.; Fransoo, J.C.

    2013-01-01

    Time is the most critical resource at the disposal of schedulers. Hence, an adequate management of time from the schedulers may impact positively on the scheduler’s productivity and responsiveness to uncertain scheduling environments. This paper presents a field study of how schedulers make use of

  19. Dutch house price fundamentals

    NARCIS (Netherlands)

    Haffner, M.E.A.; de Vries, P.

    2009-01-01

    This paper discusses house price developments in the Netherlands, specifically focussing on the question whether current house prices in the Dutch owner-occupied market are likely to decrease. We analyse three aspects of the question based on a literature review: (1) whether there is a house price

  20. Price setting in turbulent times

    DEFF Research Database (Denmark)

    Ólafsson, Tjörvi; Pétursdóttir, Ásgerdur; Vignisdóttir, Karen Á.

    This price setting survey among Icelandic firms aims to make two contributions to the literature. First, it studies price setting in an advanced economy within a more turbulent macroeconomic environment than has previously been done. The results indicate that price adjustments are to a larger...... extent driven by exchange rate fluctuations than in most other advanced countries. The median Icelandic firm reviews its prices every four months and changes them every six months. The main sources of price rigidity and the most commonly used price setting methods are the same as in most other countries....... A second contribution to the literature is our analysis of the nexus between price setting and exchange rate movements, a topic that has attracted surprisingly limited attention in this survey-based literature. A novel aspect of our approach is to base our analysis on a categorisation of firms...

  1. Optimization and Flight Schedules of Pioneer Routes in Papua Province

    Science.gov (United States)

    Ronting, Y.; Adisasmita, S. A.; Hamid, S.; Hustim, M.

    2018-04-01

    The province of Papua has a very varied topography, ranging from swampy lowlands, hills, and plateaus up steep hills. The total area of land is 410,660 km2, which consists of 28 counties and one city, 389 districts and 5.420 villages. The population of Papua Province in 2017 was 3.265.202 people with an average growth of 4.21% per year. The transportation services is still low, especially in the mountainous region, which is isolated and could only be reached by an air transportation mode, causing a considerable price disparity between coastal and mountainous areas. The purpose of this paper is to develop the route optimization and pioneer flight schedules models as an airbridge. This research is conducted by collecting primary data and secondary data. Data is based on field surveys; interviews; discussions with airport authority, official government, etc; and also from various agencies. The analytical tools used to optimization flight schedule and route are analyzed by add-in solver in Microsoft Excel. The results of the analysis we can get a more optimal route so that it can save transportation costs by 7.26%.

  2. Optimizing Air Transportation Service to Metroplex Airports. Par 2; Analysis Using the Airline Schedule Optimization Model (ASOM)

    Science.gov (United States)

    Donoue, George; Hoffman, Karla; Sherry, Lance; Ferguson, John; Kara, Abdul Qadar

    2010-01-01

    The air transportation system is a significant driver of the U.S. economy, providing safe, affordable, and rapid transportation. During the past three decades airspace and airport capacity has not grown in step with demand for air transportation; the failure to increase capacity at the same rate as the growth in demand results in unreliable service and systemic delay. This report describes the results of an analysis of airline strategic decision-making that affects geographic access, economic access, and airline finances, extending the analysis of these factors using historic data (from Part 1 of the report). The Airline Schedule Optimization Model (ASOM) was used to evaluate how exogenous factors (passenger demand, airline operating costs, and airport capacity limits) affect geographic access (markets-served, scheduled flights, aircraft size), economic access (airfares), airline finances (profit), and air transportation efficiency (aircraft size). This analysis captures the impact of the implementation of airport capacity limits, as well as the effect of increased hedged fuel prices, which serve as a proxy for increased costs per flight that might occur if auctions or congestion pricing are imposed; also incorporated are demand elasticity curves based on historical data that provide information about how passenger demand is affected by airfare changes.

  3. A pharmacoeconomic modeling approach to estimate a value-based price for new oncology drugs in Europe.

    Science.gov (United States)

    Dranitsaris, George; Ortega, Ana; Lubbe, Martie S; Truter, Ilse

    2012-03-01

    Several European governments have recently mandated price cuts in drugs to reduce health care spending. However, such measures without supportive evidence may compromise patient care because manufacturers may withdraw current products or not launch new agents. A value-based pricing scheme may be a better approach for determining a fair drug price and may be a medium for negotiations between the key stakeholders. To demonstrate this approach, pharmacoeconomic (PE) modeling was used from the Spanish health care system perspective to estimate a value-based price for bevacizumab, a drug that provides a 1.4-month survival benefit to patients with metastatic colorectal cancer (mCRC). The threshold used for economic value was three times the Spanish per capita GDP, as recommended by the World Health Organization (WHO). A PE model was developed to simulate outcomes in mCRC patients receiving chemotherapy ± bevacizumab. Clinical data were obtained from randomized trials and costs from a Spanish hospital. Utility estimates were determined by interviewing 24 Spanish oncology nurses and pharmacists. A price per dose of bevacizumab was then estimated using a target threshold of € 78,300 per quality-adjusted life year gained, which is three times the Spanish per capita GDP. For a 1.4-month survival benefit, a price of € 342 per dose would be considered cost effective from the Spanish public health care perspective. The price may be increased to € 733 or € 843 per dose if the drug were able to improve patient quality of life or enhance survival from 1.4 to 3 months. This study demonstrated that a value-based pricing approach using PE modeling and the WHO criteria for economic value is feasible and perhaps a better alternative to government mandated price cuts. The former approach would be a good starting point for opening dialog between European government payers and the pharmaceutical industry.

  4. Instant Childhood Immunization Schedule

    Science.gov (United States)

    ... Recommendations Why Immunize? Vaccines: The Basics Instant Childhood Immunization Schedule Recommend on Facebook Tweet Share Compartir Get ... date. See Disclaimer for additional details. Based on Immunization Schedule for Children 0 through 6 Years of ...

  5. Empirical assessment of energy-price policies: the case for cross-price elasticities

    International Nuclear Information System (INIS)

    Frondel, M.

    2004-01-01

    Evaluations of energy-price policies are necessarily based on measures of the substitution of energy and non-energy inputs. Facing a variety of substitution elasticities, the central question arises which measure would be appropriate. Apparently, for a long time, this question has not been at issue: Allen's elasticities of substitution (AES) have been the most-used measures in applied production analysis. This paper's main contribution is an instructive survey of the origin of substitution measures and of the trinity of empirical substitution elasticities-AES, cross-price elasticities, and the Morishima elasticities of substitution (MES)-with particular emphasis on their interpretations and the perspectives that will be captured by these measures. This survey clarifies why classical cross-price elasticities are to be preferred for many practical purposes. Berndt and Wood's (Rev. Econom. Stat. 57(1975) 259) frequently applied data set of US manufacturing is used to illustrate why assessments of energy-price policies would be better based on cross-price elasticities like the energy-price elasticity of capital, rather than on AES or MES. (author)

  6. Empirical assessment of energy-price policies: the case for cross-price elasticities

    International Nuclear Information System (INIS)

    Frondel, Manuel

    2004-01-01

    Evaluations of energy-price policies are necessarily based on measures of the substitution of energy and non-energy inputs. Facing a variety of substitution elasticities, the central question arises which measure would be appropriate. Apparently, for a long time, this question has not been at issue: Allen's elasticities of substitution (AES) have been the most-used measures in applied production analysis. This paper's main contribution is an instructive survey of the origin of substitution measures and of the trinity of empirical substitution elasticities - AES, cross-price elasticities, and the Morishima elasticities of substitution (MES) - with particular emphasis on their interpretations and the perspectives that will be captured by these measures. This survey clarifies why classical cross-price elasticities are to be preferred for many practical purposes. Berndt and Wood's (Rev. Econom. Stat. 57 (1975) 259) frequently applied data set of US manufacturing is used to illustrate why assessments of energy-price policies would be better based on cross-price elasticities like the energy-price elasticity of capital, rather than on AES or MES

  7. Stochastic scheduling of aggregators of plug-in electric vehicles for participation in energy and ancillary service markets

    International Nuclear Information System (INIS)

    Alipour, Manijeh; Mohammadi-Ivatloo, Behnam; Moradi-Dalvand, Mohammad; Zare, Kazem

    2017-01-01

    Plug-in electric vehicles are expected to play a major role in the transportation system as the environmental problems and energy crisis are being more and more urgent recently. Implementing a large number of vehicles with proper control could bring an opportunity of large storage and flexibility for power systems. The plug-in electric vehicle aggregator is responsible for providing power and controlling the charging pattern of the plug-in electric vehicles under its contracted area. This paper deals with the problem of optimal scheduling problem of plug-in electric vehicle aggregators in electricity market considering the uncertainties of market prices, availability of vehicles and status of being called by the ISO in the reserve market. The impact of the market price and reserve market uncertainties on the electric vehicle scheduling problem is characterized through a stochastic programming framework. The objective of the aggregator is to maximize its profit by charging the plug-in electric vehicles on the low price time intervals as well as participating in ancillary service markets. The operational constraints of plug-in electric vehicles and constraints of vehicle to grid are modeled in the proposed framework. An illustrative example is provided to confirm the performance of the proposed model. - Highlights: • Optimal scheduling of vehicle aggregators in electricity market has been addressed. • The operational constraints of plug-in vehicle to grid are considered. • The uncertainties of calling status in reserve market and market prices are modeled. • Vehicles' driving patterns and availability uncertainty are modeled. • The effect of risk measure weight in the vehicle to grid model has been studied.

  8. Innovative Production Scheduling with Customer Satisfaction Based Measurement for the Sustainability of Manufacturing Firms

    Directory of Open Access Journals (Sweden)

    Sang-Oh Shim

    2017-12-01

    Full Text Available Scheduling problems for the sustainability of manufacturing firms in the era of the fourth industrial revolution is addressed in this research. In terms of open innovation, innovative production scheduling can be defined as scheduling using big data, cyber-physical systems, internet of things, cloud computing, mobile network, and so on. In this environment, one of the most important things is to develop an innovative scheduling algorithm for the sustainability of manufacturing firms. In this research, a flexible flowshop scheduling problem is considered with the properties of sequence-dependent setup and different process plans for jobs. In a flexible flowshop, there are serial workstations with multiple pieces of equipment that are able to process multiple lots simultaneously. Since the scheduling in this workshop is known to be extremely difficult, it is important to devise an efficient and effective scheduling algorithm. In this research, a heuristic algorithm is proposed based on a few dispatching rules and economic lot size model with the objective of minimizing total tardiness of orders. For the purposes of performance evaluation, a simulation study is conducted on randomly generated problem instances. The results imply that our proposed method outperforms the existing ones, and greatly enhances the sustainability of manufacturing firms.

  9. 7 CFR 1000.50 - Class prices, component prices, and advanced pricing factors.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 9 2010-01-01 2009-01-01 true Class prices, component prices, and advanced pricing... advanced pricing factors. Class prices per hundredweight of milk containing 3.5 percent butterfat, component prices, and advanced pricing factors shall be as follows. The prices and pricing factors described...

  10. Land of Addicts? An Empirical Investigation of Habit-Based Asset Pricing Behavior

    OpenAIRE

    Xiaohong Chen; Sydney C. Ludvigson

    2004-01-01

    This paper studies the ability of a general class of habit-based asset pricing models to match the conditional moment restrictions implied by asset pricing theory. We treat the functional form of the habit as unknown, and to estimate it along with the rest of the model's finite dimensional parameters. Using quarterly data on consumption growth, assets returns and instruments, our empirical results indicate that the estimated habit function is nonlinear, the habit formation is better described...

  11. Effectiveness of the management of price risk methodologies for the corn market based on trading signals

    Directory of Open Access Journals (Sweden)

    W. Rossouw

    2013-03-01

    Full Text Available Corn production is scattered geographically over various continents, but most of it is grown in the United States. As such, the world price of corn futures contracts is largely dominated by North American corn prices as traded on the Chicago Board of Trade. In recent years, this market has been characterised by an increase in price volatility and magnitude of price movement as a result of decreasing stock levels. The development and implementation of an effective and successful derivative price risk management strategy based on the Chicago Board of Trade corn futures contract will therefore be of inestimable value to market stakeholders worldwide. The research focused on the efficient market hypothesis and the possibility of contesting this phenomenon through an application of a derivative price risk management methodology. The methodology is based on a combination of an analysis of market trends and technical oscillators with the objective of generating returns superior to that of a market benchmark. The study found that market participants are currently unable to exploit price movement in a manner which results in returns that contest the notion of efficient markets. The methodology proposed, however, does allow the user to consistently achieve returns superior to that of a predetermined market benchmark. The benchmark price for the purposes of this study was the average price offered by the market over the contract lifetime, and as such, the efficient market hypothesis was successfully contested

  12. Dynamic pricing for demand response considering market price uncertainty

    DEFF Research Database (Denmark)

    Ghazvini, Mohammad Ali Fotouhi; Soares, Joao; Morais, Hugo

    2017-01-01

    Retail energy providers (REPs) can employ different strategies such as offering demand response (DR) programs, participating in bilateral contracts, and employing self-generation distributed generation (DG) units to avoid financial losses in the volatile electricity markets. In this paper......, the problem of setting dynamic retail sales price by a REP is addressed with a robust optimization technique. In the proposed model, the REP offers price-based DR programs while it faces uncertainties in the wholesale market price. The main contribution of this paper is using a robust optimization approach...

  13. Transfer Pricing - An Innovative Approach

    Directory of Open Access Journals (Sweden)

    Ramona MAXIM

    2017-06-01

    Full Text Available This paper presents transfer pricing and elements of drafting the transfer pricing file by the big companies. The transfer pricing procedure was founded based upon Order no. 442/2016 and the Fiscal Procedure Code and it represents a method upon which the tax base is transferred from a high tax country to a country with low taxation. This legislation outlines the conditions which companies must observe in order to draft the transfer pricing documentation and the significance thresholds. The purpose to draft a transfer pricing file is to reduce the differences between prices and market value and the actual results of company taxation. Economic double taxation occurs when tax authorities apply price adjustments because the company did not respect the principle of market value. Keeping records of transfer pricing and practicing a price aligned to market requirements contribute to an understanding of business development and the creation of appropriate tax planning. Taking into account all these aspects and the fact that any taxpayer is tempted to pay the lowest possible fees, tax havens become an option. In this context we can speak of a tax haven as a loophole in the use of the market price.

  14. A derived heuristics based multi-objective optimization procedure for micro-grid scheduling

    Science.gov (United States)

    Li, Xin; Deb, Kalyanmoy; Fang, Yanjun

    2017-06-01

    With the availability of different types of power generators to be used in an electric micro-grid system, their operation scheduling as the load demand changes with time becomes an important task. Besides satisfying load balance constraints and the generator's rated power, several other practicalities, such as limited availability of grid power and restricted ramping of power output from generators, must all be considered during the operation scheduling process, which makes it difficult to decide whether the optimization results are accurate and satisfactory. In solving such complex practical problems, heuristics-based customized optimization algorithms are suggested. However, due to nonlinear and complex interactions of variables, it is difficult to come up with heuristics in such problems off-hand. In this article, a two-step strategy is proposed in which the first task deciphers important heuristics about the problem and the second task utilizes the derived heuristics to solve the original problem in a computationally fast manner. Specifically, the specific operation scheduling is considered from a two-objective (cost and emission) point of view. The first task develops basic and advanced level knowledge bases offline from a series of prior demand-wise optimization runs and then the second task utilizes them to modify optimized solutions in an application scenario. Results on island and grid connected modes and several pragmatic formulations of the micro-grid operation scheduling problem clearly indicate the merit of the proposed two-step procedure.

  15. Market interdependence among commodity prices based on information transmission on the Internet

    Science.gov (United States)

    Ji, Qiang; Guo, Jian-Feng

    2015-05-01

    Human behaviour on the Internet has become a synchro-projection of real society. In this paper, we introduce the public concern derived from query volumes on the Web to empirically analyse the influence of information on commodity markets (e.g., crude oil, heating oil, corn and gold) using multivariate GARCH models based on dynamic conditional correlations. The analysis found that the changes of public concern on the Internet can well depict the changes of market prices, as the former has significant Granger causality effects on market prices. The findings indicate that the information of external shocks to commodity markets could be transmitted quickly, and commodity markets easily absorb the public concern of the information-sensitive traders. Finally, the conditional correlation among commodity prices varies dramatically over time.

  16. Pricing-based revenue management for flexible products on a network

    NARCIS (Netherlands)

    Sierag, DIrk

    2017-01-01

    This paper proposes and analyses a pricing-based revenue management model that allows flexible products on a network, with a non-trivial extension to group reservations. Under stochastic demand the problem can be solved using dynamic programming, though it suffers from the curse of dimensionality.

  17. Analysis and Development of a Web-Enabled Planning and Scheduling Database Application

    Science.gov (United States)

    2013-09-01

    will be fully functional of the Macintosh Operating System . This is the platform of the original database and the platform of the testing system ...was to explore available scheduling tools operational on the Macintosh Operating System with 78 the smallest practical price tag. The solution was...48 F. PROPOSED DBMS ENVIRONMENT .........................49 1. Operating System (OS) ........................49 2

  18. Model-based development of a course of action scheduling tool

    DEFF Research Database (Denmark)

    Kristensen, Lars Michael; Mechlenborg, Peter; Zhang, Lin

    2008-01-01

    . The scheduling capabilities of COAST are based on state space exploration of the embedded CPN model. Planners interact with COAST using a domain-specific graphical user interface (GUI) that hides the embedded CPN model and analysis algorithms. This means that COAST is based on a rigorous semantical model......, but the use of formal methods is transparent to the users. Trials of operational planning using COAST have been conducted within the Australian Defence Force....

  19. Domestic Price, (Expected) Foreign Price, and Travel Spending by Canadians in the United States

    OpenAIRE

    Jan Vilasuso; Fredric C. Menz

    1998-01-01

    In this paper, the authors develop and test a model to explain travel expenditures in the United States by Canadians. The model examines a consumer's choice problem where income is allocated between domestic and foreign consumption. Consumers do not know the foreign price level and base their spending in part on expected foreign price. In addition to expected foreign price, domestic price, exchange rates, income, and foreign price uncertainty influence travel spending. Empirically, each deter...

  20. Economic power schedule and transactive energy through an intelligent centralized energy management system for a DC residential distribution system

    DEFF Research Database (Denmark)

    Yue, Jingpeng; Hu, Zhijian; Li, Chendan

    2017-01-01

    Direct current (DC) residential distribution systems (RDS) consisting of DC living homes will be a significant integral part of future green transmission. Meanwhile, the increasing number of distributed resources and intelligent devices will change the power flow between the main grid...... (CEMS), but also a control approach to implement and ensure DG output voltages to various DC buses in a DC RDS. Based on data collection, prediction and a certain objectives, the expert system in a CEMS can work out the optimization schedule, after this, the voltage droop control for steady voltage...... is aligned with the command of the unit power schedule. In this work, a DC RDS is used as a case study to demonstrate the process, the RDS is associated with unit economic models, and a cost minimization objective is proposed that is to be achieved based on the real-time electrical price. The results show...

  1. Joint pricing and resource allocation for OFDMA-based cognitive radio systems

    KAUST Repository

    Ben Ghorbel, Mahdi; Goldsmith, André a J.; Alouini, Mohamed-Slim

    2011-01-01

    Cognitive users can share spectrum with primary users under constraints on the interference that results. We present a new pricing strategy for sharing the primary users' available subchannels with cognitive users by optimizing the secondary and primary users' utilities while meeting the primary users' interference constraints. The primary users aim to maximize their revenues by sharing their subchannels with secondary users while ensuring that they achieve a minimum target capacity. On the other hand, the secondary users aim to maximize their capacity under three different constraints: consumed power, a given budget for sharing subchannels, and tolerable interference caused to the primary users. We introduce a sequential procedure based on a distributed algorithm to determine the resource allocation, interference thresholds and prices that satisfy the requirements of both parties in the network. Simulations show that the users face a tradeoff between capacity, power, and price. © 2011 IEEE.

  2. Joint pricing and resource allocation for OFDMA-based cognitive radio systems

    KAUST Repository

    Ben Ghorbel, Mahdi

    2011-04-01

    Cognitive users can share spectrum with primary users under constraints on the interference that results. We present a new pricing strategy for sharing the primary users\\' available subchannels with cognitive users by optimizing the secondary and primary users\\' utilities while meeting the primary users\\' interference constraints. The primary users aim to maximize their revenues by sharing their subchannels with secondary users while ensuring that they achieve a minimum target capacity. On the other hand, the secondary users aim to maximize their capacity under three different constraints: consumed power, a given budget for sharing subchannels, and tolerable interference caused to the primary users. We introduce a sequential procedure based on a distributed algorithm to determine the resource allocation, interference thresholds and prices that satisfy the requirements of both parties in the network. Simulations show that the users face a tradeoff between capacity, power, and price. © 2011 IEEE.

  3. International positioning of South African electricity prices and commodity differentiated pricing

    Directory of Open Access Journals (Sweden)

    George A. Thopila

    2013-07-01

    Full Text Available The South African electricity industry has seen a dramatic increase in prices over the past 3 years. This increase has been blanketed across all sectors and is based on a number of factors such as sector, usage and, in the case of domestic pricing, suburb. The cost of electricity in South Africa, particularly to the industrial sector, has been among the lowest in the world. In this paper, we analyse the recent price increases in the South African electricity sector and discuss the price determination mechanism employed by Eskom, South Africa's electricity provider. We also analyse the revenue and sales of Eskom and review the electricity price from an international perspective. The concept of differential pricing and international benchmarking is analysed as a possibility for the South African industrial electricity industry, so that all sectors are not adversely affected by across-the-board increases. Our aim is to raise the question of whether South Africa's electricity prices are in line with international increases and to suggest the possibility of differentiated prices in the local electricity sector.

  4. Spikes and memory in (Nord Pool) electricity price spot prices

    DEFF Research Database (Denmark)

    Proietti, Tomasso; Haldrup, Niels; Knapik, Oskar

    Electricity spot prices are subject to transitory sharp movements commonly referred to as spikes. The paper aims at assessing their effects on model based inferences and predictions, with reference to the Nord Pool power exchange. We identify a spike as a price value which deviates substantially...

  5. Overcoming barriers to scheduling embedded generation to support distribution networks

    Energy Technology Data Exchange (ETDEWEB)

    Wright, A.J.; Formby, J.R.

    2000-07-01

    Current scheduling of embedded generation for distribution in the UK is limited and patchy. Some DNOs actively schedule while others do none. The literature on the subject is mainly about accommodating volatile wind output, and optimising island systems, for both cost of supply and network stability. The forthcoming NETA will lower prices, expose unpredictable generation to imbalance markets and could introduce punitive constraint payments on DNOs, but at the same time create a dynamic market for both power and ancillary services from embedded generators. Most renewable generators either run as base load (e.g. waste ) or according to the vagaries of the weather (e.g. wind, hydro), so offer little scope for scheduling other than 'off'. CHP plant is normally heat- led for industrial processes or building needs, but supplementary firing or thermal storage often allow considerable scope for scheduling. Micro-CHP with thermal storage could provide short-term scheduling, but tends to be running anyway during the evening peak. Standby generation appears to be ideal for scheduling, but in practice operators may be unwilling to run parallel with the network, and noise and pollution problems may preclude frequent operation. Statistical analysis can be applied to calculate the reliability of several generators compared to one; with a large number of generators such as micro-CHP reliability of a proportion of load is close to unity. The type of communication for generation used will depend on requirements for bandwidth, cost, reliability and whether it is bundled with other services. With high levels of deeply embedded, small-scale generation using induction machines, voltage control and black start capability will become important concerns on 11 kV and LV networks. This will require increased generation monitoring and remote control of switchgear. Examples of cost benefits from scheduling are given, including deferred reinforcement, increased exports on non

  6. A Hybrid Genetic Algorithm with a Knowledge-Based Operator for Solving the Job Shop Scheduling Problems

    Directory of Open Access Journals (Sweden)

    Hamed Piroozfard

    2016-01-01

    Full Text Available Scheduling is considered as an important topic in production management and combinatorial optimization in which it ubiquitously exists in most of the real-world applications. The attempts of finding optimal or near optimal solutions for the job shop scheduling problems are deemed important, because they are characterized as highly complex and NP-hard problems. This paper describes the development of a hybrid genetic algorithm for solving the nonpreemptive job shop scheduling problems with the objective of minimizing makespan. In order to solve the presented problem more effectively, an operation-based representation was used to enable the construction of feasible schedules. In addition, a new knowledge-based operator was designed based on the problem’s characteristics in order to use machines’ idle times to improve the solution quality, and it was developed in the context of function evaluation. A machine based precedence preserving order-based crossover was proposed to generate the offspring. Furthermore, a simulated annealing based neighborhood search technique was used to improve the local exploitation ability of the algorithm and to increase its population diversity. In order to prove the efficiency and effectiveness of the proposed algorithm, numerous benchmarked instances were collected from the Operations Research Library. Computational results of the proposed hybrid genetic algorithm demonstrate its effectiveness.

  7. Industrial Pricing: Theory and Managerial Practice

    OpenAIRE

    Peter M. Noble; Thomas S. Gruca

    1999-01-01

    We organize the existing theoretical pricing research into a new two-level framework for industrial goods pricing. The first level consists of four pricing situations: New Product, Competitive, Product Line, and Cost-based. The second level consists of the pricing strategies appropriate for a given situation. For example, within the new product pricing situation, there are three alternative pricing strategies: Skim, Penetration, and Experience Curve pricing. There are a total of ten pricing s...

  8. 10 CFR 218.12 - Pricing.

    Science.gov (United States)

    2010-01-01

    ... 10 Energy 3 2010-01-01 2010-01-01 false Pricing. 218.12 Section 218.12 Energy DEPARTMENT OF ENERGY OIL STANDBY MANDATORY INTERNATIONAL OIL ALLOCATION Supply Orders § 218.12 Pricing. The price for oil subject to a supply order issued pursuant to this subpart shall be based on the price conditions...

  9. Structural changes in the German pharmaceutical market: price setting mechanisms based on the early benefit evaluation.

    Science.gov (United States)

    Henschke, Cornelia; Sundmacher, Leonie; Busse, Reinhard

    2013-03-01

    In the past, free price setting mechanisms in Germany led to high prices of patented pharmaceuticals and to increasing expenditures in the pharmaceutical sector. In order to control patented pharmaceutical prices and to curb increasing pharmaceutical spending, the Act for Restructuring the Pharmaceutical Market in Statutory Health Insurance (AMNOG) came into effect on 1st January 2011. In a structured dossier, pharmaceutical manufacturers have to demonstrate the additional therapeutic benefit of the newly approved pharmaceutical compared to its appropriate comparator. According to the level of additional benefit, pharmaceuticals will be subject to price negotiations between the Federal Association of Statutory Health Insurance Funds and the pharmaceutical company concerned (or assigned to a reference price group in case of no additional benefit). Therefore, the health care reform is a first step to decision making based on "value for money". The process of price setting based on early benefit evaluation has an impact on the German as well as the European pharmaceutical markets. Therefore, these structural changes in Germany are of importance for pricing decisions in many European countries both from a political point of view and for strategic planning for pharmaceutical manufacturers, which may have an effect on insured patients' access to pharmaceuticals. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  10. Tri-generation based hybrid power plant scheduling for renewable resources rich area with energy storage

    International Nuclear Information System (INIS)

    Pazheri, F.R.

    2015-01-01

    Highlights: • Involves scheduling of the tri-generation based hybrid power plant. • Utilization of renewable energy through energy storage is discussed. • Benefits of the proposed model are illustrated. • Energy efficient and environmental friendly dispatch is analyzed. • Modeled scheduling problem is applicable to any fuel enriched area. - Abstract: Solving power system scheduling is crucial to ensure smooth operations of the electric power industry. Effective utilization of available conventional and renewable energy sources (RES) by tri-generation and with the aid of energy storage facilities (ESF) can ensure clean and energy efficient power generation. Such power generation can play an important role in countries, like Saudi Arabia, where abundant fossil fuels (FF) and renewable energy sources (RES) are available. Hence, effective modeling of such hybrid power systems scheduling is essential in such countries based on the available fuel resources. The intent of this paper is to present a simple model for tri-generation based hybrid power system scheduling for energy resources rich area in presence of ESF, to ensure optimum fuel utilization and minimum pollutant emissions while meeting the power demand. This research points an effective operation strategy which ensure a clean and energy efficient power scheduling by exploiting available energy resources effectively. Hence, it has an important role in current and future power generation. In order to illustrate the benefits of the presented approach a clean and energy efficient hybrid power supply scheme for King Saud University (KSU), Saudi Arabia, is proposed and analyzed here. Results show that the proposed approach is very suitable for KSU since adequate solar power is available during its peak demand periods

  11. The price of pollution

    International Nuclear Information System (INIS)

    Bleijenberg, A.N.; Davidson, M.D.; Wit, R.

    1998-06-01

    The market does not create a price for environmental pollution for the simple reason that there is no market for the environment. What can be done is to calculate shadow prices for environmental pollution, which is achieved by calculating the price that would arise if there would be a market for the environment. In applying this method, it generally proves to be necessary to base calculations on government environmental targets. Using available research data, the method is used to calculate shadow prices for a number of key pollutants. The present report is based on the CE studies 'Schaduwprijzen Prioriterings Methodiek (SPM)' (1997), commissioned by ICI Holland BV, and 'De prijs van Milieuvervuiling' (1997), commissioned by KNP BT Packaging

  12. Potential impacts of electricity price changes on price formation in the economy: a social accounting matrix price modeling analysis for Turkey

    International Nuclear Information System (INIS)

    Akkemik, K. Ali

    2011-01-01

    Recent reforms in the Turkish electricity sector since 2001 aim to introduce a tariff system that reflects costs. This is expected to affect the production and consumer prices of electricity. The changes in electricity prices are then reflected in production costs in other segments of the economy. Subsequently, producer and consumer prices will be affected. The potential impact of the changes in electricity prices that the ongoing electricity reforms in Turkey will bring about may have important implications on the price formation in economic activities and the cost of living for households. This paper evaluates the potential impacts of changes in electricity prices from a social accounting matrix (SAM) price modeling perspective. It is found that based on the estimated price multipliers that prices in the energy-producing sectors, mining, and iron and steel manufacturing sectors would be affected more severely than the remaining sectors of the economy. Consumer prices are affected slightly less than producer prices. - Research Highlights: → The impact of electricity generation costs on prices in other sectors is modeled. → A micro-SAM emphasizing electricity supply is constructed using 2002 I-O tables. → Energy, mining, and steel sectors are more responsive to electricity costs. → Living costs are less responsive to electricity cost changes than producer prices.

  13. An Optimal Scheduling Dispatch of a Microgrid under Risk Assessment

    Directory of Open Access Journals (Sweden)

    Whei-Min Lin

    2018-06-01

    Full Text Available This paper presents the scheduling dispatch of a microgrid (MG, while considering renewable energy, battery storage systems, and time-of-use price. For the risk evaluation of an MG, the Value-at-Risk (VAR is calculated by using the Historical Simulation Method (HSM. By considering the various confidence levels of the VAR, a scheduling dispatch model of the MG is formulated to achieve a reasonable trade-off between the risk and cost. An Improved Bee Swarm Optimization (IBSO is proposed to solve the scheduling dispatch model of the MG. In the IBSO procedure, the Sin-wave Weight Factor (SWF and Forward-Backward Control Factor (FBCF are embedded in the bee swarm of the BSO to improve the movement behaviors of each bee, specifically, its search efficiency and accuracy. The effectiveness of the IBSO is demonstrated via a real MG case and the results are compared with other methods. In either a grid-connected scenario or a stand-alone scenario, an optimal scheduling dispatch of MGs is carried out, herein, at various confidence levels of risk. The simulation results provide more information for handling uncertain environments when analyzing the VAR of MGs.

  14. Beyond the sticker price: including and excluding time in comparing food prices.

    Science.gov (United States)

    Yang, Yanliang; Davis, George C; Muth, Mary K

    2015-07-01

    An ongoing debate in the literature is how to measure the price of food. Most analyses have not considered the value of time in measuring the price of food. Whether or not the value of time is included in measuring the price of a food may have important implications for classifying foods based on their relative cost. The purpose of this article is to compare prices that exclude time (time-exclusive price) with prices that include time (time-inclusive price) for 2 types of home foods: home foods using basic ingredients (home recipes) vs. home foods using more processed ingredients (processed recipes). The time-inclusive and time-exclusive prices are compared to determine whether the time-exclusive prices in isolation may mislead in drawing inferences regarding the relative prices of foods. We calculated the time-exclusive price and time-inclusive price of 100 home recipes and 143 processed recipes and then categorized them into 5 standard food groups: grains, proteins, vegetables, fruit, and dairy. We then examined the relation between the time-exclusive prices and the time-inclusive prices and dietary recommendations. For any food group, the processed food time-inclusive price was always less than the home recipe time-inclusive price, even if the processed food's time-exclusive price was more expensive. Time-inclusive prices for home recipes were especially higher for the more time-intensive food groups, such as grains, vegetables, and fruit, which are generally underconsumed relative to the guidelines. Focusing only on the sticker price of a food and ignoring the time cost may lead to different conclusions about relative prices and policy recommendations than when the time cost is included. © 2015 American Society for Nutrition.

  15. Gist-based memory for prices and "better buys" in younger and older adults.

    Science.gov (United States)

    Flores, Cynthia C; Hargis, Mary B; McGillivray, Shannon; Friedman, Michael C; Castel, Alan D

    2017-04-01

    Ageing typically leads to various memory deficits which results in older adults' tendency to remember more general information and rely on gist memory. The current study examined if younger and older adults could remember which of two comparable grocery items (e.g., two similar but different jams) was paired with a lower price (the "better buy"). Participants studied lists of grocery items and their prices, in which the two items in each category were presented consecutively (Experiment 1), or separated by intervening items (Experiment 2). At test, participants were asked to identify the "better buy" and recall the price of both items. There were negligible age-related differences for the "better buy" in Experiment 1, but age-related differences were present in Experiment 2 when there were greater memory demands involved in comparing the two items. Together, these findings suggest that when price information of two items can be evaluated and compared within a short period of time, older adults can form stable gist-based memory for prices, but that this is impaired with longer delays. We relate the findings to age-related changes in the use of gist and verbatim memory when remembering prices, as well as the associative deficit account of cognitive ageing.

  16. The California ISO experience with price spikes and search for remedies

    Energy Technology Data Exchange (ETDEWEB)

    Barkovich, B. R. [Barkovich and Yap, Inc., San Francisco, CA (United States)

    2000-07-01

    An overview of the conditions under which price spikes have occurred in California, and the attempts to eliminate those conditions are discussed. Several periods of price spikes have occurred since the competitive electricity market became a reality in California, usually at times of high system load.. Price spikes in the ancillary services (A/S) (one of the two markets run by the California Independent System Operator (CAISO), the other being balancing or real-time energy), occurred when the supply of competitive bids has been restricted either by bid insufficiency or gaming. Bid insufficiency is the failure of the market to produce enough bids for a particular product. Gaming is defined as taking advantage of an occasion when there is likely to be short supply due to transmission constraints or geographical distribution of generation and using the occasion to maximize prices. The key tool used by the CAISO to reduce price spikes has been to reduce and adjust procurement of A/S by instituting additional enforcement of market participants' ability to meet their requirements to provide A/S on command. If they fail to do so, they do not receive payment for capacity that has been bid, with the bids accepted, but not provided. Changes in the scheduling system to facilitate inter-Scheduling Coordinator trades of A/S obligations, designed to reduce procurement through the CAISO markets and thus potentially lower market clearing prices for A/S in those markets, has been another technique used. The institution of 'Rational Buyer' has been yet another, and more substantial, means used to reduce price spikes. This mechanism, involving demand substitution across the markets for A/S, has the effect of defeating attempts by a generator to place a high-priced bid in a generally lower value market in the expectation of a smaller number of bids in that market. Significant decline in the amount of A/S procured, and a significant decline in the ratio of the total cost

  17. The California ISO experience with price spikes and search for remedies

    International Nuclear Information System (INIS)

    Barkovich, B. R.

    2000-01-01

    An overview of the conditions under which price spikes have occurred in California, and the attempts to eliminate those conditions are discussed. Several periods of price spikes have occurred since the competitive electricity market became a reality in California, usually at times of high system load.. Price spikes in the ancillary services (A/S) (one of the two markets run by the California Independent System Operator (CAISO), the other being balancing or real-time energy), occurred when the supply of competitive bids has been restricted either by bid insufficiency or gaming. Bid insufficiency is the failure of the market to produce enough bids for a particular product. Gaming is defined as taking advantage of an occasion when there is likely to be short supply due to transmission constraints or geographical distribution of generation and using the occasion to maximize prices. The key tool used by the CAISO to reduce price spikes has been to reduce and adjust procurement of A/S by instituting additional enforcement of market participants' ability to meet their requirements to provide A/S on command. If they fail to do so, they do not receive payment for capacity that has been bid, with the bids accepted, but not provided. Changes in the scheduling system to facilitate inter-Scheduling Coordinator trades of A/S obligations, designed to reduce procurement through the CAISO markets and thus potentially lower market clearing prices for A/S in those markets, has been another technique used. The institution of 'Rational Buyer' has been yet another, and more substantial, means used to reduce price spikes. This mechanism, involving demand substitution across the markets for A/S, has the effect of defeating attempts by a generator to place a high-priced bid in a generally lower value market in the expectation of a smaller number of bids in that market. Significant decline in the amount of A/S procured, and a significant decline in the ratio of the total cost of A

  18. Dynamic pricing based on a cloud computing framework to support the integration of renewable energy sources

    Directory of Open Access Journals (Sweden)

    Rajeev Thankappan Nair

    2014-12-01

    Full Text Available Integration of renewable energy sources into the electric grid in the domestic sector results in bidirectional energy flow from the supply side of the consumer to the grid. Traditional pricing methods are difficult to implement in such a situation of bidirectional energy flow and they face operational challenges on the application of price-based demand side management programme because of the intermittent characteristics of renewable energy sources. In this study, a dynamic pricing method using real-time data based on a cloud computing framework is proposed to address the aforementioned issues. The case study indicates that the dynamic pricing captures the variation of energy flow in the household. The dynamic renewable factor introduced in the model supports consumer oriented pricing. A new method is presented in this study to determine the appropriate level of photovoltaic (PV penetration in the distribution system based on voltage stability aspect. The load flow study result for the electric grid in Kerala, India, indicates that the overvoltage caused by various PV penetration levels up to 33% is within the voltage limits defined for distribution feeders. The result justifies the selected level of penetration.

  19. Integrating Preventive Maintenance Scheduling As Probability Machine Failure And Batch Production Scheduling

    Directory of Open Access Journals (Sweden)

    Zahedi Zahedi

    2016-06-01

    Full Text Available This paper discusses integrated model of batch production scheduling and machine maintenance scheduling. Batch production scheduling uses minimize total actual flow time criteria and machine maintenance scheduling uses the probability of machine failure based on Weibull distribution. The model assumed no nonconforming parts in a planning horizon. The model shows an increase in the number of the batch (length of production run up to a certain limit will minimize the total actual flow time. Meanwhile, an increase in the length of production run will implicate an increase in the number of PM. An example was given to show how the model and algorithm work.

  20. Day-ahead electricity prices forecasting by a modified CGSA technique and hybrid WT in LSSVM based scheme

    International Nuclear Information System (INIS)

    Shayeghi, H.; Ghasemi, A.

    2013-01-01

    Highlights: • Presenting a hybrid CGSA-LSSVM scheme for price forecasting. • Considering uncertainties for filtering in input data and feature selection to improve efficiency. • Using DWT input featured LSSVM approach to classify next-week prices. • Used three real markets to illustrate performance of the proposed price forecasting model. - Abstract: At the present time, day-ahead electricity market is closely associated with other commodity markets such as fuel market and emission market. Under such an environment, day-ahead electricity price forecasting has become necessary for power producers and consumers in the current deregulated electricity markets. Seeking for more accurate price forecasting techniques, this paper proposes a new combination of a Feature Selection (FS) technique based mutual information (MI) technique and Wavelet Transform (WT) in this study. Moreover, in this paper a new modified version of Gravitational Search Algorithm (GSA) optimization based chaos theory, namely Chaotic Gravitational Search Algorithm (CGSA) is developed to find the optimal parameters of Least Square Support Vector Machine (LSSVM) to predict electricity prices. The performance and price forecast accuracy of the proposed technique is assessed by means of real data from Iran’s, Ontario’s and Spain’s price markets. The simulation results from numerical tables and figures in different cases show that the proposed technique increases electricity price market forecasting accuracy than the other classical and heretical methods in the scientific researches

  1. Socioeconophysics:. Opinion Dynamics for Number of Transactions and Price, a Trader Based Model

    Science.gov (United States)

    Tuncay, Çağlar

    Involving effects of media, opinion leader and other agents on the opinion of individuals of market society, a trader based model is developed and utilized to simulate price via supply and demand. Pronounced effects are considered with several weights and some personal differences between traders are taken into account. Resulting time series and probabilty distribution function involving a power law for price come out similar to the real ones.

  2. Dynamic Pricing Based on Strategic Consumers and Substitutes in a Duopoly Setting

    Directory of Open Access Journals (Sweden)

    Gongbing Bi

    2014-01-01

    Full Text Available Based on the rational strategic consumers, we construct a dynamic game to build a two-period dynamic pricing model for two brands of substitutes which are sold by duopoly. The solution concept of the dynamic game is Nash equilibrium. In our model, consumers have been clearly segmented into several consumption classes, according to their expected value of the products. The two competing firms enter a pricing game and finally reach the state of Nash equilibrium. In addition, decision-making process with only myopic consumers existing in the market is analyzed. To make the paper more practical and realistic, the condition, in which the myopic and strategic consumers both exist in the market, is also considered and studied. In order to help the readers understand better and make it intuitively more clearly, a numerical example is given to describe the influence of the main parameters to the optimal prices. The result indicates that, to maintain the firms’ respective optimal profits, the prices of the products should be adjusted appropriately with the changes of product differentiation coefficient.

  3. Risk Measure and Early-Warning System of China's Stock Market Based on Price-Earnings Ratio and Price-to-Book Ratio

    Directory of Open Access Journals (Sweden)

    Rongda Chen

    2014-01-01

    Full Text Available Based on the actual situation of China's stock market, this paper proposes a method for measuring the stock market's risk and early-warning methods which are based on price-to-earnings ratio and price-to-book ratio. The study found that the method of VaR can capture the bigger daily drops in a period, and if the drop is at the periodical top of the index, the probability of a sharp index decline will be very high. It also confirmed that the method is feasible and practical for people to use. In the long run, this method really can send early-warning signals of sharp decline; the warning levels increase as the index rises. The study also found that index will not fall after every warning but will continue going forward because of inertia, particularly during a big trend.

  4. A framework for cost-based pricing of transmission and ancillary services in competitive electric power markets

    International Nuclear Information System (INIS)

    Zobian, A.; Ilic, M.D.

    1995-01-01

    In this paper the authors propose a framework for accurate cost determination and pricing of transmission and ancillary services in competitive electric power markets. The proposed framework is based on their anticipation of the evolving environment and industry structure. They envision the future as a competitive energy market with a centralized control entity that coordinates system activities, prices transmission and ancillary services and controls various system resources. This control entity has control over a certain (pre-defined) geographical area. It is proposed that the system operation and control be kept as they are currently done in control centers, no major change in these functions is required for the proposed pricing strategy. The pricing strategy is divided into two main classes based on time scale separation and firmness, short and long term, firm and interruptible contracts. The approach is based on superposition of different transaction on the network, and a three-part tariff design. The charges are directly related to the impact of each transaction on the system

  5. Schedule-Aware Workflow Management Systems

    Science.gov (United States)

    Mans, Ronny S.; Russell, Nick C.; van der Aalst, Wil M. P.; Moleman, Arnold J.; Bakker, Piet J. M.

    Contemporary workflow management systems offer work-items to users through specific work-lists. Users select the work-items they will perform without having a specific schedule in mind. However, in many environments work needs to be scheduled and performed at particular times. For example, in hospitals many work-items are linked to appointments, e.g., a doctor cannot perform surgery without reserving an operating theater and making sure that the patient is present. One of the problems when applying workflow technology in such domains is the lack of calendar-based scheduling support. In this paper, we present an approach that supports the seamless integration of unscheduled (flow) and scheduled (schedule) tasks. Using CPN Tools we have developed a specification and simulation model for schedule-aware workflow management systems. Based on this a system has been realized that uses YAWL, Microsoft Exchange Server 2007, Outlook, and a dedicated scheduling service. The approach is illustrated using a real-life case study at the AMC hospital in the Netherlands. In addition, we elaborate on the experiences obtained when developing and implementing a system of this scale using formal techniques.

  6. CMS multicore scheduling strategy

    International Nuclear Information System (INIS)

    Yzquierdo, Antonio Pérez-Calero; Hernández, Jose; Holzman, Burt; Majewski, Krista; McCrea, Alison

    2014-01-01

    In the next years, processor architectures based on much larger numbers of cores will be most likely the model to continue 'Moore's Law' style throughput gains. This not only results in many more jobs in parallel running the LHC Run 1 era monolithic applications, but also the memory requirements of these processes push the workernode architectures to the limit. One solution is parallelizing the application itself, through forking and memory sharing or through threaded frameworks. CMS is following all of these approaches and has a comprehensive strategy to schedule multicore jobs on the GRID based on the glideinWMS submission infrastructure. The main component of the scheduling strategy, a pilot-based model with dynamic partitioning of resources that allows the transition to multicore or whole-node scheduling without disallowing the use of single-core jobs, is described. This contribution also presents the experiences made with the proposed multicore scheduling schema and gives an outlook of further developments working towards the restart of the LHC in 2015.

  7. The Potential Cost Effectiveness of Different Dengue Vaccination Programmes in Malaysia: A Value-Based Pricing Assessment Using Dynamic Transmission Mathematical Modelling.

    Science.gov (United States)

    Shafie, Asrul Akmal; Yeo, Hui Yee; Coudeville, Laurent; Steinberg, Lucas; Gill, Balvinder Singh; Jahis, Rohani; Amar-Singh Hss

    2017-05-01

    Dengue disease poses a great economic burden in Malaysia. This study evaluated the cost effectiveness and impact of dengue vaccination in Malaysia from both provider and societal perspectives using a dynamic transmission mathematical model. The model incorporated sensitivity analyses, Malaysia-specific data, evidence from recent phase III studies and pooled efficacy and long-term safety data to refine the estimates from previous published studies. Unit costs were valued in $US, year 2013 values. Six vaccination programmes employing a three-dose schedule were identified as the most likely programmes to be implemented. In all programmes, vaccination produced positive benefits expressed as reductions in dengue cases, dengue-related deaths, life-years lost, disability-adjusted life-years and dengue treatment costs. Instead of incremental cost-effectiveness ratios (ICERs), we evaluated the cost effectiveness of the programmes by calculating the threshold prices for a highly cost-effective strategy [ICER price of $US32.39 for programme 6 (highly cost effective up to $US14.15) and up to a price of $US100.59 for programme 1 (highly cost effective up to $US47.96) from the provider perspective. The cost-effectiveness analysis is sensitive to under-reporting, vaccine protection duration and model time horizon. Routine vaccination for a population aged 13 years with a catch-up cohort aged 14-30 years in targeted hotspot areas appears to be the best-value strategy among those investigated. Dengue vaccination is a potentially good investment if the purchaser can negotiate a price at or below the cost-effective threshold price.

  8. Reference-based transitions in short-run price elasticity

    NARCIS (Netherlands)

    K.H. Pauwels (Koen); Ph.H.B.F. Franses (Philip Hans); S. Srinivasan (Shuba)

    2003-01-01

    textabstractMarketing literature has long recognized that price response need not be monotonic and symmetric, but has yet to provide generalizable market-level insights on reference price type, asymmetric thresholds and sign and magnitude of elasticity transitions. In this paper, we introduce smooth

  9. Method of determining the efficiency of price and non-price competition in service sector

    Directory of Open Access Journals (Sweden)

    Savel’eva Nadezhda

    2017-01-01

    Full Text Available With the end of 2014, the domestic banking system has serious difficulties with the availability of capital for lending and investment programs. Problems based on international political divisions, and their resolution lies in the distant future. in these circumstances, the government is concerned about the development of the Russian banking system in terms of ensuring their competitiveness in the international arena. foreign capital has always been a cheap resource for the domestic banking system, the problem area remains its state at the time of lifting of sanctions. Nowadays banks are forced to use different competition methods in target to adapt to environmental changes and ensure competitive success. So the development of methods for price and non-price competition has economic importance. Analysis of qualitative methodological foundations in banks service revealed strong background. Based on neoteric qualitative evaluation methodology, authors developed method for price and non-price competitiveness. It defines variables of price and non-price competitiveness, to set the value factors, to identify the closest competitors, and to set the position of a particular bank among other participants. It also helps to shape competitors dossier based on the evaluated score.

  10. Null Space Based Preemptive Scheduling For Joint URLLC and eMBB Traffic in 5G Networks

    DEFF Research Database (Denmark)

    Abdul-Mawgood Ali Ali Esswie, Ali; Pedersen, Klaus

    2018-01-01

    In this paper, we propose a null-space-based preemptive scheduling framework for cross-objective optimization to always guarantee robust URLLC performance, while extracting the maximum possible eMBB capacity. The proposed scheduler perpetually grants incoming URLLC traffic a higher priority for i...

  11. Range Scheduling Aid (RSA)

    Science.gov (United States)

    Logan, J. R.; Pulvermacher, M. K.

    1991-01-01

    Range Scheduling Aid (RSA) is presented in the form of the viewgraphs. The following subject areas are covered: satellite control network; current and new approaches to range scheduling; MITRE tasking; RSA features; RSA display; constraint based analytic capability; RSA architecture; and RSA benefits.

  12. Distribution Locational Marginal Pricing for Optimal Electric Vehicle Charging Management

    DEFF Research Database (Denmark)

    Li, Ruoyang; Wu, Qiuwei; Oren, Shmuel S.

    2013-01-01

    This paper presents an integrated distribution locational marginal pricing (DLMP) method designed to alleviate congestion induced by electric vehicle (EV) loads in future power systems. In the proposed approach, the distribution system operator (DSO) determines distribution locational marginal...... shown that the socially optimal charging schedule can be implemented through a decentralized mechanism where loads respond autonomously to the posted DLMPs by maximizing their individual net surplus...

  13. Comparing The Effects Of Reference Pricing And Centers-Of-Excellence Approaches To Value-Based Benefit Design.

    Science.gov (United States)

    Zhang, Hui; Cowling, David W; Facer, Matthew

    2017-12-01

    Various health insurance benefit designs based on value-based purchasing have been promoted to steer patients to high-value providers, but little is known about the designs' relative effectiveness and underlying mechanisms. We compared the impact of two designs implemented by the California Public Employees' Retirement System on inpatient hospital total hip or knee replacement: a reference-based pricing design for preferred provider organizations (PPOs) and a centers-of-excellence design for health maintenance organizations (HMOs). Payment and utilization data for the procedures in the period 2008-13 were evaluated using pre-post and quasi-experimental designs at the system and health plan levels, adjusting for demographic characteristics, case-mix, and other confounders. We found that both designs prompted higher use of designated low-price high-quality facilities and reduced average replacement expenses per member at the plan and system levels. However, the designs used different routes: The reference-based pricing design reduced average replacement payments per case in PPOs by 26.7 percent in the first year, compared to HMOs, but did not lower PPO members' utilization rates. In contrast, the centers-of-excellence design lowered HMO members' utilization rates by 29.2 percent in the first year, compared to PPOs, but did not reduce HMO average replacement payments per case. The reference-based pricing design appears more suitable for reducing price variation, and the centers-of-excellence design for addressing variation in use.

  14. A Case Study of Pharmaceutical Pricing in China: Setting the Price for Off-Patent Originators.

    Science.gov (United States)

    Hu, Shanlian; Zhang, Yabing; He, Jiangjiang; Du, Lixia; Xu, Mingfei; Xie, Chunyan; Peng, Ying; Wang, Linan

    2015-08-01

    This article aims to define a value-based approach to pricing and reimbursement for off-patent originators using a multiple criteria decision analysis (MCDA) approach centered on a systematic analysis of current pricing and reimbursement policies in China. A drug price policy review was combined with a quantitative analysis of China's drug purchasing database. Policy preferences were identified through a MCDA performed by interviewing well-known academic experts and industry stakeholders. The study findings indicate that the current Chinese price policy includes cost-based pricing and the establishment of maximum retail prices and premiums for off-patent originators, whereas reference pricing may be adopted in the future. The literature review revealed significant differences in the dissolution profiles between originators and generics; therefore, dissolution profiles need to be improved. Market data analysis showed that the overall price ratio of generics and off-patent originators was around 0.54-0.59 in 2002-2011, with a 40% price difference, on average. Ten differentiating value attributes were identified and MCDA was applied to test the impact of three pricing policy scenarios. With the condition of implementing quality consistency regulations and controls, a reduction in the price gap between high-quality off-patent products (including originator and generics) seemed to be the preferred policy. Patents of many drugs will expire within the next 10 years; thus, pricing will be an issue of importance for off-patent originators and generic alternatives.

  15. The Pricing of natural gas

    International Nuclear Information System (INIS)

    Nese, Gjermund

    2004-11-01

    The report focuses on the pricing of natural gas. The motivation has been the wish of the Norwegian authorities to increase the use of natural gas and that this should follow market conditions. The pricing of gas occurs at present in various ways in the different markets. The report identifies to main factors behind the pricing. 1) The type of market i.e. how far the liberalization of the gas markets has gone in the various countries. 2) The development within the regulation, climate and tax policies. The gas markets are undergoing as the energy markets in general, a liberalization process where the traditional monopoly based market structures are replaced by markets based on competition. There are great differences in the liberalization development of the various countries, which is reflected in the various pricing principles applied for the trade of gas in the countries. The analysis shows that the net-back-pricing is predominant in some countries i.e. that the price is in various ways indexed towards and follow the development of the price of alternative energy carriers so that the gas may be able to compete. The development towards trade places for gas where the pricing is based on offer and demand is already underway. As the liberalization of the European gas markets progresses it is expected that the gas price will be determined increasingly at spot markets instead of through bilateral agreements between monopolistic corporations. The development within the regulation, climate and tax policies and to what extent this may influence the gas prices in the future, are also studied. There seem to be effects that may pull in both directions but it is evident that these political variables will influence the gas pricing in the international market to a large extent and thereby also the future internal natural gas market

  16. A uniform price auction with locational price adjustments for competitive electricity markets

    International Nuclear Information System (INIS)

    Ethier, R.; Mount, T.; Schulze, W.; Zimmerman, R.; Thomas, R.

    1999-01-01

    Competitive electricity markets which rely on centralized dispatch require a mechanism to solicit offers from competing generators. Ideally, such an auction mechanism, provides incentives to submit offers equal to the marginal cost of generation for each generator. Economic theory suggests that the Uniform Price auction is an appropriate institution. However, an efficient implementation of this auction in an electricity context requires that the offers used in the auction reflect the appropriate locational price adjustments for transmission losses and congestion. This paper describes a uniform price auction that incorporates locational price adjustments on a Web-based platform suitable for experimentation. Preliminary results show dramatically different price and revenue results when compared with a simple continuous Discriminative auction. (author)

  17. Optimal stochastic scheduling of CHP-PEMFC, WT, PV units and hydrogen storage in reconfigurable micro grids considering reliability enhancement

    International Nuclear Information System (INIS)

    Bornapour, Mosayeb; Hooshmand, Rahmat-Allah; Khodabakhshian, Amin; Parastegari, Moein

    2017-01-01

    Highlights: • Stochastic model is proposed for coordinated scheduling of renewable energy sources. • The effect of combined heat and power is considered. • Uncertainties of wind speed, solar radiation and electricity market price are considered. • Profit maximization, emission and AENS minimization are considered as objective functions. • Modified firefly algorithm is employed to solve the problem. - Abstract: Nowadays the operation of renewable energy sources and combined heat and power (CHP) units is increased in micro grids; therefore, to reach optimal performance, optimal scheduling of these units is required. In this regard, in this paper a micro grid consisting of proton exchange membrane fuel cell-combined heat and power (PEMFC-CHP), wind turbines (WT) and photovoltaic (PV) units, is modeled to determine the optimal scheduling state of these units by considering uncertain behavior of renewable energy resources. For this purpose, a scenario-based method is used for modeling the uncertainties of electrical market price, the wind speed, and solar irradiance. It should be noted that the hydrogen storage strategy is also applied in this study for PEMFC-CHP units. Market profit, total emission production, and average energy not supplied (AENS) are the objective functions considered in this paper simultaneously. Consideration of the above-mentioned objective functions converts the proposed problem to a mixed integer nonlinear programming. To solve this problem, a multi-objective firefly algorithm is used. The uncertainties of parameters convert the mixed integer nonlinear programming problem to a stochastic mixed integer nonlinear programming problem. Moreover, optimal coordinated scheduling of renewable energy resources and thermal units in micro-grids improve the value of the objective functions. Simulation results obtained from a modified 33-bus distributed network as a micro grid illustrates the effectiveness of the proposed method.

  18. A new intuitionistic fuzzy rule-based decision-making system for an operating system process scheduler.

    Science.gov (United States)

    Butt, Muhammad Arif; Akram, Muhammad

    2016-01-01

    We present a new intuitionistic fuzzy rule-based decision-making system based on intuitionistic fuzzy sets for a process scheduler of a batch operating system. Our proposed intuitionistic fuzzy scheduling algorithm, inputs the nice value and burst time of all available processes in the ready queue, intuitionistically fuzzify the input values, triggers appropriate rules of our intuitionistic fuzzy inference engine and finally calculates the dynamic priority (dp) of all the processes in the ready queue. Once the dp of every process is calculated the ready queue is sorted in decreasing order of dp of every process. The process with maximum dp value is sent to the central processing unit for execution. Finally, we show complete working of our algorithm on two different data sets and give comparisons with some standard non-preemptive process schedulers.

  19. Dynamic Relation Mechanism between Cotton Future Price and Stock Price of Related Listed Companies

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    The Dynamic relation mechanism between ZCE cotton futures price and related listed company stock price has been studied based on the metastock historical data in January 1st,2007 to September 1st,2010,Johansen co-integration analysis,Vector error correction model,Granger causality test and variance decomposition method.The results indicated that:long-term equilibrium relationship existed between ZCE cotton futures price and Xinsai share stock price while which changed in the same tendency and speed in the long-term.Cotton futures price is the main reason for the changing of Xinsai share stock price.The lead-lag relationship in changing course had been confirmed that existed between ZCE cotton futures price and the Xinsai share stock price.Meanwhile,the forward pass mechanism of price changing information had been found only from the ZCE cotton futures market to the stock market while showing asymmetry.Conclusions of the study can be used for cotton and related corporate to hedge business risks by the cotton price changes.

  20. Word of Mouth : An Agent-based Approach to Predictability of Stock Prices

    Science.gov (United States)

    Shimokawa, Tetsuya; Misawa, Tadanobu; Watanabe, Kyoko

    This paper addresses how communication processes among investors affect stock prices formation, especially emerging predictability of stock prices, in financial markets. An agent based model, called the word of mouth model, is introduced for analyzing the problem. This model provides a simple, but sufficiently versatile, description of informational diffusion process and is successful in making lucidly explanation for the predictability of small sized stocks, which is a stylized fact in financial markets but difficult to resolve by traditional models. Our model also provides a rigorous examination of the under reaction hypothesis to informational shocks.

  1. The Optimal Price Ratio of Typical Energy Sources in Beijing Based on the Computable General Equilibrium Model

    Directory of Open Access Journals (Sweden)

    Yongxiu He

    2014-04-01

    Full Text Available In Beijing, China, the rational consumption of energy is affected by the insufficient linkage mechanism of the energy pricing system, the unreasonable price ratio and other issues. This paper combines the characteristics of Beijing’s energy market, putting forward the society-economy equilibrium indicator R maximization taking into consideration the mitigation cost to determine a reasonable price ratio range. Based on the computable general equilibrium (CGE model, and dividing four kinds of energy sources into three groups, the impact of price fluctuations of electricity and natural gas on the Gross Domestic Product (GDP, Consumer Price Index (CPI, energy consumption and CO2 and SO2 emissions can be simulated for various scenarios. On this basis, the integrated effects of electricity and natural gas price shocks on the Beijing economy and environment can be calculated. The results show that relative to the coal prices, the electricity and natural gas prices in Beijing are currently below reasonable levels; the solution to these unreasonable energy price ratios should begin by improving the energy pricing mechanism, through means such as the establishment of a sound dynamic adjustment mechanism between regulated prices and market prices. This provides a new idea for exploring the rationality of energy price ratios in imperfect competitive energy markets.

  2. 75 FR 2723 - Fair Credit Reporting Risk-Based Pricing Regulations

    Science.gov (United States)

    2010-01-15

    ...-based pricing notice to a consumer when the creditor uses a consumer report to grant or extend credit to... consumers to combat identity theft, increase the accuracy of consumer reports, and allow consumers to... consumer report is often used in evaluating the risk posed by the consumer. Creditors that engage in risk...

  3. Port pricing : principles, structure and models

    OpenAIRE

    Meersman, Hilde; Strandenes, Siri Pettersen; Van de Voorde, Eddy

    2014-01-01

    Price level and price transparency are input to shippers’ choice of supply chain and transport mode. In this paper, we analyse current port pricing structures in the light of the pricing literature and consider opportunities for improvement. We present a detailed overview of pricing criteria, who sets prices and who ultimately foots the bill for port-of-call charges, cargo-handling fees and congestion charges. Current port pricing practice is based on a rather linear structure and fails to in...

  4. A decentralized scheduling algorithm for time synchronized channel hopping

    Directory of Open Access Journals (Sweden)

    Andrew Tinka

    2011-09-01

    Full Text Available Time Synchronized Channel Hopping (TSCH is an existing Medium Access Control scheme which enables robust communication through channel hopping and high data rates through synchronization. It is based on a time-slotted architecture, and its correct functioning depends on a schedule which is typically computed by a central node. This paper presents, to our knowledge, the first scheduling algorithm for TSCH networks which both is distributed and which copes with mobile nodes. Two variations on scheduling algorithms are presented. Aloha-based scheduling allocates one channel for broadcasting advertisements for new neighbors. Reservation- based scheduling augments Aloha-based scheduling with a dedicated timeslot for targeted advertisements based on gossip information. A mobile ad hoc motorized sensor network with frequent connectivity changes is studied, and the performance of the two proposed algorithms is assessed. This performance analysis uses both simulation results and the results of a field deployment of floating wireless sensors in an estuarial canal environment. Reservation-based scheduling performs significantly better than Aloha-based scheduling, suggesting that the improved network reactivity is worth the increased algorithmic complexity and resource consumption.

  5. Strategic Generation with Conjectured Transmission Price Responses in a Mixed Transmission Pricing System. Part 1. Formulation

    International Nuclear Information System (INIS)

    Hobbs, B.F.; Rijkers, F.A.M.

    2004-05-01

    The conjectured supply function (CSF) model calculates an oligopolistic equilibrium among competing generating companies (GenCos), presuming that GenCos anticipate that rival firms will react to price increases by expanding their sales at an assumed rate. The CSF model is generalized here to include each generator's conjectures concerning how the price of transmission services (point-to-point service and constrained interfaces) will be affected by the amount of those services that the generator demands. This generalization reflects the market reality that large producers will anticipate that they can favorably affect transmission prices by their actions. The model simulates oligopolistic competition among generators while simultaneously representing a mixed transmission pricing system. This mixed system includes fixed transmission tariffs, congestion-based pricing of physical transmission constraints (represented as a linearized dc load flow), and auctions of interface capacity in a path-based pricing system. Pricing inefficiencies, such as export fees and no credit for counterflows, can be simulated. The model is formulated as a linear mixed complementarity problem, which enables very large market models to be solved. In the second paper of this two-paper series, the capabilities of the model are illustrated with an application to northwest Europe, where transmission pricing is based on such a mixture of approaches

  6. Optimization of a Future RLV Business Case using Multiple Strategic Market Prices

    Science.gov (United States)

    Charania, A.; Olds, J. R.

    2002-01-01

    There is a lack of depth in the current paradigm of conceptual level economic models used to evaluate the value and viability of future capital projects such as a commercial reusable launch vehicle (RLV). Current modeling methods assume a single price is charged to all customers, public or private, in order to optimize the economic metrics of interest. This assumption may not be valid given the different utility functions for space services of public and private entities. The government's requirements are generally more inflexible than its commercial counterparts. A government's launch schedules are much more rigid, choices of international launch services restricted, and launch specifications generally more stringent as well as numerous. These requirements generally make the government's demand curve more inelastic. Subsequently, a launch vehicle provider will charge a higher price (launch price per kg) to the government and may obtain a higher level of financial profit compared to an equivalent a commercial payload. This profit is not a sufficient condition to enable RLV development by itself but can help in making the financial situation slightly better. An RLV can potentially address multiple payload markets; each market has a different price elasticity of demand for both the commercial and government customer. Thus, a more resilient examination of the economic landscape requires optimization of multiple prices in which each price affects a different demand curve. Such an examination is performed here using the Cost and Business Analysis Module (CABAM), an MS-Excel spreadsheet-based model that attempts to couple both the demand and supply for space transportation services in the future. The demand takes the form of market assumptions (both near-term and far-term) and the supply comes from user-defined vehicles that are placed into the model. CABAM represents RLV projects as commercial endeavors with the possibility to model the effects of government

  7. Research on choices of methods of internet of things pricing based on variation of perceived value of service

    Directory of Open Access Journals (Sweden)

    Wei Li

    2013-03-01

    Full Text Available Purpose: With the rapid progress of Internet of Things technology, the information service of IoT has got unprecedented development, and plays an increasingly important role in real life. For the increasing demand of information service, the pricing of information service becomes more important. This paper aims to analyze the strategic options and payoff function between information provider and intermediaries based on Stackelberg game. Firstly, we describe information service delivery method based on the Internet of Things specific function. Secondly, we calculate the consumer demand for the information service. Finally, we explain two kinds of strategic options by the game theory, and then discuss the optimal pricing method of information services based on profit maximization.Design/methodology/approach: To achieve this objective, Considering the consumer perceived value of Internet of Things Service changing, we establish a Stackelberg model in which the supplier is the leader followed by the middleman. Then, we compare the advantages of using individual pricing with that of bundling pricing.Findings: The results show that whether information providers adopt bundling pricing strategy or individual pricing strategy depends on the cost of perception equipment, if information providers want to adopt individual pricing strategy, the variation of consumers’ perception value of information services must meet certain conditions.Research limitations/implications: the providers make price for the information service, in addition to continuously improve the quality of information service, it also devotes resources to tapping and understanding market information, such as the sensor device price, the variation of perception value of information services and so on, so as to create competitive advantage. This paper is just a preliminary model, it does not take into account the effect of mixed bundling.Originality/value: In this research, a new model for

  8. Integrated approach to transmission services pricing

    International Nuclear Information System (INIS)

    Yu, C.W.; David, A.K.

    1999-01-01

    The paper presents an intuitively logical split between: (a) embedded, (b) operating, and (c) expansion cost based pricing and methodologies for implementation, for transmission services. A conceptually straightforward mechanism for the equitable allocation of transmission network embedded cost recovery based on capacity-use and reliability benefit is proposed, expansion cost is charged on a long-run marginal cost basis and finally, operating cost recovery is based on short-run marginal pricing. This is followed by co-ordinating these alternatives and integrating the pricing mechanisms to achieve appropriate price signals for bulk power users of transmission systems. (author)

  9. An On-Time Power-Aware Scheduling Scheme for Medical Sensor SoC-Based WBAN Systems

    Science.gov (United States)

    Hwang, Tae-Ho; Kim, Dong-Sun; Kim, Jung-Guk

    2013-01-01

    The focus of many leading technologies in the field of medical sensor systems is on low power consumption and robust data transmission. For example, the implantable cardioverter-defibrillator (ICD), which is used to maintain the heart in a healthy state, requires a reliable wireless communication scheme with an extremely low duty-cycle, high bit rate, and energy-efficient media access protocols. Because such devices must be sustained for over 5 years without access to battery replacement, they must be designed to have extremely low power consumption in sleep mode. Here, an on-time, energy-efficient scheduling scheme is proposed that performs power adjustments to minimize the sleep-mode current. The novelty of this scheduler is that it increases the determinacy of power adjustment and the predictability of scheduling by employing non-pre-emptible dual priority scheduling. This predictable scheduling also guarantees the punctuality of important periodic tasks based on their serialization, by using their worst case execution time) and the power consumption optimization. The scheduler was embedded into a system on chip (SoC) developed to support the wireless body area network—a wakeup-radio and wakeup-timer for implantable medical devices. This scheduling system is validated by the experimental results of its performance when used with life-time extensions of ICD devices. PMID:23271602

  10. An on-time power-aware scheduling scheme for medical sensor SoC-based WBAN systems.

    Science.gov (United States)

    Hwang, Tae-Ho; Kim, Dong-Sun; Kim, Jung-Guk

    2012-12-27

    The focus of many leading technologies in the field of medical sensor systems is on low power consumption and robust data transmission. For example, the implantable cardioverter-defibrillator (ICD), which is used to maintain the heart in a healthy state, requires a reliable wireless communication scheme with an extremely low duty-cycle, high bit rate, and energy-efficient media access protocols. Because such devices must be sustained for over 5 years without access to battery replacement, they must be designed to have extremely low power consumption in sleep mode. Here, an on-time, energy-efficient scheduling scheme is proposed that performs power adjustments to minimize the sleep-mode current. The novelty of this scheduler is that it increases the determinacy of power adjustment and the predictability of scheduling by employing non-pre-emptible dual priority scheduling. This predictable scheduling also guarantees the punctuality of important periodic tasks based on their serialization, by using their worst case execution time) and the power consumption optimization. The scheduler was embedded into a system on chip (SoC) developed to support the wireless body area network-a wakeup-radio and wakeup-timer for implantable medical devices. This scheduling system is validated by the experimental results of its performance when used with life-time extensions of ICD devices.

  11. An improved quantum-behaved particle swarm optimization method for short-term combined economic emission hydrothermal scheduling

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Songfeng; Sun, Chengfu; Lu, Zhengding [School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074 (China)

    2010-03-15

    This paper presents a modified quantum-behaved particle swarm optimization (QPSO) for short-term combined economic emission scheduling (CEES) of hydrothermal power systems with several equality and inequality constraints. The hydrothermal scheduling is formulated as a bi-objective problem: (i) minimizing fuel cost and (ii) minimizing pollutant emission. The bi-objective problem is converted into a single objective one by price penalty factor. The proposed method, denoted as QPSO-DM, combines the QPSO algorithm with differential mutation operation to enhance the global search ability. In this study, heuristic strategies are proposed to handle the equality constraints especially water dynamic balance constraints and active power balance constraints. A feasibility-based selection technique is also employed to meet the reservoir storage volumes constraints. To show the efficiency of the proposed method, different case studies are carried out and QPSO-DM is compared with the differential evolution (DE), the particle swarm optimization (PSO) with same heuristic strategies in terms of the solution quality, robustness and convergence property. The simulation results show that the proposed method is capable of yielding higher-quality solutions stably and efficiently in the short-term hydrothermal scheduling than any other tested optimization algorithms. (author)

  12. An improved quantum-behaved particle swarm optimization method for short-term combined economic emission hydrothermal scheduling

    Energy Technology Data Exchange (ETDEWEB)

    Lu Songfeng [School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074 (China); Sun Chengfu, E-mail: ajason_369@sina.co [School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074 (China); Lu Zhengding [School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074 (China)

    2010-03-15

    This paper presents a modified quantum-behaved particle swarm optimization (QPSO) for short-term combined economic emission scheduling (CEES) of hydrothermal power systems with several equality and inequality constraints. The hydrothermal scheduling is formulated as a bi-objective problem: (i) minimizing fuel cost and (ii) minimizing pollutant emission. The bi-objective problem is converted into a single objective one by price penalty factor. The proposed method, denoted as QPSO-DM, combines the QPSO algorithm with differential mutation operation to enhance the global search ability. In this study, heuristic strategies are proposed to handle the equality constraints especially water dynamic balance constraints and active power balance constraints. A feasibility-based selection technique is also employed to meet the reservoir storage volumes constraints. To show the efficiency of the proposed method, different case studies are carried out and QPSO-DM is compared with the differential evolution (DE), the particle swarm optimization (PSO) with same heuristic strategies in terms of the solution quality, robustness and convergence property. The simulation results show that the proposed method is capable of yielding higher-quality solutions stably and efficiently in the short-term hydrothermal scheduling than any other tested optimization algorithms.

  13. An improved quantum-behaved particle swarm optimization method for short-term combined economic emission hydrothermal scheduling

    International Nuclear Information System (INIS)

    Lu Songfeng; Sun Chengfu; Lu Zhengding

    2010-01-01

    This paper presents a modified quantum-behaved particle swarm optimization (QPSO) for short-term combined economic emission scheduling (CEES) of hydrothermal power systems with several equality and inequality constraints. The hydrothermal scheduling is formulated as a bi-objective problem: (i) minimizing fuel cost and (ii) minimizing pollutant emission. The bi-objective problem is converted into a single objective one by price penalty factor. The proposed method, denoted as QPSO-DM, combines the QPSO algorithm with differential mutation operation to enhance the global search ability. In this study, heuristic strategies are proposed to handle the equality constraints especially water dynamic balance constraints and active power balance constraints. A feasibility-based selection technique is also employed to meet the reservoir storage volumes constraints. To show the efficiency of the proposed method, different case studies are carried out and QPSO-DM is compared with the differential evolution (DE), the particle swarm optimization (PSO) with same heuristic strategies in terms of the solution quality, robustness and convergence property. The simulation results show that the proposed method is capable of yielding higher-quality solutions stably and efficiently in the short-term hydrothermal scheduling than any other tested optimization algorithms.

  14. A priority-based heuristic algorithm (PBHA for optimizing integrated process planning and scheduling problem

    Directory of Open Access Journals (Sweden)

    Muhammad Farhan Ausaf

    2015-12-01

    Full Text Available Process planning and scheduling are two important components of a manufacturing setup. It is important to integrate them to achieve better global optimality and improved system performance. To find optimal solutions for integrated process planning and scheduling (IPPS problem, numerous algorithm-based approaches exist. Most of these approaches try to use existing meta-heuristic algorithms for solving the IPPS problem. Although these approaches have been shown to be effective in optimizing the IPPS problem, there is still room for improvement in terms of quality of solution and algorithm efficiency, especially for more complicated problems. Dispatching rules have been successfully utilized for solving complicated scheduling problems, but haven’t been considered extensively for the IPPS problem. This approach incorporates dispatching rules with the concept of prioritizing jobs, in an algorithm called priority-based heuristic algorithm (PBHA. PBHA tries to establish job and machine priority for selecting operations. Priority assignment and a set of dispatching rules are simultaneously used to generate both the process plans and schedules for all jobs and machines. The algorithm was tested for a series of benchmark problems. The proposed algorithm was able to achieve superior results for most complex problems presented in recent literature while utilizing lesser computational resources.

  15. Multiuser switched diversity scheduling schemes

    KAUST Repository

    Shaqfeh, Mohammad; Alnuweiri, Hussein M.; Alouini, Mohamed-Slim

    2012-01-01

    Multiuser switched-diversity scheduling schemes were recently proposed in order to overcome the heavy feedback requirements of conventional opportunistic scheduling schemes by applying a threshold-based, distributed, and ordered scheduling mechanism. The main idea behind these schemes is that slight reduction in the prospected multiuser diversity gains is an acceptable trade-off for great savings in terms of required channel-state-information feedback messages. In this work, we characterize the achievable rate region of multiuser switched diversity systems and compare it with the rate region of full feedback multiuser diversity systems. We propose also a novel proportional fair multiuser switched-based scheduling scheme and we demonstrate that it can be optimized using a practical and distributed method to obtain the feedback thresholds. We finally demonstrate by numerical examples that switched-diversity scheduling schemes operate within 0.3 bits/sec/Hz from the ultimate network capacity of full feedback systems in Rayleigh fading conditions. © 2012 IEEE.

  16. Multiuser switched diversity scheduling schemes

    KAUST Repository

    Shaqfeh, Mohammad

    2012-09-01

    Multiuser switched-diversity scheduling schemes were recently proposed in order to overcome the heavy feedback requirements of conventional opportunistic scheduling schemes by applying a threshold-based, distributed, and ordered scheduling mechanism. The main idea behind these schemes is that slight reduction in the prospected multiuser diversity gains is an acceptable trade-off for great savings in terms of required channel-state-information feedback messages. In this work, we characterize the achievable rate region of multiuser switched diversity systems and compare it with the rate region of full feedback multiuser diversity systems. We propose also a novel proportional fair multiuser switched-based scheduling scheme and we demonstrate that it can be optimized using a practical and distributed method to obtain the feedback thresholds. We finally demonstrate by numerical examples that switched-diversity scheduling schemes operate within 0.3 bits/sec/Hz from the ultimate network capacity of full feedback systems in Rayleigh fading conditions. © 2012 IEEE.

  17. Price control and macromarketing

    Directory of Open Access Journals (Sweden)

    Kancir Rade

    2003-01-01

    Full Text Available Price control at macro level is part of integral macro marketing strategic control system, or more precisely, part of social marketing mix control. Price impact is direct, if it is regarded in the context of needs satisfaction, and indirect, within the context of resource allocation. These two patterns of price impact define control mechanism structuring. Price control in sense of its direct impact at process of need satisfaction should comprise qualitative and quantitative level of needs satisfaction at a given price level and its structure, informational dimension of price and different disputable forms of corporate pricing policies. Control of price allocation function is based at objectives of macro marketing system management in the area of resource allocation and the role of price as allocator in contemporary market economies. Control process is founded, on one hand, at theoretical models of correlation between price and demand in different market structures, and on the other hand, at complex limits that price as allocator has, and which make whole control process even more complex because of reduction of the degree of determinism in functioning of contemporary economic systems. Control of price allocation function must be continuous and dynamic process if it is to provide for convergence with environmental changes and if it is to provide for placing control systems at micro marketing levels in the function of socially valid objectives.

  18. Fog computing job scheduling optimization based on bees swarm

    Science.gov (United States)

    Bitam, Salim; Zeadally, Sherali; Mellouk, Abdelhamid

    2018-04-01

    Fog computing is a new computing architecture, composed of a set of near-user edge devices called fog nodes, which collaborate together in order to perform computational services such as running applications, storing an important amount of data, and transmitting messages. Fog computing extends cloud computing by deploying digital resources at the premise of mobile users. In this new paradigm, management and operating functions, such as job scheduling aim at providing high-performance, cost-effective services requested by mobile users and executed by fog nodes. We propose a new bio-inspired optimization approach called Bees Life Algorithm (BLA) aimed at addressing the job scheduling problem in the fog computing environment. Our proposed approach is based on the optimized distribution of a set of tasks among all the fog computing nodes. The objective is to find an optimal tradeoff between CPU execution time and allocated memory required by fog computing services established by mobile users. Our empirical performance evaluation results demonstrate that the proposal outperforms the traditional particle swarm optimization and genetic algorithm in terms of CPU execution time and allocated memory.

  19. Pricing Strategy, Pricing Stability and Financial Condition in the Defense Aerospace Industry

    OpenAIRE

    Johnstone, Jeffrey Carl; Keavney, Patrick Daniel

    1987-01-01

    Approved for public release, distribution unlimited The purpose of this research is to determine if pricing strategy and pricing stability for products in the defense aerospace industry can be predicted based on a firm's financial condition. The sample for this research includes 17 contractors and 52 missile and aircraft programs. Two separate issues are addressed. The first issue concerns the relationship between financial condition and contractor pricing strategy. The second concerns the...

  20. Food Prices and Climate Extremes: A Model of Global Grain Price Variability with Storage

    Science.gov (United States)

    Otto, C.; Schewe, J.; Frieler, K.

    2015-12-01

    Extreme climate events such as droughts, floods, or heat waves affect agricultural production in major cropping regions and therefore impact the world market prices of staple crops. In the last decade, crop prices exhibited two very prominent price peaks in 2007-2008 and 2010-2011, threatening food security especially for poorer countries that are net importers of grain. There is evidence that these spikes in grain prices were at least partly triggered by actual supply shortages and the expectation of bad harvests. However, the response of the market to supply shocks is nonlinear and depends on complex and interlinked processes such as warehousing, speculation, and trade policies. Quantifying the contributions of such different factors to short-term price variability remains difficult, not least because many existing models ignore the role of storage which becomes important on short timescales. This in turn impedes the assessment of future climate change impacts on food prices. Here, we present a simple model of annual world grain prices that integrates grain stocks into the supply and demand functions. This firstly allows us to model explicitly the effect of storage strategies on world market price, and thus, for the first time, to quantify the potential contribution of trade policies to price variability in a simple global framework. Driven only by reported production and by long--term demand trends of the past ca. 40 years, the model reproduces observed variations in both the global storage volume and price of wheat. We demonstrate how recent price peaks can be reproduced by accounting for documented changes in storage strategies and trade policies, contrasting and complementing previous explanations based on different mechanisms such as speculation. Secondly, we show how the integration of storage allows long-term projections of grain price variability under climate change, based on existing crop yield scenarios.

  1. Dynamic pricing based on a cloud computing framework to support the integration of renewable energy sources

    OpenAIRE

    Rajeev Thankappan Nair; Ashok Sankar

    2014-01-01

    Integration of renewable energy sources into the electric grid in the domestic sector results in bidirectional energy flow from the supply side of the consumer to the grid. Traditional pricing methods are difficult to implement in such a situation of bidirectional energy flow and they face operational challenges on the application of price-based demand side management programme because of the intermittent characteristics of renewable energy sources. In this study, a dynamic pricing method usi...

  2. Harnessing the private health sector by using prices as a policy instrument: Lessons learned from South Africa.

    Science.gov (United States)

    Barber, Sarah L; Kumar, Ankit; Roubal, Tomas; Colombo, Francesca; Lorenzoni, Luca

    2018-05-01

    Governments frequently draw upon the private health care sector to promote sustainability, optimal use of resources, and increased choice. In doing so, policy-makers face the challenge of harnessing resources while grappling with the market failures and equity concerns associated with private financing of health care. The growth of the private health sector in South Africa has fundamentally changed the structure of health care delivery. A mutually reinforcing ecosystem of private health insurers, private hospitals and specialists has grown to account for almost half of the country's spending on health care, despite only serving 16% of the population with the capacity to pay. Following years of consolidation among private hospital groups and insurance schemes, and after successive failures at establishing credible price benchmarks, South Africa's private hospitals charge prices comparable with countries that are considerably richer. This compromises the affordability of a broad-based expansion in health care for the population. The South African example demonstrates that prices can be part of a structure that perpetuates inequalities in access to health care resources. The lesson for other countries is the importance of norms and institutions that uphold price schedules in high-income countries. Efforts to compromise or liberalize price setting should be undertaken with a healthy degree of caution. Copyright © 2018 Elsevier B.V. All rights reserved.

  3. Valuing Trial Designs from a Pharmaceutical Perspective Using Value-Based Pricing.

    Science.gov (United States)

    Breeze, Penny; Brennan, Alan

    2015-11-01

    Our aim was to adapt the traditional framework for expected net benefit of sampling (ENBS) to be more compatible with drug development trials from the pharmaceutical perspective. We modify the traditional framework for conducting ENBS and assume that the price of the drug is conditional on the trial outcomes. We use a value-based pricing (VBP) criterion to determine price conditional on trial data using Bayesian updating of cost-effectiveness (CE) model parameters. We assume that there is a threshold price below which the company would not market the new intervention. We present a case study in which a phase III trial sample size and trial duration are varied. For each trial design, we sampled 10,000 trial outcomes and estimated VBP using a CE model. The expected commercial net benefit is calculated as the expected profits minus the trial costs. A clinical trial with shorter follow-up, and larger sample size, generated the greatest expected commercial net benefit. Increasing the duration of follow-up had a modest impact on profit forecasts. Expected net benefit of sampling can be adapted to value clinical trials in the pharmaceutical industry to optimise the expected commercial net benefit. However, the analyses can be very time consuming for complex CE models. © 2014 The Authors. Health Economics published by John Wiley & Sons Ltd.

  4. Hierarchical Scheduling Framework Based on Compositional Analysis Using Uppaal

    DEFF Research Database (Denmark)

    Boudjadar, Jalil; David, Alexandre; Kim, Jin Hyun

    2014-01-01

    This paper introduces a reconfigurable compositional scheduling framework, in which the hierarchical structure, the scheduling policies, the concrete task behavior and the shared resources can all be reconfigured. The behavior of each periodic preemptive task is given as a list of timed actions, ...

  5. Job shop scheduling problem with late work criterion

    Science.gov (United States)

    Piroozfard, Hamed; Wong, Kuan Yew

    2015-05-01

    Scheduling is considered as a key task in many industries, such as project based scheduling, crew scheduling, flight scheduling, machine scheduling, etc. In the machine scheduling area, the job shop scheduling problems are considered to be important and highly complex, in which they are characterized as NP-hard. The job shop scheduling problems with late work criterion and non-preemptive jobs are addressed in this paper. Late work criterion is a fairly new objective function. It is a qualitative measure and concerns with late parts of the jobs, unlike classical objective functions that are quantitative measures. In this work, simulated annealing was presented to solve the scheduling problem. In addition, operation based representation was used to encode the solution, and a neighbourhood search structure was employed to search for the new solutions. The case studies are Lawrence instances that were taken from the Operations Research Library. Computational results of this probabilistic meta-heuristic algorithm were compared with a conventional genetic algorithm, and a conclusion was made based on the algorithm and problem.

  6. A Bayesian matching pursuit based scheduling algorithm for feedback reduction in MIMO broadcast channels

    KAUST Repository

    Shibli, Hussain J.

    2013-06-01

    Opportunistic schedulers rely on the feedback of all users in order to schedule a set of users with favorable channel conditions. While the downlink channels can be easily estimated at all user terminals via a single broadcast, several key challenges are faced during uplink transmission. First of all, the statistics of the noisy and fading feedback channels are unknown at the base station (BS) and channel training is usually required from all users. Secondly, the amount of network resources (air-time) required for feedback transmission grows linearly with the number of users. In this paper, we tackle the above challenges and propose a Bayesian based scheduling algorithm that 1) reduces the air-time required to identify the strong users, and 2) is agnostic to the statistics of the feedback channels and utilizes the a priori statistics of the additive noise to identify the strong users. Numerical results show that the proposed algorithm reduces the feedback air-time while improving detection in the presence of fading and noisy channels when compared to recent compressed sensing based algorithms. Furthermore, the proposed algorithm achieves a sum-rate throughput close to that obtained by noiseless dedicated feedback systems. © 2013 IEEE.

  7. 7 CFR 1124.50 - Class prices, component prices, and advanced pricing factors.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 9 2010-01-01 2009-01-01 true Class prices, component prices, and advanced pricing factors. 1124.50 Section 1124.50 Agriculture Regulations of the Department of Agriculture (Continued... prices, and advanced pricing factors. See § 1000.50. ...

  8. 7 CFR 1030.50 - Class prices, component prices, and advanced pricing factors.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 9 2010-01-01 2009-01-01 true Class prices, component prices, and advanced pricing factors. 1030.50 Section 1030.50 Agriculture Regulations of the Department of Agriculture (Continued... prices, and advanced pricing factors. See § 1000.50. ...

  9. A Trial-and-Error Method with Autonomous Vehicle-to-Infrastructure Traffic Counts for Cordon-Based Congestion Pricing

    Directory of Open Access Journals (Sweden)

    Zhiyuan Liu

    2017-01-01

    Full Text Available This study proposes a practical trial-and-error method to solve the optimal toll design problem of cordon-based pricing, where only the traffic counts autonomously collected on the entry links of the pricing cordon are needed. With the fast development and adoption of vehicle-to-infrastructure (V2I facilities, it is very convenient to autonomously collect these data. Two practical properties of the cordon-based pricing are further considered in this article: the toll charge on each entry of one pricing cordon is identical; the total inbound flow to one cordon should be restricted in order to maintain the traffic conditions within the cordon area. Then, the stochastic user equilibrium (SUE with asymmetric link travel time functions is used to assess each feasible toll pattern. Based on a variational inequality (VI model for the optimal toll pattern, this study proposes a theoretically convergent trial-and-error method for the addressed problem, where only traffic counts data are needed. Finally, the proposed method is verified based on a numerical network example.

  10. Spot Pricing When Lagrange Multipliers Are Not Unique

    DEFF Research Database (Denmark)

    Feng, Donghan; Xu, Zhao; Zhong, Jin

    2012-01-01

    Classical spot pricing theory is based on multipliers of the primal problem of an optimal market dispatch, i.e., the solution of the dual problem. However, the dual problem of market dispatch may yield multiple solutions. In these circumstances, spot pricing or any standard pricing practice based...... on a strict extension of the principles of spot pricing and surplus allocation, we propose a new pricing methodology that can yield unique, impartial, and robust solution. The new method has been analyzed and compared with other pricing approaches in accordance with spot pricing theory. Case studies support...

  11. Using pharmacoeconomic modelling to determine value-based pricing for new pharmaceuticals in malaysia.

    Science.gov (United States)

    Dranitsaris, George; Truter, Ilse; Lubbe, Martie S; Sriramanakoppa, Nitin N; Mendonca, Vivian M; Mahagaonkar, Sangameshwar B

    2011-10-01

    Decision analysis (DA) is commonly used to perform economic evaluations of new pharmaceuticals. Using multiples of Malaysia's per capita 2010 gross domestic product (GDP) as the threshold for economic value as suggested by the World Health Organization (WHO), DA was used to estimate a price per dose for bevacizumab, a drug that provides a 1.4-month survival benefit in patients with metastatic colorectal cancer (mCRC). A decision model was developed to simulate progression-free and overall survival in mCRC patients receiving chemotherapy with and without bevacizumab. Costs for chemotherapy and management of side effects were obtained from public and private hospitals in Malaysia. Utility estimates, measured as quality-adjusted life years (QALYs), were determined by interviewing 24 oncology nurses using the time trade-off technique. The price per dose was then estimated using a target threshold of US$44 400 per QALY gained, which is 3 times the Malaysian per capita GDP. A cost-effective price for bevacizumab could not be determined because the survival benefit provided was insufficient According to the WHO criteria, if the drug was able to improve survival from 1.4 to 3 or 6 months, the price per dose would be $567 and $1258, respectively. The use of decision modelling for estimating drug pricing is a powerful technique to ensure value for money. Such information is of value to drug manufacturers and formulary committees because it facilitates negotiations for value-based pricing in a given jurisdiction.

  12. The development of KMRR schedule and progress control system (KSPCS) for the master schedule of KMRR project

    International Nuclear Information System (INIS)

    Choi, Chang Woong; Lee, Tae Joon; Kim, Joon Yun; Cho, Yun Ho; Hah, Jong Hyun

    1993-07-01

    This report was to development the computerized schedule and progress control system for the master schedule of KMRR project with ARTEMIS 7000/386 CM (Ver. 7.4.2.) based on project management theory (PERT/CPM, PDM, and S-curve). This system has been efficiently used for KMRR master schedule and will be utilized for the detail scheduling of KMRR project. (Author) 23 refs., 26 figs., 52 tabs

  13. The development of KMRR schedule and progress control system (KSPCS) for the master schedule of KMRR project

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Chang Woong; Lee, Tae Joon; Kim, Joon Yun; Cho, Yun Ho; Hah, Jong Hyun [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1993-07-01

    This report was to development the computerized schedule and progress control system for the master schedule of KMRR project with ARTEMIS 7000/386 CM (Ver. 7.4.2.) based on project management theory (PERT/CPM, PDM, and S-curve). This system has been efficiently used for KMRR master schedule and will be utilized for the detail scheduling of KMRR project. (Author) 23 refs., 26 figs., 52 tabs.

  14. Minimizing tardiness for job shop scheduling under uncertainties

    OpenAIRE

    Yahouni , Zakaria; Mebarki , Nasser; Sari , Zaki

    2016-01-01

    International audience; —Many disturbances can occur during the execution of a manufacturing scheduling process. To cope with this drawback , flexible solutions are proposed based on the offline and the online phase of the schedule. Groups of permutable operations is one of the most studied flexible scheduling methods bringing flexibility as well as quality to a schedule. The online phase of this method is based on a human-machine system allowing to choose in real-time one schedule from a set...

  15. The Arbitrage Pricing Model: A Pedagogic Derivation and a Spreadsheet-Based Illustration

    Directory of Open Access Journals (Sweden)

    Clarence C. Y. Kwan

    2016-05-01

    Full Text Available This paper derives, from a pedagogic perspective, the Arbitrage Pricing Model, which is an important asset pricing model in modern finance. The derivation is based on the idea that, if a self-financed investment has no risk exposures, the payoff from the investment can only be zero. Microsoft Excel plays an important pedagogic role in this paper. The Excel illustration not only helps students recognize more fully the various nuances in the model derivation, but also serves as a good starting point for students to explore on their own the relevance of the noise issue in the model derivation.

  16. Oil price shocks and long run price and import demand behavior

    International Nuclear Information System (INIS)

    Kleibergen, F.; Van Dijk, H.K.; Urbain, J.P.

    1997-01-01

    The effect which the oil price time series has on the long run properties of Vector AutoRegressive (VAR) models for price levels and import demand is investigated. As the oil price variable is assumed to be weakly exogenous for the long run parameters, a cointegration testing procedure allowing for weakly exogenous variables is developed using a LU decomposition of the long run multiplier matrix. The likelihood based cointegration test statistics, Wald, Likelihood Ratio and Lagrange Multiplier, are constructed and their limiting distributions derived. Using these tests, we find that incorporating the oil price in a model for the domestic or import price level of seven industrialized countries decreases the long run memory of the inflation rate. Second, we find that the results for import demand can be classified with respect to the oil importing or exporting status of the specific country. The result for Japan is typical as its import price is not influenced by gnp in the long run, which is the case for all other countries. 31 refs

  17. An On-Time Power-Aware Scheduling Scheme for Medical Sensor SoC-Based WBAN Systems

    Directory of Open Access Journals (Sweden)

    Jung-Guk Kim

    2012-12-01

    Full Text Available The focus of many leading technologies in the field of medical sensor systems is on low power consumption and robust data transmission. For example, the implantable cardioverter-defibrillator (ICD, which is used to maintain the heart in a healthy state, requires a reliable wireless communication scheme with an extremely low duty-cycle, high bit rate, and energy-efficient media access protocols. Because such devices must be sustained for over 5 years without access to battery replacement, they must be designed to have extremely low power consumption in sleep mode. Here, an on-time, energy-efficient scheduling scheme is proposed that performs power adjustments to minimize the sleep-mode current. The novelty of this scheduler is that it increases the determinacy of power adjustment and the predictability of scheduling by employing non-pre-emptible dual priority scheduling. This predictable scheduling also guarantees the punctuality of important periodic tasks based on their serialization, by using their worst case execution time and the power consumption optimization. The scheduler was embedded into a system on chip (SoC developed to support the wireless body area network—a wakeup-radio and wakeup-timer for implantable medical devices. This scheduling system is validated by the experimental results of its performance when used with life-time extensions of ICD devices.

  18. Perceived benefits of adopting Standard – Based pricing mechanism for mechanical and electrical services installations

    Directory of Open Access Journals (Sweden)

    Ganiyu Amuda Yusuf

    2014-06-01

    Full Text Available Cost is an important measure of project success and clients will expect a reliable forecast at the early stage of construction projects to inform their business decision. This study was undertaken to investigate the current practices in managing cost of mechanical and electrical (M&E services in buildings. The perceptions of practitioners on the benefits of adopting Standard – Based Pricing Mechanism for M&E services as used for building fabrics and finishes was ascertained. The methodology adopted for the study was semi – structure interview and questionnaire survey.  Inferential statistics technique was used to analyse the data collected. The results revealed that, M&E services tender documents are often based on lump sum contract. Practitioners are of the opinion that the adoption of Standard – Based Pricing Mechanism (SBPM could enhance the quality of M&E services price forecast; ensure active post contract cost monitoring and control; encourage collaborative working relationship; enhance efficient whole life cycle cost management; improve risk management and facilitate efficient tendering process. The study suggested the development of local Standard Method of Measurement for M&E services and proposed strategies to facilitate the adoption of SBPM as basis for forecasting contract price of mechanical and electrical services in buildings.

  19. Cross-border electricity market effects due to price caps in an emission trading system : An agent-based approach

    NARCIS (Netherlands)

    Richstein, J.C.; Chappin, E.J.L.; De Vries, L.J.

    2014-01-01

    The recent low CO2 prices in the European Union Emission Trading Scheme (EU ETS) have triggered a discussion whether the EU ETS needs to be adjusted. We study the effects of CO2 price floors and a price ceiling on the dynamic investment pathway of two interlinked electricity markets (loosely based

  20. QoS Differential Scheduling in Cognitive-Radio-Based Smart Grid Networks: An Adaptive Dynamic Programming Approach.

    Science.gov (United States)

    Yu, Rong; Zhong, Weifeng; Xie, Shengli; Zhang, Yan; Zhang, Yun

    2016-02-01

    As the next-generation power grid, smart grid will be integrated with a variety of novel communication technologies to support the explosive data traffic and the diverse requirements of quality of service (QoS). Cognitive radio (CR), which has the favorable ability to improve the spectrum utilization, provides an efficient and reliable solution for smart grid communications networks. In this paper, we study the QoS differential scheduling problem in the CR-based smart grid communications networks. The scheduler is responsible for managing the spectrum resources and arranging the data transmissions of smart grid users (SGUs). To guarantee the differential QoS, the SGUs are assigned to have different priorities according to their roles and their current situations in the smart grid. Based on the QoS-aware priority policy, the scheduler adjusts the channels allocation to minimize the transmission delay of SGUs. The entire transmission scheduling problem is formulated as a semi-Markov decision process and solved by the methodology of adaptive dynamic programming. A heuristic dynamic programming (HDP) architecture is established for the scheduling problem. By the online network training, the HDP can learn from the activities of primary users and SGUs, and adjust the scheduling decision to achieve the purpose of transmission delay minimization. Simulation results illustrate that the proposed priority policy ensures the low transmission delay of high priority SGUs. In addition, the emergency data transmission delay is also reduced to a significantly low level, guaranteeing the differential QoS in smart grid.

  1. A Partial Backlogging Inventory Model for Deteriorating Items with Fluctuating Selling Price and Purchasing Cost

    Directory of Open Access Journals (Sweden)

    Hui-Ling Yang

    2012-01-01

    Full Text Available In today’s competitive markets, selling price and purchasing cost are usually fluctuating with economic conditions. Both selling price and purchasing cost are vital to the profitability of a firm. Therefore, in this paper, I extend the inventory model introduced by Teng and Yang (2004 to allow for not only the selling price but also the purchasing cost to change from one replenishment cycle to another during a finite time horizon. The objective is to find the optimal replenishment schedule and pricing policy to obtain the profit as maximum as possible. The conditions that lead to a maximizing solution guarantee that the existence, uniqueness, and global optimality are proposed. An efficient solution procedure and some theoretical results are presented. Finally, numerical examples for illustration and sensitivity analysis for managerial decision making are also performed.

  2. Refinery production planning and scheduling: the refining core business

    Directory of Open Access Journals (Sweden)

    M. Joly

    2012-06-01

    Full Text Available Intelligent production planning and scheduling are of paramount importance to ensure refinery profitability, logistic reliability and safety at the local and corporate levels. In Brazil, such activities play a particularly critical role, since the Brazilian downstream model is moving towards a demand-driven model rather than a supply-driven one. Moreover, new and specialized non-linear constraints are continuously being incorporated into these large-scale problems: increases in oil prices implying the need for processing poor quality crudes, increasing demand and new demand patterns for petroleum products, new stringent environmental regulations related to clean fuels and start-up of new production technologies embedded into more complex refining schemes. This paper aims at clarifying the central role of refinery planning and scheduling activities in the Petrobras refining business. Major past and present results are outlined and corporate long-term strategies to deal with present and future challenges are presented.

  3. A Countrywide House Price Index for 152 Years

    DEFF Research Database (Denmark)

    Lunde, Jens; Helding Madsen, Anders; Lundbæk Laursen, Maria

    for Herengracht (the Netherlands), Norway, USA, France, and recently also Australia. Until now, the here presented house price index for Denmark is the longest countrywide house price index ever been published, based on official data, and qualitatively probably the best long house price index....... in house prices is depicted. The Danish house price index covering all the 152 years is in reality a simple average sale price index for houses. From 1920 on it was possible to construct another and a “pure” house price index, based on the Sales Price Appraisal Ratio (SPAR) method. Several challenges...... for creating the house price index arose, especially in converting the previous registered house prices in the statistics into current market prices. In real terms, the average sale price index increased more than the SPAR index for the years where the two indices were compared, and the difference express...

  4. Analysis of domestic price and inflation determinants in Iran (as a developing oil-export based economy)

    NARCIS (Netherlands)

    S.F. Dizaji (Sajjad Faraji)

    2011-01-01

    textabstractAbstract The objective of this study is to examine and investigate both behaviour and determinants of domestic prices and inflation rate in Iran as a developing oil export based economy. I apply two models; the first model is for investigating the main determinants of domestic prices

  5. Research on Energy-Saving Production Scheduling Based on a Clustering Algorithm for a Forging Enterprise

    Directory of Open Access Journals (Sweden)

    Yifei Tong

    2016-02-01

    Full Text Available Energy efficiency is a buzzword of the 21st century. With the ever growing need for energy efficient and low-carbon production, it is a big challenge for high energy-consumption enterprises to reduce their energy consumption. To this aim, a forging enterprise, DVR (the abbreviation of a forging enterprise, is researched. Firstly, an investigation into the production processes of DVR is given as well as an analysis of forging production. Then, the energy-saving forging scheduling is decomposed into two sub-problems. One is for cutting and machining scheduling, which is similar to traditional machining scheduling. The other one is for forging and heat treatment scheduling. Thirdly, former forging production scheduling is presented and solved based on an improved genetic algorithm. Fourthly, the latter is discussed in detail, followed by proposed dynamic clustering and stacking combination optimization. The proposed stacking optimization requires making the gross weight of forgings as close to the maximum batch capacity as possible. The above research can help reduce the heating times, and increase furnace utilization with high energy efficiency and low carbon emissions.

  6. Pricing effects on food choices.

    Science.gov (United States)

    French, Simone A

    2003-03-01

    Individual dietary choices are primarily influenced by such considerations as taste, cost, convenience and nutritional value of foods. The current obesity epidemic has been linked to excessive consumption of added sugars and fat, as well as to sedentary lifestyles. Fat and sugar provide dietary energy at very low cost. Food pricing and marketing practices are therefore an essential component of the eating environment. Recent studies have applied economic theories to changing dietary behavior. Price reduction strategies promote the choice of targeted foods by lowering their cost relative to alternative food choices. Two community-based intervention studies used price reductions to promote the increased purchase of targeted foods. The first study examined lower prices and point-of-purchase promotion on sales of lower fat vending machine snacks in 12 work sites and 12 secondary schools. Price reductions of 10%, 25% and 50% on lower fat snacks resulted in an increase in sales of 9%, 39% and 93%, respectively, compared with usual price conditions. The second study examined the impact of a 50% price reduction on fresh fruit and baby carrots in two secondary school cafeterias. Compared with usual price conditions, price reductions resulted in a four-fold increase in fresh fruit sales and a two-fold increase in baby carrot sales. Both studies demonstrate that price reductions are an effective strategy to increase the purchase of more healthful foods in community-based settings such as work sites and schools. Results were generalizable across various food types and populations. Reducing prices on healthful foods is a public health strategy that should be implemented through policy initiatives and industry collaborations.

  7. Optional time-of-use prices for electricity: Analysis of PG E's experimental TOU rates

    Energy Technology Data Exchange (ETDEWEB)

    Train, K.; Mehrez, G.

    1992-07-01

    We examine customers' time-of-use (TOU) demand for electricity and their choice between standard and TOU rate schedules. We specify an econometric model in which the customer's demand curves determine the customer's choice of rate schedule. We estimate the model on data from Pacific Gas Electric Company's experiment with optional TOU prices in the residential sector. With the model, we compare the TOU consumption and price elasticities of customers who chose TOU rates with those who chose standard rates. We also estimate the impact of the TOU rates on the utility's revenues and costs. The analysis suggests that the TOU rates offered under PG E's experiment decreased PG E's profits and hence contributed to higher general rate levels. The model can be used, however, to design optional TOU rates that increase profits and lower general rate levels.

  8. Land Prices and Fundamentals

    OpenAIRE

    Koji Nakamura; Yumi Saita

    2007-01-01

    This paper examines the long-term relationship between macro economic fundamentals and the weighted-average land price indicators, which are supposed to be more appropriate than the official land price indicators when analyzing their impacts on the macro economy. In many cases, we find the cointegrating relationships between the weighted-average land price indicators and the discounted present value of land calculated based on the macro economic fundamentals indicators. We also find that the ...

  9. Activity-based costing for pathology examinations and comparison with the current pricing system in Turkey.

    Science.gov (United States)

    Ergün, Ferda A K; Ağirbaş, Ismail; Kuzu, Işınsu

    2013-01-01

    To demonstrate the real cost data of the pathology examinations by using the activity-based costing method and to contribute to the financial planning of the departments, health managers and also the social security institution. Forty-four examinations selected from the Healthcare Implementation Notification system list and performed at the Ankara University Faculty of Medicine Pathology Department during September 2010 were studied. The analysis and the real cost calculations were done according to the duration of the procedures. Calculated costs were compared with the Healthcare Implementation Notification system and Medicare price lists. The costs of the pathology tests listed within the same pricing levels in the Healthcare Implementation Notification system list showed great differences. The minimum and maximum costs in level 1, 2, 3, and 4 were 15,98-80,15 TL, 15,95-258,59 TL, 42,38- 236,87 TL, and 124,42-406,76 TL, respectively. Medicare price levels were more consistent with the real costs of the examinations compared to the Healthcare Implementation Notification system price list. The prices of the pathology examination listed at different levels in the Healthcare Implementation Notification system lists do not cover the real costs of the work done. The principal parameters of Activity-Based Costing system are more suitable for making the most realistic cost categorization. Although the prices could differ between countries, the Medicare system categories are more realistic than the Healthcare Implementation Notification system. The Healthcare Implementation Notification system list needs to be revised in order to reflect the real costs of the pathology examinations.

  10. MULTISHAPE TASK SCHEDULING ALGORITHM FOR REAL TIME MICRO-CONTROLLER BASED APPLICATION

    OpenAIRE

    Ankur Jain

    2017-01-01

    Embedded Systems are usually microcontroller-based systems that represent a class of reliable and dependable dedicated computer systems designed for specific purposes. Micro-controllers are used in most electronic devices in an endless variety of ways. Some micro-controller-based embedded systems are required to respond to external events in the shortest possible time and such systems are known as realtime embedded systems. So in multitasking system there is a need of task Scheduling, there a...

  11. ANALYSIS OF EXPECTED PRICE DYNAMICS BETWEEN FLUID MILK FUTURES CONTRACTS AND CASH PRICES FOR FLUID MILK

    OpenAIRE

    T. Randall FORTENBERY; Robert A. CROPP; Hector O. ZAPATA

    1997-01-01

    The objective of this study is to provide an empirical evaluation of the expected relationship between cash and futures prices for fluid milk. This is done using historic cash prices from 1988 to 1995, and making inferences about how futures prices would have behaved if they had traded during this sample period. Futures prices are simulated over the sample period based on two assumptions about futures market behavior for fluid milk. The first is that the futures market will essentially price ...

  12. Price-based Optimal Control of Electrical Power Systems

    Energy Technology Data Exchange (ETDEWEB)

    Jokic, A.

    2007-09-10

    The research presented in this thesis is motivated by the following issue of concern for the operation of future power systems: Future power systems will be characterized by significantly increased uncertainties at all time scales and, consequently, their behavior in time will be difficult to predict. In Chapter 2 we will present a novel explicit, dynamic, distributed feedback control scheme that utilizes nodal-prices for real-time optimal power balance and network congestion control. The term explicit means that the controller is not based on solving an optimization problem on-line. Instead, the nodal prices updates are based on simple, explicitly defined and easily comprehensible rules. We prove that the developed control scheme, which acts on the measurements from the current state of the system, always provide the correct nodal prices. In Chapter 3 we will develop a novel, robust, hybrid MPC control (model predictive controller) scheme for power balance control with hard constraints on line power flows and network frequency deviations. The developed MPC controller acts in parallel with the explicit controller from Chapter 2, and its task is to enforce the constraints during the transient periods following suddenly occurring power imbalances in the system. In Chapter 4 the concept of autonomous power networks will be presented as a concise formulation to deal with economic, technical and reliability issues in power systems with a large penetration of distributed generating units. With autonomous power networks as new market entities, we propose a novel operational structure of ancillary service markets. In Chapter 5 we will consider the problem of controlling a general linear time-invariant dynamical system to an economically optimal operating point, which is defined by a multiparametric constrained convex optimization problem related with the steady-state operation of the system. The parameters in the optimization problem are values of the exogenous inputs to

  13. When do price thresholds matter in retail categories?

    OpenAIRE

    Pauwels, Koen; Srinivasan, Shuba; Franses, Philip Hans

    2007-01-01

    textabstractMarketing literature has long recognized that brand price elasticity need not be monotonic and symmetric, but has yet to provide generalizable market-level insights on threshold-based price elasticity, asymmetric thresholds, and the sign and magnitude of elasticity transitions. This paper introduces smooth transition regression models to study threshold-based price elasticity of the top 4 brands across 20 fast-moving consumer good categories. Threshold-based price elasticity is fo...

  14. Accounting for fuel price risk when comparing renewable togas-fired generation: the role of forward natural gas prices

    Energy Technology Data Exchange (ETDEWEB)

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2004-07-17

    Unlike natural gas-fired generation, renewable generation (e.g., from wind, solar, and geothermal power) is largely immune to fuel price risk. If ratepayers are rational and value long-term price stability, then--contrary to common practice--any comparison of the levelized cost of renewable to gas-fired generation should be based on a hedged gas price input, rather than an uncertain gas price forecast. This paper compares natural gas prices that can be locked in through futures, swaps, and physical supply contracts to contemporaneous long-term forecasts of spot gas prices. We find that from 2000-2003, forward gas prices for terms of 2-10 years have been considerably higher than most contemporaneous long-term gas price forecasts. This difference is striking, and implies that comparisons between renewable and gas-fired generation based on these forecasts over this period have arguably yielded results that are biased in favor of gas-fired generation.

  15. Electricity price modeling with stochastic time change

    International Nuclear Information System (INIS)

    Borovkova, Svetlana; Schmeck, Maren Diane

    2017-01-01

    In this paper, we develop a novel approach to electricity price modeling, based on the powerful technique of stochastic time change. This technique allows us to incorporate the characteristic features of electricity prices (such as seasonal volatility, time varying mean reversion and seasonally occurring price spikes) into the model in an elegant and economically justifiable way. The stochastic time change introduces stochastic as well as deterministic (e.g., seasonal) features in the price process' volatility and in the jump component. We specify the base process as a mean reverting jump diffusion and the time change as an absolutely continuous stochastic process with seasonal component. The activity rate of the stochastic time change can be related to the factors that influence supply and demand. Here we use the temperature as a proxy for the demand and hence, as the driving factor of the stochastic time change, and show that this choice leads to realistic price paths. We derive properties of the resulting price process and develop the model calibration procedure. We calibrate the model to the historical EEX power prices and apply it to generating realistic price paths by Monte Carlo simulations. We show that the simulated price process matches the distributional characteristics of the observed electricity prices in periods of both high and low demand. - Highlights: • We develop a novel approach to electricity price modeling, based on the powerful technique of stochastic time change. • We incorporate the characteristic features of electricity prices, such as seasonal volatility and spikes into the model. • We use the temperature as a proxy for the demand and hence, as the driving factor of the stochastic time change • We derive properties of the resulting price process and develop the model calibration procedure. • We calibrate the model to the historical EEX power prices and apply it to generating realistic price paths.

  16. Taking the lag out of jet lag through model-based schedule design.

    Science.gov (United States)

    Dean, Dennis A; Forger, Daniel B; Klerman, Elizabeth B

    2009-06-01

    Travel across multiple time zones results in desynchronization of environmental time cues and the sleep-wake schedule from their normal phase relationships with the endogenous circadian system. Circadian misalignment can result in poor neurobehavioral performance, decreased sleep efficiency, and inappropriately timed physiological signals including gastrointestinal activity and hormone release. Frequent and repeated transmeridian travel is associated with long-term cognitive deficits, and rodents experimentally exposed to repeated schedule shifts have increased death rates. One approach to reduce the short-term circadian, sleep-wake, and performance problems is to use mathematical models of the circadian pacemaker to design countermeasures that rapidly shift the circadian pacemaker to align with the new schedule. In this paper, the use of mathematical models to design sleep-wake and countermeasure schedules for improved performance is demonstrated. We present an approach to designing interventions that combines an algorithm for optimal placement of countermeasures with a novel mode of schedule representation. With these methods, rapid circadian resynchrony and the resulting improvement in neurobehavioral performance can be quickly achieved even after moderate to large shifts in the sleep-wake schedule. The key schedule design inputs are endogenous circadian period length, desired sleep-wake schedule, length of intervention, background light level, and countermeasure strength. The new schedule representation facilitates schedule design, simulation studies, and experiment design and significantly decreases the amount of time to design an appropriate intervention. The method presented in this paper has direct implications for designing jet lag, shift-work, and non-24-hour schedules, including scheduling for extreme environments, such as in space, undersea, or in polar regions.

  17. Stock price forecasting based on time series analysis

    Science.gov (United States)

    Chi, Wan Le

    2018-05-01

    Using the historical stock price data to set up a sequence model to explain the intrinsic relationship of data, the future stock price can forecasted. The used models are auto-regressive model, moving-average model and autoregressive-movingaverage model. The original data sequence of unit root test was used to judge whether the original data sequence was stationary. The non-stationary original sequence as a first order difference needed further processing. Then the stability of the sequence difference was re-inspected. If it is still non-stationary, the second order differential processing of the sequence is carried out. Autocorrelation diagram and partial correlation diagram were used to evaluate the parameters of the identified ARMA model, including coefficients of the model and model order. Finally, the model was used to forecast the fitting of the shanghai composite index daily closing price with precision. Results showed that the non-stationary original data series was stationary after the second order difference. The forecast value of shanghai composite index daily closing price was closer to actual value, indicating that the ARMA model in the paper was a certain accuracy.

  18. Research on the ITOC based scheduling system for ship piping production

    Science.gov (United States)

    Li, Rui; Liu, Yu-Jun; Hamada, Kunihiro

    2010-12-01

    Manufacturing of ship piping systems is one of the major production activities in shipbuilding. The schedule of pipe production has an important impact on the master schedule of shipbuilding. In this research, the ITOC concept was introduced to solve the scheduling problems of a piping factory, and an intelligent scheduling system was developed. The system, in which a product model, an operation model, a factory model, and a knowledge database of piping production were integrated, automated the planning process and production scheduling. Details of the above points were discussed. Moreover, an application of the system in a piping factory, which achieved a higher level of performance as measured by tardiness, lead time, and inventory, was demonstrated.

  19. Duality-based algorithms for scheduling on unrelated parallel machines

    NARCIS (Netherlands)

    van de Velde, S.L.; van de Velde, S.L.

    1993-01-01

    We consider the following parallel machine scheduling problem. Each of n independent jobs has to be scheduled on one of m unrelated parallel machines. The processing of job J[sub l] on machine Mi requires an uninterrupted period of positive length p[sub lj]. The objective is to find an assignment of

  20. A novel downlink scheduling strategy for traffic communication system based on TD-LTE technology.

    Science.gov (United States)

    Chen, Ting; Zhao, Xiangmo; Gao, Tao; Zhang, Licheng

    2016-01-01

    There are many existing classical scheduling algorithms which can obtain better system throughput and user equality, however, they are not designed for traffic transportation environment, which cannot consider whether the transmission performance of various information flows could meet comprehensive requirements of traffic safety and delay tolerance. This paper proposes a novel downlink scheduling strategy for traffic communication system based on TD-LTE technology, which can perform two classification mappings for various information flows in the eNodeB: firstly, associate every information flow packet with traffic safety importance weight according to its relevance to the traffic safety; secondly, associate every traffic information flow with service type importance weight according to its quality of service (QoS) requirements. Once the connection is established, at every scheduling moment, scheduler would decide the scheduling order of all buffers' head of line packets periodically according to the instant value of scheduling importance weight function, which calculated by the proposed algorithm. From different scenario simulations, it can be verified that the proposed algorithm can provide superior differentiated transmission service and reliable QoS guarantee to information flows with different traffic safety levels and service types, which is more suitable for traffic transportation environment compared with the existing popularity PF algorithm. With the limited wireless resource, information flow closed related to traffic safety will always obtain priority scheduling right timely, which can help the passengers' journey more safe. Moreover, the proposed algorithm cannot only obtain good flow throughput and user fairness which are almost equal to those of the PF algorithm without significant differences, but also provide better realtime transmission guarantee to realtime information flow.

  1. Novel transmission pricing scheme based on point-to-point tariff and transaction pair matching for pool market

    International Nuclear Information System (INIS)

    Chen, Qixin; Xia, Qing; Kang, Chongqing

    2010-01-01

    Transmission pricing scheme is a key component in the infrastructure of power market, and pool is an indispensable pattern of market organization; meanwhile, pay-as-bid (PAB) serves as a main option to determine market prices in pool. In this paper, a novel transmission pricing scheme is proposed for pool power market based on PAB. The new scheme is developed by utilizing point-to-point (PTP) tariff and introducing an approach of transaction pair matching (TPM). The model and procedure of the new scheme are presented in detail. Apart from the advantages of existing transmission pricing schemes, such as ensuing open, fair and non-discriminatory access, proper recovery for investment as well as transparency, the new scheme provides economic signals to promote the maximum use of the existing transmission network, encourages appropriate bidding behaviors in pool, and helps to reduce the possibility of the enforcement of market power and the appearing of price spikes; thus improves market operation efficiency and trading effects. In order to testify the effectiveness of the proposed scheme, a case based on IEEE 30-bus system is studied. (author)

  2. Novel transmission pricing scheme based on point-to-point tariff and transaction pair matching for pool market

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Qixin; Xia, Qing; Kang, Chongqing [State Key Lab. of Power System, Dept. of Electrical Engineering, Tsinghua University, Beijing 100084 (China)

    2010-04-15

    Transmission pricing scheme is a key component in the infrastructure of power market, and pool is an indispensable pattern of market organization; meanwhile, pay-as-bid (PAB) serves as a main option to determine market prices in pool. In this paper, a novel transmission pricing scheme is proposed for pool power market based on PAB. The new scheme is developed by utilizing point-to-point (PTP) tariff and introducing an approach of transaction pair matching (TPM). The model and procedure of the new scheme are presented in detail. Apart from the advantages of existing transmission pricing schemes, such as ensuing open, fair and non-discriminatory access, proper recovery for investment as well as transparency, the new scheme provides economic signals to promote the maximum use of the existing transmission network, encourages appropriate bidding behaviors in pool, and helps to reduce the possibility of the enforcement of market power and the appearing of price spikes; thus improves market operation efficiency and trading effects. In order to testify the effectiveness of the proposed scheme, a case based on IEEE 30-bus system is studied. (author)

  3. A new approach for crude oil price analysis based on empirical mode decomposition

    International Nuclear Information System (INIS)

    Zhang, Xun; Wang, Shou-Yang; Lai, K.K.

    2008-01-01

    The importance of understanding the underlying characteristics of international crude oil price movements attracts much attention from academic researchers and business practitioners. Due to the intrinsic complexity of the oil market, however, most of them fail to produce consistently good results. Empirical Mode Decomposition (EMD), recently proposed by Huang et al., appears to be a novel data analysis method for nonlinear and non-stationary time series. By decomposing a time series into a small number of independent and concretely implicational intrinsic modes based on scale separation, EMD explains the generation of time series data from a novel perspective. Ensemble EMD (EEMD) is a substantial improvement of EMD which can better separate the scales naturally by adding white noise series to the original time series and then treating the ensemble averages as the true intrinsic modes. In this paper, we extend EEMD to crude oil price analysis. First, three crude oil price series with different time ranges and frequencies are decomposed into several independent intrinsic modes, from high to low frequency. Second, the intrinsic modes are composed into a fluctuating process, a slowly varying part and a trend based on fine-to-coarse reconstruction. The economic meanings of the three components are identified as short term fluctuations caused by normal supply-demand disequilibrium or some other market activities, the effect of a shock of a significant event, and a long term trend. Finally, the EEMD is shown to be a vital technique for crude oil price analysis. (author)

  4. Relating price strategies and price-setting practices

    NARCIS (Netherlands)

    Ingenbleek, P.T.M.; Lans, van der I.A.

    2013-01-01

    Purpose - This article addresses the relationship between price strategies and price-setting practices. The first derive from a normative tradition in the pricing literature and the latter from a descriptive tradition. Price strategies are visible in the market, whereas price-setting practices are

  5. Orphan Drug Pricing: An Original Exponential Model Relating Price to the Number of Patients

    Directory of Open Access Journals (Sweden)

    Andrea Messori

    2016-10-01

    Full Text Available In managing drug prices at the national level, orphan drugs represent a special case because the price of these agents is higher than that determined according to value-based principles. A common practice is to set the orphan drug price in an inverse relationship with the number of patients, so that the price increases as the number of patients decreases. Determination of prices in this context generally has a purely empirical nature, but a theoretical basis would be needed. The present paper describes an original exponential model that manages the relationship between price and number of patients for orphan drugs. Three real examples are analysed in detail (eculizumab, bosentan, and a data set of 17 orphan drugs published in 2010. These analyses have been aimed at identifying some objective criteria to rationally inform this relationship between prices and patients and at converting these criteria into explicit quantitative rules.

  6. A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems

    Directory of Open Access Journals (Sweden)

    Yingni Zhai

    2014-10-01

    Full Text Available Purpose: A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems (JSP is proposed.Design/methodology/approach: In the algorithm, a number of sub-problems are constructed by iteratively decomposing the large-scale JSP according to the process route of each job. And then the solution of the large-scale JSP can be obtained by iteratively solving the sub-problems. In order to improve the sub-problems' solving efficiency and the solution quality, a detection method for multi-bottleneck machines based on critical path is proposed. Therewith the unscheduled operations can be decomposed into bottleneck operations and non-bottleneck operations. According to the principle of “Bottleneck leads the performance of the whole manufacturing system” in TOC (Theory Of Constraints, the bottleneck operations are scheduled by genetic algorithm for high solution quality, and the non-bottleneck operations are scheduled by dispatching rules for the improvement of the solving efficiency.Findings: In the process of the sub-problems' construction, partial operations in the previous scheduled sub-problem are divided into the successive sub-problem for re-optimization. This strategy can improve the solution quality of the algorithm. In the process of solving the sub-problems, the strategy that evaluating the chromosome's fitness by predicting the global scheduling objective value can improve the solution quality.Research limitations/implications: In this research, there are some assumptions which reduce the complexity of the large-scale scheduling problem. They are as follows: The processing route of each job is predetermined, and the processing time of each operation is fixed. There is no machine breakdown, and no preemption of the operations is allowed. The assumptions should be considered if the algorithm is used in the actual job shop.Originality/value: The research provides an efficient scheduling method for the

  7. When Do Price Thresholds Matter in Retail Categories?

    OpenAIRE

    Koen Pauwels; Shuba Srinivasan; Philip Hans Franses

    2007-01-01

    Marketing literature has long recognized that brand price elasticity need not be monotonic and symmetric, but has yet to provide generalizable market-level insights on threshold-based price elasticity, asymmetric thresholds, and the sign and magnitude of elasticity transitions. This paper introduces smooth transition regression models to study threshold-based price elasticity of the top 4 brands across 20 fast-moving consumer good categories. Threshold-based price elasticity is found for 76% ...

  8. A Graph-Based Approach to Action Scheduling in a Parallel Database System

    NARCIS (Netherlands)

    Grefen, P.W.P.J.; Apers, Peter M.G.

    Parallel database machines are meant to obtain high performance in transaction processing, both in terms of response time adn throughput. To obtain high performance, a good scheduling of the execution of the various actions in transactions is crucial. This paper describes a graph-based technique for

  9. Artificial intelligence approaches to astronomical observation scheduling

    Science.gov (United States)

    Johnston, Mark D.; Miller, Glenn

    1988-01-01

    Automated scheduling will play an increasing role in future ground- and space-based observatory operations. Due to the complexity of the problem, artificial intelligence technology currently offers the greatest potential for the development of scheduling tools with sufficient power and flexibility to handle realistic scheduling situations. Summarized here are the main features of the observatory scheduling problem, how artificial intelligence (AI) techniques can be applied, and recent progress in AI scheduling for Hubble Space Telescope.

  10. Marketplace pricing

    International Nuclear Information System (INIS)

    Anon.

    1991-01-01

    As discussed in this chapter, interest in marketplace pricing has been increasing in recent years, reflecting the societal trend toward substituting competition for regulation where appropriate. Competition is valuable because it encourages utilities to make efficient decisions with a minimum of regulatory intervention. It enhances efficiency through the incentive for innovation by the regulated companies and by increasing the likelihood they will come forward with proposals for better services, lower prices or both. Ultimately, consumers are beneficiaries. Marketplace pricing is emblematic of the view that the degree of regulation should reflect the degree of market power, that workably competitive markets should be allowed to operate with as little regulatory interference as possible. The Edison Electric Institute has made perhaps the most detailed proposal on marketplace pricing. It and others perceive numerous benefits from this method of pricing transmission services. Given the undeniable market power resulting from line ownership, FERC has emphasized the need to find a workably competitive market before approving such proposals. The ability to make this distinction without a full-blown antitrust review for every transaction is questionable, and FERC has yet to provide generic guidance. Finally, FERC's legal ability to depart from cost-based standards is questionable

  11. Prediction Based Proactive Thermal Virtual Machine Scheduling in Green Clouds

    Directory of Open Access Journals (Sweden)

    Supriya Kinger

    2014-01-01

    Full Text Available Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a criterion for Virtual Machine (VM scheduling. This paper proposes a new proactive technique that considers current and maximum threshold temperature of Server Machines (SMs before making scheduling decisions with the help of a temperature predictor, so that maximum temperature is never reached. Different workload scenarios have been taken into consideration. The results obtained show that the proposed system is better than existing systems of VM scheduling, which does not consider current temperature of nodes before making scheduling decisions. Thus, a reduction in need of cooling systems for a Cloud environment has been obtained and validated.

  12. Prediction based proactive thermal virtual machine scheduling in green clouds.

    Science.gov (United States)

    Kinger, Supriya; Kumar, Rajesh; Sharma, Anju

    2014-01-01

    Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a criterion for Virtual Machine (VM) scheduling. This paper proposes a new proactive technique that considers current and maximum threshold temperature of Server Machines (SMs) before making scheduling decisions with the help of a temperature predictor, so that maximum temperature is never reached. Different workload scenarios have been taken into consideration. The results obtained show that the proposed system is better than existing systems of VM scheduling, which does not consider current temperature of nodes before making scheduling decisions. Thus, a reduction in need of cooling systems for a Cloud environment has been obtained and validated.

  13. Prediction Based Proactive Thermal Virtual Machine Scheduling in Green Clouds

    Science.gov (United States)

    Kinger, Supriya; Kumar, Rajesh; Sharma, Anju

    2014-01-01

    Cloud computing has rapidly emerged as a widely accepted computing paradigm, but the research on Cloud computing is still at an early stage. Cloud computing provides many advanced features but it still has some shortcomings such as relatively high operating cost and environmental hazards like increasing carbon footprints. These hazards can be reduced up to some extent by efficient scheduling of Cloud resources. Working temperature on which a machine is currently running can be taken as a criterion for Virtual Machine (VM) scheduling. This paper proposes a new proactive technique that considers current and maximum threshold temperature of Server Machines (SMs) before making scheduling decisions with the help of a temperature predictor, so that maximum temperature is never reached. Different workload scenarios have been taken into consideration. The results obtained show that the proposed system is better than existing systems of VM scheduling, which does not consider current temperature of nodes before making scheduling decisions. Thus, a reduction in need of cooling systems for a Cloud environment has been obtained and validated. PMID:24737962

  14. Taking the lag out of jet lag through model-based schedule design.

    Directory of Open Access Journals (Sweden)

    Dennis A Dean

    2009-06-01

    Full Text Available Travel across multiple time zones results in desynchronization of environmental time cues and the sleep-wake schedule from their normal phase relationships with the endogenous circadian system. Circadian misalignment can result in poor neurobehavioral performance, decreased sleep efficiency, and inappropriately timed physiological signals including gastrointestinal activity and hormone release. Frequent and repeated transmeridian travel is associated with long-term cognitive deficits, and rodents experimentally exposed to repeated schedule shifts have increased death rates. One approach to reduce the short-term circadian, sleep-wake, and performance problems is to use mathematical models of the circadian pacemaker to design countermeasures that rapidly shift the circadian pacemaker to align with the new schedule. In this paper, the use of mathematical models to design sleep-wake and countermeasure schedules for improved performance is demonstrated. We present an approach to designing interventions that combines an algorithm for optimal placement of countermeasures with a novel mode of schedule representation. With these methods, rapid circadian resynchrony and the resulting improvement in neurobehavioral performance can be quickly achieved even after moderate to large shifts in the sleep-wake schedule. The key schedule design inputs are endogenous circadian period length, desired sleep-wake schedule, length of intervention, background light level, and countermeasure strength. The new schedule representation facilitates schedule design, simulation studies, and experiment design and significantly decreases the amount of time to design an appropriate intervention. The method presented in this paper has direct implications for designing jet lag, shift-work, and non-24-hour schedules, including scheduling for extreme environments, such as in space, undersea, or in polar regions.

  15. a Quadtree Organization Construction and Scheduling Method for Urban 3d Model Based on Weight

    Science.gov (United States)

    Yao, C.; Peng, G.; Song, Y.; Duan, M.

    2017-09-01

    The increasement of Urban 3D model precision and data quantity puts forward higher requirements for real-time rendering of digital city model. Improving the organization, management and scheduling of 3D model data in 3D digital city can improve the rendering effect and efficiency. This paper takes the complexity of urban models into account, proposes a Quadtree construction and scheduling rendering method for Urban 3D model based on weight. Divide Urban 3D model into different rendering weights according to certain rules, perform Quadtree construction and schedule rendering according to different rendering weights. Also proposed an algorithm for extracting bounding box extraction based on model drawing primitives to generate LOD model automatically. Using the algorithm proposed in this paper, developed a 3D urban planning&management software, the practice has showed the algorithm is efficient and feasible, the render frame rate of big scene and small scene are both stable at around 25 frames.

  16. A QUADTREE ORGANIZATION CONSTRUCTION AND SCHEDULING METHOD FOR URBAN 3D MODEL BASED ON WEIGHT

    Directory of Open Access Journals (Sweden)

    C. Yao

    2017-09-01

    Full Text Available The increasement of Urban 3D model precision and data quantity puts forward higher requirements for real-time rendering of digital city model. Improving the organization, management and scheduling of 3D model data in 3D digital city can improve the rendering effect and efficiency. This paper takes the complexity of urban models into account, proposes a Quadtree construction and scheduling rendering method for Urban 3D model based on weight. Divide Urban 3D model into different rendering weights according to certain rules, perform Quadtree construction and schedule rendering according to different rendering weights. Also proposed an algorithm for extracting bounding box extraction based on model drawing primitives to generate LOD model automatically. Using the algorithm proposed in this paper, developed a 3D urban planning&management software, the practice has showed the algorithm is efficient and feasible, the render frame rate of big scene and small scene are both stable at around 25 frames.

  17. 7 CFR 1131.53 - Announcement of class prices, component prices, and advanced pricing factors.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 9 2010-01-01 2009-01-01 true Announcement of class prices, component prices, and advanced pricing factors. 1131.53 Section 1131.53 Agriculture Regulations of the Department of Agriculture... class prices, component prices, and advanced pricing factors. See § 1000.53. ...

  18. 7 CFR 1005.53 - Announcement of class prices, component prices, and advanced pricing factors.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 9 2010-01-01 2009-01-01 true Announcement of class prices, component prices, and advanced pricing factors. 1005.53 Section 1005.53 Agriculture Regulations of the Department of Agriculture... class prices, component prices, and advanced pricing factors. See § 1000.53. ...

  19. 7 CFR 1126.53 - Announcement of class prices, component prices, and advanced pricing factors.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 9 2010-01-01 2009-01-01 true Announcement of class prices, component prices, and advanced pricing factors. 1126.53 Section 1126.53 Agriculture Regulations of the Department of Agriculture... class prices, component prices, and advanced pricing factors. See § 1000.53. ...

  20. 7 CFR 1032.53 - Announcement of class prices, component prices, and advanced pricing factors.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 9 2010-01-01 2009-01-01 true Announcement of class prices, component prices, and advanced pricing factors. 1032.53 Section 1032.53 Agriculture Regulations of the Department of Agriculture... class prices, component prices, and advanced pricing factors. See § 1000.53. ...