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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. 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...

  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. 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.

  5. 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

  6. 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.

  7. 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

  8. 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....

  9. 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. .

  10. 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...

  11. 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.

  12. 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. .

  13. 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....

  14. 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....

  15. 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.

  16. 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...

  17. 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

  18. 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

  19. 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.

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

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    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.

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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 ...

  9. 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...

  10. 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....

  11. 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...

  12. 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.

  13. 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.

  14. 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...

  15. 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...

  16. 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

  17. 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...

  18. 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.

  19. 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.

  20. 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...

  1. 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.

  2. 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...

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. 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...

  10. 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...

  11. 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...

  12. 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.

  13. 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

  14. 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.

  15. 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...

  16. 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.

  17. 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

  18. 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...

  19. 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.

  20. 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.

  1. 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.

  2. Price

    International Nuclear Information System (INIS)

    Anon.

    1991-01-01

    The price terms in wheeling contracts very substantially, reflecting the differing conditions affecting the parties contracting for the service. These terms differ in the manner in which rates are calculated, the formulas used, and the philosophy underlying the accord. For example, and EEI study found that firm wheeling rates ranged from 20 cents to $1.612 per kilowatt per month. Nonfirm rates ranged from .15 mills to 5.25 mills per kilowatt-hour. The focus in this chapter is on cost-based rates, reflecting the fact that the vast majority of existing contracts are based on rate designs reflecting embedded costs. This situation may change in the future, but, for now, this fact can't be ignored

  3. 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

  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. 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.)

  6. 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...

  7. 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.

  8. 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.

  9. 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)

  10. 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.

  11. 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.

  12. 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...

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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...

  3. 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...

  4. 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.

  5. 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...

  6. 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.

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

    OpenAIRE

    Fetene, Gebeyehu Manie; Kaplan, Sigal; Prato, Carlo Giacomo; Sebald, Alexander Christopher

    2016-01-01

    This articled-based dissertation consists of five self-contained chapters. The first chapter presents the motivation of the dissertation and a summary of the four papers contenting the dissertation. Three of the chapters are applied microeconomics papers dealing with the economics of recharging 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...

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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.

  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. 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

  16. 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

  17. 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)

  18. 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

  19. 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...

  20. 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.

  1. 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.

  2. 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

  3. 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...

  4. 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...

  5. 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)

  6. 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.

  7. 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.

  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. 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.

  10. 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.

  11. 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 ...

  12. 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.

  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. 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.

  15. 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.

  16. 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...

  17. 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.

  18. Aging based maintenance and reinvestment scheduling of electric distribution

    Energy Technology Data Exchange (ETDEWEB)

    Korpijarvi, J.

    2012-07-01

    The maintenance of electric distribution network is a topical question for distribution system operators because of increasing significance of failure costs. In this dissertation the maintenance practices of the distribution system operators are analyzed and a theory for scheduling maintenance activities and reinvestment of distribution components is created. The scheduling is based on the deterioration of components and the increasing failure rates due to aging. The dynamic programming algorithm is used as a solving method to maintenance problem which is caused by the increasing failure rates of the network. The other impacts of network maintenance like environmental and regulation reasons are not included to the scope of this thesis. Further the tree trimming of the corridors and the major disturbance of the network are not included to the problem optimized in this thesis. For optimizing, four dynamic programming models are presented and the models are tested. Programming is made in VBA-language to the computer. For testing two different kinds of test networks are used. Because electric distribution system operators want to operate with bigger component groups, optimal timing for component groups is also analyzed. A maintenance software package is created to apply the presented theories in practice. An overview of the program is presented (orig.)

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. A Gain-Scheduling PI Control Based on Neural Networks

    Directory of Open Access Journals (Sweden)

    Stefania Tronci

    2017-01-01

    Full Text Available This paper presents a gain-scheduling design technique that relies upon neural models to approximate plant behaviour. The controller design is based on generic model control (GMC formalisms and linearization of the neural model of the process. As a result, a PI controller action is obtained, where the gain depends on the state of the system and is adapted instantaneously on-line. The algorithm is tested on a nonisothermal continuous stirred tank reactor (CSTR, considering both single-input single-output (SISO and multi-input multi-output (MIMO control problems. Simulation results show that the proposed controller provides satisfactory performance during set-point changes and disturbance rejection.

  6. 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.

  7. 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...

  8. 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 ...

  9. 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. 

  10. 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.

  11. 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, ...

  12. 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

  13. 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.

  14. 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...

  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. 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.

  17. 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

  18. 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.

  19. Weighted-SNR-based fair scheduling for uplink OFDMA

    KAUST Repository

    Ma, Yao

    2009-11-01

    In this paper, we study the sum rate maximization algorithms with long-term proportional rate fairness (PRF) for uplink orthogonal frequency division multiple access (OFDMA) systems. In contrast to the rate-maximization schemes which used short-term PRF in the literature, we propose to use a selective multiuser diversity (SMuD) scheme to achieve a long-term PRF and improved sum rate performance. This scheme implements weighted channel signal-to-noise ratio (w-SNR)-based ranking for user selection on each subchannel, and then uses either water-filling (WF) or equal power allocation (EPA) along the assigned channels of each user. Both offline and online methods to find the optimal SNR weight factors are designed to achieve the target proportional rates for different users. The offline optimization technique requires to know the channel distribution information (CDI) at the scheduler. The online method uses the weight adaption combined with individual user rate tracking, which avoids the need to know the CDI. Analytical throughput metrics for the proposed w-SNR scheme with WF and EPA over Rayleigh channels are derived, and verified by simulations. Simulation results show that the proposed w-SNR PRF scheme can achieve significantly higher sum rates than the frequency diversity-based short-term and long-term fairness schemes. Besides the improved performance, the proposed schemes have a low complexity which is linear to numbers of users and subchannels.

  20. 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.

  1. A risk-based approach to scheduling audits.

    Science.gov (United States)

    Rönninger, Stephan; Holmes, Malcolm

    2009-01-01

    The manufacture and supply of pharmaceutical products can be a very complex operation. Companies may purchase a wide variety of materials, from active pharmaceutical ingredients to packaging materials, from "in company" suppliers or from third parties. They may also purchase or contract a number of services such as analysis, data management, audit, among others. It is very important that these materials and services are of the requisite quality in order that patient safety and company reputation are adequately protected. Such quality requirements are ongoing throughout the product life cycle. In recent years, assurance of quality has been derived via audit of the supplier or service provider and by using periodic audits, for example, annually or at least once every 5 years. In the past, companies may have used an audit only for what they considered to be "key" materials or services and used testing on receipt, for example, as their quality assurance measure for "less important" supplies. Such approaches changed as a result of pressure from both internal sources and regulators to the time-driven audit for all suppliers and service providers. Companies recognised that eventually they would be responsible for the quality of the supplied product or service and audit, although providing only a "snapshot in time" seemed a convenient way of demonstrating that they were meeting their obligations. Problems, however, still occur with the supplied product or service and will usually be more frequent from certain suppliers. Additionally, some third-party suppliers will no longer accept routine audits from individual companies, as the overall audit load can exceed one external audit per working day. Consequently a different model is needed for assessing supplier quality. This paper presents a risk-based approach to creating an audit plan and for scheduling the frequency and depth of such audits. The approach is based on the principles and process of the Quality Risk Management

  2. Condition-based maintenance at both scheduled and unscheduled opportunities

    NARCIS (Netherlands)

    Kalosi, S.; Kapodistria, S.; Resing, J.A.C.

    2016-01-01

    Motivated by original equipment manufacturer (OEM) service and maintenance practices we consider a single component subject to replacements at failure instances and two types of preventive maintenance opportunities: scheduled, which occur due to periodic system reviews of the equipment, and

  3. Weighted-SNR-based fair scheduling for uplink OFDMA

    KAUST Repository

    Ma, Yao; Leith, Alex; Alouini, Mohamed-Slim; (Sherman) Shen X., Xuemin

    2009-01-01

    rates for different users. The offline optimization technique requires to know the channel distribution information (CDI) at the scheduler. The online method uses the weight adaption combined with individual user rate tracking, which avoids the need

  4. 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.

  5. Optimal Scheduling of Doctors Outpatient Departments Based on Patients’ Behavior

    Directory of Open Access Journals (Sweden)

    Zongwei Ren

    2016-01-01

    Full Text Available The low operational efficiency in the field of medical and health care has become a serious problem in China; the long time that the patients have to wait for is the main phenomenon of difficult medical service. Medical industry is service-oriented and its main purpose is to make profits, so the benefits and competitiveness of a hospital depend on patient satisfaction. This paper makes a survey on a large hospital in Harbin of China and collects relevant data and then uses the prospect theory to analyze patients’ and doctors’ behavioral characteristics and the model of patient satisfaction is established based on fuzzy theory with a triplet α/β/γ. The optimal scheduling of clinic is described as a problem with the rule of first come, first served which maximizes patient satisfaction for the main goal and minimizes operating costs for the secondary goal. And the corresponding mathematical model is established. Finally, a solution method named plant growth simulation algorithm (PGSA is presented. Then, by means of calculating of the example and comparing with genetic algorithm, the results show that the optimum can be reached; meanwhile the efficiency of the presented algorithm is better than the genetic algorithm.

  6. 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

  7. 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

  8. 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

  9. 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

  10. [Trust-based economics with medicine outcome-based pricing].

    Science.gov (United States)

    Lhoste, F

    2013-09-01

    In recent decades, the pharmaceutical industry as built a high level of confidence thanks to innovative medicines that improve both duration and quality of life. Some recent scandals have however discredited this industry, now suspected of cheating or bribery. Even the scientific progresses are challenged on the ground of possible conflicts of interests and value uncertainty. This situation is deleterious. Simultaneously the economic crisis exacerbates the payers' expectations in terms of clinical value and value/price ratio. It also stimulates the demand for outcomes in real life. This induces a new economic approach for the market access of highly expensive reimbursable drugs. It consists in paying only for drugs actually proven effective in terms of actual outcomes, with a full or partial refund of the payer in case of failure, according to accurate and simple criteria in so called "performance agreement". Confidence is restored accordingly. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

  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. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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...

  17. 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.

  18. 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-...

  19. Size-based scheduling to improve web performance

    NARCIS (Netherlands)

    Harchol-Balter, M.; Schroeder, B.; Bansal, N.; Agrawal, M.

    2003-01-01

    Is it possible to reduce the expected response time of every request at a web server, simply by changing the order in which we schedule the requests? That is the question we ask in this paper.This paper proposes a method for improving the performance of web servers servicing static HTTP requests.

  20. Gain Scheduling Control based on Closed-Loop System Identification

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, Klaus

    the first and a second operating point is identified in closed-loop using system identification methods with open-loop properties. Next, a linear controller is designed for this linearised model, and gain scheduling control can subsequently be achieved by interpolating between each controller...

  1. Research and Applications of Shop Scheduling Based on Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Hang ZHAO

    Full Text Available ABSTRACT Shop Scheduling is an important factor affecting the efficiency of production, efficient scheduling method and a research and application for optimization technology play an important role for manufacturing enterprises to improve production efficiency, reduce production costs and many other aspects. Existing studies have shown that improved genetic algorithm has solved the limitations that existed in the genetic algorithm, the objective function is able to meet customers' needs for shop scheduling, and the future research should focus on the combination of genetic algorithm with other optimized algorithms. In this paper, in order to overcome the shortcomings of early convergence of genetic algorithm and resolve local minimization problem in search process,aiming at mixed flow shop scheduling problem, an improved cyclic search genetic algorithm is put forward, and chromosome coding method and corresponding operation are given.The operation has the nature of inheriting the optimal individual ofthe previous generation and is able to avoid the emergence of local minimum, and cyclic and crossover operation and mutation operation can enhance the diversity of the population and then quickly get the optimal individual, and the effectiveness of the algorithm is validated. Experimental results show that the improved algorithm can well avoid the emergency of local minimum and is rapid in convergence.

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

    KAUST Repository

    Rashid, Faraan; Nam, Haewoon; Alouini, Mohamed-Slim

    2012-01-01

    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

  3. Simulation-based Advance Patient Scheduling of Operating Theatres

    DEFF Research Database (Denmark)

    Andersen, Anders Reenberg; Stidsen, Thomas Jacob Riis; Nielsen, Bo Friis

    2017-01-01

    Daily scheduling of surgical operations is a complicated and recurrent problem in the literature on health care optimization. In this study, we present an often overlooked approach to this problem that incorporates a rolling and overlapping planning horizon. The basis of our modeling approach is ...

  4. 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.

  5. 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.

  6. 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...

  7. 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...

  8. 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

  9. 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.

  10. Profit-based conventional resource scheduling with renewable energy penetration

    Science.gov (United States)

    Reddy, K. Srikanth; Panwar, Lokesh Kumar; Kumar, Rajesh; Panigrahi, B. K.

    2017-08-01

    Technological breakthroughs in renewable energy technologies (RETs) enabled them to attain grid parity thereby making them potential contenders for existing conventional resources. To examine the market participation of RETs, this paper formulates a scheduling problem accommodating energy market participation of wind- and solar-independent power producers (IPPs) treating both conventional and RETs as identical entities. Furthermore, constraints pertaining to penetration and curtailments of RETs are restructured. Additionally, an appropriate objective function for profit incurred by conventional resource IPPs through reserve market participation as a function of renewable energy curtailment is also proposed. The proposed concept is simulated with a test system comprising 10 conventional generation units in conjunction with solar photovoltaic (SPV) and wind energy generators (WEG). The simulation results indicate that renewable energy integration and its curtailment limits influence the market participation or scheduling strategies of conventional resources in both energy and reserve markets. Furthermore, load and reliability parameters are also affected.

  11. 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...

  12. 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...

  13. 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

  14. 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.

  15. 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)

  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. 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....

  18. 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.

  19. 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....

  20. 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.

  1. 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)

  2. 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.

  3. 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.

  4. 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

  5. A GIS-based hedonic price model for agricultural land

    Science.gov (United States)

    Demetriou, Demetris

    2015-06-01

    Land consolidation is a very effective land management planning approach that aims towards rural/agricultural sustainable development. Land reallocation which involves land tenure restructuring is the most important, complex and time consuming component of land consolidation. Land reallocation relies on land valuation since its fundamental principle provides that after consolidation, each landowner shall be granted a property of an aggregate value that is approximately the same as the value of the property owned prior to consolidation. Therefore, land value is the crucial factor for the land reallocation process and hence for the success and acceptance of the final land consolidation plan. Land valuation is a process of assigning values to all parcels (and its contents) and it is usually carried out by an ad-hoc committee. However, the process faces some problems such as it is time consuming hence costly, outcomes may present inconsistency since it is carried out manually and empirically without employing systematic analytical tools and in particular spatial analysis tools and techniques such as statistical/mathematical. A solution to these problems can be the employment of mass appraisal land valuation methods using automated valuation models (AVM) based on international standards. In this context, this paper presents a spatial based linear hedonic price model which has been developed and tested in a case study land consolidation area in Cyprus. Results showed that the AVM is capable to produce acceptable in terms of accuracy and reliability land values and to reduce time hence cost required by around 80%.

  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 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.

  8. 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.

  9. 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

  10. 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...

  11. Optimal scheduling of micro grids based on single objective programming

    Science.gov (United States)

    Chen, Yue

    2018-04-01

    Faced with the growing demand for electricity and the shortage of fossil fuels, how to optimally optimize the micro-grid has become an important research topic to maximize the economic, technological and environmental benefits of the micro-grid. This paper considers the role of the battery and the micro-grid and power grid to allow the exchange of power not exceeding 150kW preconditions, the main study of the economy to load for the goal is to minimize the electricity cost (abandonment of wind), to establish an optimization model, and to solve the problem by genetic algorithm. The optimal scheduling scheme is obtained and the utilization of renewable energy and the impact of the battery involved in regulation are analyzed.

  12. 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

  13. 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.

  14. 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.

  15. 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...

  16. 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.

  17. 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.

  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. 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.

  20. 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.

  1. Optimization-based sale transactions and hydrothermal scheduling

    International Nuclear Information System (INIS)

    Prasannan, B.; Luh, P.B.; Zhang, L.

    1996-01-01

    Selling and purchasing power are important activities for utilities because of potential savings. When a selling utility presents an offer including prices, power levels and durations, a purchasing utility selects power levels and durations within the offered range subject to relevant constraints. The decisionmaking process is complicated because transactions are coupled with system demand and reserve, therefore decisions have to be made in conjunction with the commitment and dispatching of units. Furthermore, transaction decisions have to be made in almost real time in view of the competitiveness of the power market caused by deregulation. In this paper, transactions are analyzed from a selling utility's viewpoint for a system consisting of thermal, hydro and pumped-storage units. To effectively solve the problem, linear sale revenues are approximated by nonlinear functions, and non-profitable options are identified and eliminated from consideration. The multipliers are then updated at the high level by using a modified subgradient method to obtain near optimal solutions quickly. Testing results show that the algorithm produces good sale offers efficiently

  2. 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

  3. 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

  4. 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.

  5. A QUADTREE ORGANIZATION CONSTRUCTION AND SCHEDULING METHOD FOR URBAN 3D MODEL BASED ON WEIGHT

    OpenAIRE

    C. Yao; G. Peng; Y. Song; M. Duan

    2017-01-01

    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 weigh...

  6. 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...

  7. 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

  8. 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.

  9. 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

  10. 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...

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  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. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. [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.

  5. 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.

  6. PERFORMANCE ANALYSIS BETWEEN EXPLICIT SCHEDULING AND IMPLICIT SCHEDULING OF PARALLEL ARRAY-BASED DOMAIN DECOMPOSITION USING OPENMP

    Directory of Open Access Journals (Sweden)

    MOHAMMED FAIZ ABOALMAALY

    2014-10-01

    Full Text Available With the continuous revolution of multicore architecture, several parallel programming platforms have been introduced in order to pave the way for fast and efficient development of parallel algorithms. Back into its categories, parallel computing can be done through two forms: Data-Level Parallelism (DLP or Task-Level Parallelism (TLP. The former can be done by the distribution of data among the available processing elements while the latter is based on executing independent tasks concurrently. Most of the parallel programming platforms have built-in techniques to distribute the data among processors, these techniques are technically known as automatic distribution (scheduling. However, due to their wide range of purposes, variation of data types, amount of distributed data, possibility of extra computational overhead and other hardware-dependent factors, manual distribution could achieve better outcomes in terms of performance when compared to the automatic distribution. In this paper, this assumption is investigated by conducting a comparison between automatic and our newly proposed manual distribution of data among threads in parallel. Empirical results of matrix addition and matrix multiplication show a considerable performance gain when manual distribution is applied against automatic distribution.

  7. 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

  8. 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.

  9. Economic analysis of electric heating based on critical electricity price

    Science.gov (United States)

    Xie, Feng; Sun, Zhijie; Zhou, Xinnan; Fu, Chengran; Yang, Jie

    2018-06-01

    The State Grid Corporation of China proposes an alternative energy strategy, which will make electric heating an important task in the field of residential electricity consumption. This article takes this as the background, has made the detailed introduction to the inhabitant electric heating technology, and take the Zhangjiakou electric panels heating technology as an example, from the expense angle, has carried on the analysis to the electric panels heating economy. In the field of residential heating, electric panels operating costs less than gas boilers. After customers implying energy-saving behavior, electric panels operating cost is even lower than coal-fired boilers. The critical price is higher than the execution price, which indicates that the economic performance of the electric panels is significantly higher than that of the coal boiler.

  10. Consumption-based macroeconomic models of asset pricing theory

    Directory of Open Access Journals (Sweden)

    Đorđević Marija

    2016-01-01

    Full Text Available The family of consumptionbased asset pricing models yields a stochastic discount factor proportional to the marginal rate of intertemporal substitution of consumption. In examining the empirical performance of this class of models, several puzzles are discovered. In this literature review we present the canonical model, the corresponding empirical tests, and different extensions to this model that propose a resolution of these puzzles.

  11. 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.

  12. Downstream-based Scheduling for Energy Conservation in Green EPONs

    KAUST Repository

    Chen, Shen; Dhaini, Ahmad R.; Ho, Pin-Han; Shihada, Basem; Shen, Gangxiang; Lin, Chih-Hao

    2012-01-01

    the ONU sleep time, it jeopardizes the quality of service (QoS) performance of the network, especially for downstream traffic in case the overlapping is based on the upstream time slot. In this paper, we study the downstream traffic performance in green

  13. 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.

  14. 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

  15. 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

  16. Downstream-based Scheduling for Energy Conservation in Green EPONs

    KAUST Repository

    Chen, Shen

    2012-05-01

    Maximizing the optical network unit’s (ONU) sleep time is an effective approach for achieving maximum energy conservation in green Ethernet passive optical networks (EPONs). While overlapping downstream and upstream ONU transmissions can maximize the ONU sleep time, it jeopardizes the quality of service (QoS) performance of the network, especially for downstream traffic in case the overlapping is based on the upstream time slot. In this paper, we study the downstream traffic performance in green EPONs under the limited service discipline and the upstream-based overlapped time window. Specifically, we first derive the expected mean packet delay, and then present a closed-form expression of the ONU sleep time, setting identical upstream/downstream transmission cycle times based on a maximum downstream traffic delay re-quirement. With the proposed system model, we present a novel downstream bandwidth allocation scheme for energy conservation in green EPONs. Simulation results verify the proposed model and highlight the advantages of our scheme over conventional approaches.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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...

  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. Gain Scheduling of PID Controller Based on Fuzzy Systems

    Directory of Open Access Journals (Sweden)

    Singh Sandeep

    2016-01-01

    Full Text Available This paper aims to utilize fuzzy rules and reasoning to determine the controller parameters and the PID controller generates the control signal. The objective of this study is to simulate the proposed scheme on various processes and arrive at results providing better response of the system when compared with best industrial auto-tuning technique: Ziegler-Nichols. The proposed scheme is based upon the Ultimate Gain (Ku and the Period (Tu of the system. The error and rate of change in error gains are tuned manually to get the desired response using LabVIEW. This can also be done with various optimization techniques. A thumb rule for choosing the ranges for Kc, Kd and Ki has been obtained experimentally.

  4. 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 ...

  5. Comparative study of heuristics algorithms in solving flexible job shop scheduling problem with condition based maintenance

    Directory of Open Access Journals (Sweden)

    Yahong Zheng

    2014-05-01

    Full Text Available Purpose: This paper focuses on a classic optimization problem in operations research, the flexible job shop scheduling problem (FJSP, to discuss the method to deal with uncertainty in a manufacturing system.Design/methodology/approach: In this paper, condition based maintenance (CBM, a kind of preventive maintenance, is suggested to reduce unavailability of machines. Different to the simultaneous scheduling algorithm (SSA used in the previous article (Neale & Cameron,1979, an inserting algorithm (IA is applied, in which firstly a pre-schedule is obtained through heuristic algorithm and then maintenance tasks are inserted into the pre-schedule scheme.Findings: It is encouraging that a new better solution for an instance in benchmark of FJSP is obtained in this research. Moreover, factually SSA used in literature for solving normal FJSPPM (FJSP with PM is not suitable for the dynamic FJSPPM. Through application in the benchmark of normal FJSPPM, it is found that although IA obtains inferior results compared to SSA used in literature, it performs much better in executing speed.Originality/value: Different to traditional scheduling of FJSP, uncertainty of machines is taken into account, which increases the complexity of the problem. An inserting algorithm (IA is proposed to solve the dynamic scheduling problem. It is stated that the quality of the final result depends much on the quality of the pre-schedule obtained during the procedure of solving a normal FJSP. In order to find the best solution of FJSP, a comparative study of three heuristics is carried out, the integrated GA, ACO and ABC. In the comparative study, we find that GA performs best in the three heuristic algorithms. Meanwhile, a new better solution for an instance in benchmark of FJSP is obtained in this research.

  6. 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.

  7. 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.

  8. Ship Block Transportation Scheduling Problem Based on Greedy Algorithm

    Directory of Open Access Journals (Sweden)

    Chong Wang

    2016-05-01

    Full Text Available Ship block transportation problems are crucial issues to address in reducing the construction cost and improving the productivity of shipyards. Shipyards aim to maximize the workload balance of transporters with time constraint such that all blocks should be transported during the planning horizon. This process leads to three types of penalty time: empty transporter travel time, delay time, and tardy time. This study aims to minimize the sum of the penalty time. First, this study presents the problem of ship block transportation with the generalization of the block transportation restriction on the multi-type transporter. Second, the problem is transformed into the classical traveling salesman problem and assignment problem through a reasonable model simplification and by adding a virtual node to the proposed directed graph. Then, a heuristic algorithm based on greedy algorithm is proposed to assign blocks to available transporters and sequencing blocks for each transporter simultaneously. Finally, the numerical experiment method is used to validate the model, and its result shows that the proposed algorithm is effective in realizing the efficient use of the transporters in shipyards. Numerical simulation results demonstrate the promising application of the proposed method to efficiently improve the utilization of transporters and to reduce the cost of ship block logistics for shipyards.

  9. 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

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Evaluating Visual Activity Schedules as Evidence-Based Practice for Individuals with Autism Spectrum Disorders

    Science.gov (United States)

    Knight, Victoria; Sartini, Emily; Spriggs, Amy D.

    2015-01-01

    A comprehensive review of the literature was conducted for articles published between 1993 and 2013 to evaluate the quality of the Visual Activity Schedules (VAS) literature using current evidence-based criteria developed by Horner et al. (Except Child 71:165-179, 2005). Authors sought to determine whether VAS can be considered an evidence-based…

  16. 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.

  17. Examination of the Evidence Base for Using Visual Activity Schedules with Students with Intellectual Disability

    Science.gov (United States)

    Spriggs, Amy D.; Mims, Pamela J.; van Dijk, Wilhelmina; Knight, Victoria F.

    2017-01-01

    We conducted a comprehensive review of the literature to establish the evidence base for using visual activity schedules (VAS) with individuals with intellectual disability. Literature published after 2005 was evaluated for quality using the criteria developed by Horner et al.; a total of 14 studies were included as acceptable. Findings suggest…

  18. 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

  19. 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 ...

  20. 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

  1. 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...

  2. 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.

  3. 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

  4. 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.

  5. 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...

  6. 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...

  7. 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.

  8. Pricing and Timing Strategies for New Product Using Agent-Based Simulation of Behavioural Consumers

    OpenAIRE

    Keeheon Lee; Hoyeop Lee; Chang Ouk Kim

    2014-01-01

    In this study, we are interested in the problem of determining the pricing and timing strategies of a new product by developing an agent-based product diffusion simulation. In the proposed simulation model, agents imitate behavioural consumers, who are reference dependent and risk averse in the evaluation of new products and whose interactions create word-of-mouth regarding new products. Pricing and timing strategies involve the timing of a new product release, the timing of providing a disco...

  9. Deterministic Echo State Networks Based Stock Price Forecasting

    Directory of Open Access Journals (Sweden)

    Jingpei Dan

    2014-01-01

    Full Text Available Echo state networks (ESNs, as efficient and powerful computational models for approximating nonlinear dynamical systems, have been successfully applied in financial time series forecasting. Reservoir constructions in standard ESNs rely on trials and errors in real applications due to a series of randomized model building stages. A novel form of ESN with deterministically constructed reservoir is competitive with standard ESN by minimal complexity and possibility of optimizations for ESN specifications. In this paper, forecasting performances of deterministic ESNs are investigated in stock price prediction applications. The experiment results on two benchmark datasets (Shanghai Composite Index and S&P500 demonstrate that deterministic ESNs outperform standard ESN in both accuracy and efficiency, which indicate the prospect of deterministic ESNs for financial prediction.

  10. CAViaR-based forecast for oil price risk

    International Nuclear Information System (INIS)

    Huang, Dashan; Yu, Baimin; Fabozzi, Frank J.; Fukushima, Masao

    2009-01-01

    As a benchmark for measuring market risk, value-at-risk (VaR) reduces the risk associated with any kind of asset to just a number (amount in terms of a currency), which can be well understood by regulators, board members, and other interested parties. This paper employs a new VaR approach due to Engle and Manganelli [Engle, R.F., Manganelli, S., 2004. CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles. Journal of Business and Economic Statistics 22, 367-381] to forecasting oil price risk. In doing so, we provide two original contributions by introducing a new exponentially weighted moving average CAViaR model and developing a mixed data regression model for multi-period VaR prediction. (author)

  11. 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)

  12. 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.

  13. 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.

  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. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  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. 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...

  3. 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....

  4. 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.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. Load Balancing Integrated Least Slack Time-Based Appliance Scheduling for Smart Home Energy Management

    Science.gov (United States)

    Silva, Bhagya Nathali; Khan, Murad; Han, Kijun

    2018-01-01

    The emergence of smart devices and smart appliances has highly favored the realization of the smart home concept. Modern smart home systems handle a wide range of user requirements. Energy management and energy conservation are in the spotlight when deploying sophisticated smart homes. However, the performance of energy management systems is highly influenced by user behaviors and adopted energy management approaches. Appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption. Hence, we propose a smart home energy management system that reduces unnecessary energy consumption by integrating an automated switching off system with load balancing and appliance scheduling algorithm. The load balancing scheme acts according to defined constraints such that the cumulative energy consumption of the household is managed below the defined maximum threshold. The scheduling of appliances adheres to the least slack time (LST) algorithm while considering user comfort during scheduling. The performance of the proposed scheme has been evaluated against an existing energy management scheme through computer simulation. The simulation results have revealed a significant improvement gained through the proposed LST-based energy management scheme in terms of cost of energy, along with reduced domestic energy consumption facilitated by an automated switching off mechanism. PMID:29495346

  10. 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.

  11. Load Balancing Integrated Least Slack Time-Based Appliance Scheduling for Smart Home Energy Management

    Directory of Open Access Journals (Sweden)

    Bhagya Nathali Silva

    2018-02-01

    Full Text Available The emergence of smart devices and smart appliances has highly favored the realization of the smart home concept. Modern smart home systems handle a wide range of user requirements. Energy management and energy conservation are in the spotlight when deploying sophisticated smart homes. However, the performance of energy management systems is highly influenced by user behaviors and adopted energy management approaches. Appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption. Hence, we propose a smart home energy management system that reduces unnecessary energy consumption by integrating an automated switching off system with load balancing and appliance scheduling algorithm. The load balancing scheme acts according to defined constraints such that the cumulative energy consumption of the household is managed below the defined maximum threshold. The scheduling of appliances adheres to the least slack time (LST algorithm while considering user comfort during scheduling. The performance of the proposed scheme has been evaluated against an existing energy management scheme through computer simulation. The simulation results have revealed a significant improvement gained through the proposed LST-based energy management scheme in terms of cost of energy, along with reduced domestic energy consumption facilitated by an automated switching off mechanism.

  12. Load Balancing Integrated Least Slack Time-Based Appliance Scheduling for Smart Home Energy Management.

    Science.gov (United States)

    Silva, Bhagya Nathali; Khan, Murad; Han, Kijun

    2018-02-25

    The emergence of smart devices and smart appliances has highly favored the realization of the smart home concept. Modern smart home systems handle a wide range of user requirements. Energy management and energy conservation are in the spotlight when deploying sophisticated smart homes. However, the performance of energy management systems is highly influenced by user behaviors and adopted energy management approaches. Appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption. Hence, we propose a smart home energy management system that reduces unnecessary energy consumption by integrating an automated switching off system with load balancing and appliance scheduling algorithm. The load balancing scheme acts according to defined constraints such that the cumulative energy consumption of the household is managed below the defined maximum threshold. The scheduling of appliances adheres to the least slack time (LST) algorithm while considering user comfort during scheduling. The performance of the proposed scheme has been evaluated against an existing energy management scheme through computer simulation. The simulation results have revealed a significant improvement gained through the proposed LST-based energy management scheme in terms of cost of energy, along with reduced domestic energy consumption facilitated by an automated switching off mechanism.

  13. 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.

  14. 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

  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. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. Efficiency Effects of Unit-based Pricing Systems and Institutional Choices of Waste Collection

    NARCIS (Netherlands)

    Dijkgraaf, E.; Gradus, R.H.J.M.

    2015-01-01

    Municipal residential waste costs are rising. Therefore, it is important to introduce measures that lower waste collection and disposal costs. Based on a large panel data set for the Netherlands we show that unit-based pricing systems are more important from a cost-minimizing point of view than the

  2. 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.

  3. 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.

  4. 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.

  5. 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...

  6. Pricing for Higher Education Institutions: A Value-Based Approach

    Science.gov (United States)

    Amir, Amizawati Mohd; Auzair, Sofiah Md; Maelah, Ruhanita; Ahmad, Azlina

    2016-01-01

    Purpose: The purpose of this paper is to propose the concept of higher education institutions (HEIs) offering educational services based on value for money. The value is determined based on customers' (i.e. students) expectations of the service and the costs in comparison to the competitors. Understanding the value and creating customer value are…

  7. 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

  8. Scheduling of head-sensitive cascaded hydro systems : a comparison based on numerical simulation results

    Energy Technology Data Exchange (ETDEWEB)

    Catalao, J.P.S.; Mariano, S.J.P.S. [Beira Interior Univ., Covilha (Portugal). Dept. of Electromechanical Engineering; Mendes, V.M.F. [Superior Engineering Inst. of Lisbon, Lisbon (Portugal). Dept. of Electrical Engineering and Automation; Ferreira, L.A.F.M. [Technical Univ. of Lisbon, Superior Technical Inst., Lisbon (Portugal). Dept. of Electrical Engineering and Computers

    2008-07-01

    The electric power sector in Portugal and Spain has shifted from a traditional monopoly to a deregulated, competitive energy market. As such, hydroelectric facilities face the optimal challenge of how to make a profit by managing water resources without compromising future potential profit. As such, hydro scheduling is a key activity for hydroelectric power utilities because of its significant economic impact. It involves the optimal management of water inflows and storage in reservoirs. This paper considered the problem of short-term hydro scheduling, concerning head-sensitive cascaded reservoirs, and the algorithmic aspects of its solution. The authors proposed and compared optimization methods based on dynamic programming, and linear and nonlinear network programming. The comparison revealed a negligible extra computational effort in a realistic cascaded hydro system where the head depended on the stored water volume. 17 refs., 3 tabs., 7 figs.

  9. Weighted-Bit-Flipping-Based Sequential Scheduling Decoding Algorithms for LDPC Codes

    Directory of Open Access Journals (Sweden)

    Qing Zhu

    2013-01-01

    Full Text Available Low-density parity-check (LDPC codes can be applied in a lot of different scenarios such as video broadcasting and satellite communications. LDPC codes are commonly decoded by an iterative algorithm called belief propagation (BP over the corresponding Tanner graph. The original BP updates all the variable-nodes simultaneously, followed by all the check-nodes simultaneously as well. We propose a sequential scheduling algorithm based on weighted bit-flipping (WBF algorithm for the sake of improving the convergence speed. Notoriously, WBF is a low-complexity and simple algorithm. We combine it with BP to obtain advantages of these two algorithms. Flipping function used in WBF is borrowed to determine the priority of scheduling. Simulation results show that it can provide a good tradeoff between FER performance and computation complexity for short-length LDPC codes.

  10. Cloud computing task scheduling strategy based on differential evolution and ant colony optimization

    Science.gov (United States)

    Ge, Junwei; Cai, Yu; Fang, Yiqiu

    2018-05-01

    This paper proposes a task scheduling strategy DEACO based on the combination of Differential Evolution (DE) and Ant Colony Optimization (ACO), aiming at the single problem of optimization objective in cloud computing task scheduling, this paper combines the shortest task completion time, cost and load balancing. DEACO uses the solution of the DE to initialize the initial pheromone of ACO, reduces the time of collecting the pheromone in ACO in the early, and improves the pheromone updating rule through the load factor. The proposed algorithm is simulated on cloudsim, and compared with the min-min and ACO. The experimental results show that DEACO is more superior in terms of time, cost, and load.

  11. Research on a scheduling mechanism in a complex system based on TOC

    International Nuclear Information System (INIS)

    Wen, Zhang; Ya-Ming, Zhang; Jinbo, Chen; Kaijun, Leng

    2016-01-01

    Under the condition where there is no seasonal demand fluctuation, short life cycle product supply chain should confront the market environment such as the decreasing of product value, the launch of substitutes and the appearance of competitors’ similar products, and the supply chain will become a very complex system. In this paper, the authors consider a TOC-based scheduling mechanism in this complex supply chain system. under the constant total production cost, it is more important to improve the availability of the wanted product in order to enhance the overall supply chain competitiveness so to obtain more effective output(profit rate) for the supply chain in a long period. Especially we try to apply the SDBR concept into a schedule mechanism in a particular supply chain system, and use numerical analysis to test the efficiency of the proposed method.

  12. A Simulated Annealing-Based Heuristic Algorithm for Job Shop Scheduling to Minimize Lateness

    Directory of Open Access Journals (Sweden)

    Rui Zhang

    2013-04-01

    Full Text Available A decomposition-based optimization algorithm is proposed for solving large job shop scheduling problems with the objective of minimizing the maximum lateness. First, we use the constraint propagation theory to derive the orientation of a portion of disjunctive arcs. Then we use a simulated annealing algorithm to find a decomposition policy which satisfies the maximum number of oriented disjunctive arcs. Subsequently, each subproblem (corresponding to a subset of operations as determined by the decomposition policy is successively solved with a simulated annealing algorithm, which leads to a feasible solution to the original job shop scheduling problem. Computational experiments are carried out for adapted benchmark problems, and the results show the proposed algorithm is effective and efficient in terms of solution quality and time performance.

  13. Rolling scheduling of electric power system with wind power based on improved NNIA algorithm

    Science.gov (United States)

    Xu, Q. S.; Luo, C. J.; Yang, D. J.; Fan, Y. H.; Sang, Z. X.; Lei, H.

    2017-11-01

    This paper puts forth a rolling modification strategy for day-ahead scheduling of electric power system with wind power, which takes the operation cost increment of unit and curtailed wind power of power grid as double modification functions. Additionally, an improved Nondominated Neighbor Immune Algorithm (NNIA) is proposed for solution. The proposed rolling scheduling model has further improved the operation cost of system in the intra-day generation process, enhanced the system’s accommodation capacity of wind power, and modified the key transmission section power flow in a rolling manner to satisfy the security constraint of power grid. The improved NNIA algorithm has defined an antibody preference relation model based on equal incremental rate, regulation deviation constraints and maximum & minimum technical outputs of units. The model can noticeably guide the direction of antibody evolution, and significantly speed up the process of algorithm convergence to final solution, and enhance the local search capability.

  14. A Dynamic Resource Scheduling Method Based on Fuzzy Control Theory in Cloud Environment

    Directory of Open Access Journals (Sweden)

    Zhijia Chen

    2015-01-01

    Full Text Available The resources in cloud environment have features such as large-scale, diversity, and heterogeneity. Moreover, the user requirements for cloud computing resources are commonly characterized by uncertainty and imprecision. Hereby, to improve the quality of cloud computing service, not merely should the traditional standards such as cost and bandwidth be satisfied, but also particular emphasis should be laid on some extended standards such as system friendliness. This paper proposes a dynamic resource scheduling method based on fuzzy control theory. Firstly, the resource requirements prediction model is established. Then the relationships between resource availability and the resource requirements are concluded. Afterwards fuzzy control theory is adopted to realize a friendly match between user needs and resources availability. Results show that this approach improves the resources scheduling efficiency and the quality of service (QoS of cloud computing.

  15. Scheduling of head-sensitive cascaded hydro systems : a comparison based on numerical simulation results

    International Nuclear Information System (INIS)

    Catalao, J.P.S.; Mariano, S.J.P.S.; Mendes, V.M.F.; Ferreira, L.A.F.M.

    2008-01-01

    The electric power sector in Portugal and Spain has shifted from a traditional monopoly to a deregulated, competitive energy market. As such, hydroelectric facilities face the optimal challenge of how to make a profit by managing water resources without compromising future potential profit. As such, hydro scheduling is a key activity for hydroelectric power utilities because of its significant economic impact. It involves the optimal management of water inflows and storage in reservoirs. This paper considered the problem of short-term hydro scheduling, concerning head-sensitive cascaded reservoirs, and the algorithmic aspects of its solution. The authors proposed and compared optimization methods based on dynamic programming, and linear and nonlinear network programming. The comparison revealed a negligible extra computational effort in a realistic cascaded hydro system where the head depended on the stored water volume. 17 refs., 3 tabs., 7 figs

  16. 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.

  17. 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

  18. 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.

  19. Forecasting Crude Oil Price Using EEMD and RVM with Adaptive PSO-Based Kernels

    Directory of Open Access Journals (Sweden)

    Taiyong Li

    2016-12-01

    Full Text Available Crude oil, as one of the most important energy sources in the world, plays a crucial role in global economic events. An accurate prediction for crude oil price is an interesting and challenging task for enterprises, governments, investors, and researchers. To cope with this issue, in this paper, we proposed a method integrating ensemble empirical mode decomposition (EEMD, adaptive particle swarm optimization (APSO, and relevance vector machine (RVM—namely, EEMD-APSO-RVM—to predict crude oil price based on the “decomposition and ensemble” framework. Specifically, the raw time series of crude oil price were firstly decomposed into several intrinsic mode functions (IMFs and one residue by EEMD. Then, RVM with combined kernels was applied to predict target value for the residue and each IMF individually. To improve the prediction performance of each component, an extended particle swarm optimization (PSO was utilized to simultaneously optimize the weights and parameters of single kernels for the combined kernel of RVM. Finally, simple addition was used to aggregate all the predicted results of components into an ensemble result as the final result. Extensive experiments were conducted on the crude oil spot price of the West Texas Intermediate (WTI to illustrate and evaluate the proposed method. The experimental results are superior to those by several state-of-the-art benchmark methods in terms of root mean squared error (RMSE, mean absolute percent error (MAPE, and directional statistic (Dstat, showing that the proposed EEMD-APSO-RVM is promising for forecasting crude oil price.

  20. Research on the factors influencing the price of commercial housing based on support vector machine (SVM)

    Science.gov (United States)

    Xiaoyang, Zhong; Hong, Ren; Jingxin, Gao

    2018-03-01

    With the gradual maturity of the real estate market in China, urban housing prices are also better able to reflect changes in market demand and the commodity property of commercial housing has become more and more obvious. Many scholars in our country have made a lot of research on the factors that affect the price of commercial housing in the city and the number of related research papers increased rapidly. These scholars’ research results provide valuable wealth to solve the problem of urban housing price changes in our country. However, due to the huge amount of literature, the vast amount of information is submerged in the library and cannot be fully utilized. Text mining technology has been widely concerned and developed in the field of Humanities and Social Sciences in recent years. But through the text mining technology to obtain the influence factors on the price of urban commercial housing is still relatively rare. In this paper, the research results of the existing scholars were excavated by text mining algorithm based on support vector machine in order to further make full use of the current research results and to provide a reference for stabilizing housing prices.

  1. 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.

  2. Distributed project scheduling at NASA: Requirements for manual protocols and computer-based support

    Science.gov (United States)

    Richards, Stephen F.

    1992-01-01

    The increasing complexity of space operations and the inclusion of interorganizational and international groups in the planning and control of space missions lead to requirements for greater communication, coordination, and cooperation among mission schedulers. These schedulers must jointly allocate scarce shared resources among the various operational and mission oriented activities while adhering to all constraints. This scheduling environment is complicated by such factors as the presence of varying perspectives and conflicting objectives among the schedulers, the need for different schedulers to work in parallel, and limited communication among schedulers. Smooth interaction among schedulers requires the use of protocols that govern such issues as resource sharing, authority to update the schedule, and communication of updates. This paper addresses the development and characteristics of such protocols and their use in a distributed scheduling environment that incorporates computer-aided scheduling tools. An example problem is drawn from the domain of Space Shuttle mission planning.

  3. 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.

  4. 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.

  5. 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.

  6. 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...

  7. 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.

  8. 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.

  9. 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.

  10. 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...

  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. 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.

  13. Harem: Hardwood lumber remanufacturing program for maxmizing value based on size, grade and current market prices

    Science.gov (United States)

    C.J. Schwehm; P. Klinkhachorn; Charles W. McMillin; Henry A. Huber

    1990-01-01

    This paper describes an expert system computer program which will determine the optimum way to edge and trim a hardwood board so as to yield the highest dollar value based on the grade, size of each board, and current market prices. The program uses the Automated Hardwood Lumber Grading Program written by Klinkhachorn, et al. for determining the grade of each board...

  14. 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

  15. Renewable Energy for Electric Vehicles : Price Based Charging Coordination

    NARCIS (Netherlands)

    Richstein, J.C.; Schuller, A.; Dinther, C.; Ketter, W.; Weinhardt, C.

    2012-01-01

    In this paper we investigate the charging coordination of battery electric vehicles (BEV) with respect to the availability of intermittent renewable energy generation considering individual real world driving profiles in a deterministic simulation based analysis, mapping a part of the German power

  16. Online Dynamic Balance Technology for High Speed Spindle Based on Gain Parameter Adaption and Scheduling Control

    Directory of Open Access Journals (Sweden)

    Shihai Zhang

    2018-06-01

    Full Text Available Unbalance vibration is one of the main vibration forms of a high speed machine tool spindle. The overlarge unbalance vibration will have some adverse effects on the working life of the spindle system and the surface quality of the work-piece. In order to reduce the unbalance of a high speed spindle system, a pneumatic online dynamic balance device and its control system are presented in the paper. To improve the balance accuracy and adaptation of the balance system, the gain parameter adaption and scheduling control method are proposed first, and then the different balance effects of the influence coefficient method and the gain scheduling control method are compared through many dynamic balance experiments of the high speed spindle. The experimental results indicate that the gain parameters can be changed timely according to the transformation of the speed and kinetic parameters of the spindle system. The balance accuracy can be improved for a high speed spindle with time-varying characteristics, based on the adaptive gain scheduling control method.

  17. 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.

  18. Threshold Based Opportunistic Scheduling of Secondary Users in Underlay Cognitive Radio Networks

    KAUST Repository

    Song, Yao

    2011-12-01

    In underlay cognitive radio networks, secondary users can share the spectrum with primary users as long as the interference caused by the secondary users to primary users is below a certain predetermined threshold. It is reasonable to assume that there is always a large pool of secondary users trying to access the channel, which can be occupied by only one secondary user at a given time. As a result, a multi-user scheduling problem arises among the secondary users. In this thesis, by manipulating basic schemes based on selective multi-user diversity, normalized thresholding, transmission power control, and opportunistic round robin, we propose and analyze eight scheduling schemes of secondary users in an underlay cognitive radio set-up. The system performance of these schemes is quantified by using various performance metrics such as the average system capacity, normalized average feedback load, scheduling outage probability, and system fairness of access. In our proposed schemes, the best user out of all the secondary users in the system is picked to transmit at each given time slot in order to maximize the average system capacity. Two thresholds are used in the two rounds of the selection process to determine the best user. The first threshold is raised by the power constraint from the primary user. The second threshold, which can be adjusted by us, is introduced to reduce the feedback load. The overall system performance is therefore dependent on the choice of these two thresholds and the number of users in the system given the channel conditions for all the users. In this thesis, by deriving analytical formulas and presenting numerical examples, we try to provide insights of the relationship between the performance metrics and the involved parameters including two selection thresholds and the number of active users in the system, in an effort to maximize the average system capacity as well as satisfy the requirements of scheduling outage probability and

  19. Earthquake insurance pricing: a risk-based approach.

    Science.gov (United States)

    Lin, Jeng-Hsiang

    2018-04-01

    Flat earthquake premiums are 'uniformly' set for a variety of buildings in many countries, neglecting the fact that the risk of damage to buildings by earthquakes is based on a wide range of factors. How these factors influence the insurance premiums is worth being studied further. Proposed herein is a risk-based approach to estimate the earthquake insurance rates of buildings. Examples of application of the approach to buildings located in Taipei city of Taiwan were examined. Then, the earthquake insurance rates for the buildings investigated were calculated and tabulated. To fulfil insurance rating, the buildings were classified into 15 model building types according to their construction materials and building height. Seismic design levels were also considered in insurance rating in response to the effect of seismic zone and construction years of buildings. This paper may be of interest to insurers, actuaries, and private and public sectors of insurance. © 2018 The Author(s). Disasters © Overseas Development Institute, 2018.

  20. Price Formation Based on Particle-Cluster Aggregation

    Science.gov (United States)

    Wang, Shijun; Zhang, Changshui

    In the present work, we propose a microscopic model of financial markets based on particle-cluster aggregation on a two-dimensional small-world information network in order to simulate the dynamics of the stock markets. "Stylized facts" of the financial market time series, such as fat-tail distribution of returns, volatility clustering and multifractality, are observed in the model. The results of the model agree with empirical data taken from historical records of the daily closures of the NYSE composite index.

  1. 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.

  2. 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.

  3. Ant colony optimization and event-based dynamic task scheduling and staffing for software projects

    Science.gov (United States)

    Ellappan, Vijayan; Ashwini, J.

    2017-11-01

    In programming change organizations from medium to inconceivable scale broadens, the issue of wander orchestrating is amazingly unusual and testing undertaking despite considering it a manual system. Programming wander-organizing requirements to deal with the issue of undertaking arranging and in addition the issue of human resource portion (also called staffing) in light of the way that most of the advantages in programming ventures are individuals. We propose a machine learning approach with finds respond in due order regarding booking by taking in the present arranging courses of action and an event based scheduler revives the endeavour arranging system moulded by the learning computation in perspective of the conformity in event like the begin with the Ander, the instant at what time possessions be free starting to ended errands, and the time when delegates stick together otherwise depart the wander inside the item change plan. The route toward invigorating the timetable structure by the even based scheduler makes the arranging method dynamic. It uses structure components to exhibit the interrelated surges of endeavours, slip-ups and singular all through different progression organizes and is adjusted to mechanical data. It increases past programming wander movement ask about by taking a gander at a survey based process with a one of a kind model, organizing it with the data based system for peril assessment and cost estimation, and using a choice showing stage.

  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. 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)

  6. 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.

  7. A Genetic Algorithm-based Heuristic for Part-Feeding Mobile Robot Scheduling Problem

    DEFF Research Database (Denmark)

    Dang, Vinh Quang; Nielsen, Izabela Ewa; Bocewicz, Grzegorz

    2012-01-01

    This present study deals with the problem of sequencing feeding tasks of a single mobile robot with manipulation arm which is able to provide parts or components for feeders of machines in a manufacturing cell. The mobile robot has to be scheduled in order to keep machines within the cell producing...... products without any shortage of parts. A method based on the characteristics of feeders and inspired by the (s, Q) inventory system, is thus applied to define time windows for feeding tasks of the robot. The performance criterion is to minimize total traveling time of the robot in a given planning horizon...

  8. Reliability-based optimization of maintenance scheduling of mechanical components under fatigue

    Science.gov (United States)

    Beaurepaire, P.; Valdebenito, M.A.; Schuëller, G.I.; Jensen, H.A.

    2012-01-01

    This study presents the optimization of the maintenance scheduling of mechanical components under fatigue loading. The cracks of damaged structures may be detected during non-destructive inspection and subsequently repaired. Fatigue crack initiation and growth show inherent variability, and as well the outcome of inspection activities. The problem is addressed under the framework of reliability based optimization. The initiation and propagation of fatigue cracks are efficiently modeled using cohesive zone elements. The applicability of the method is demonstrated by a numerical example, which involves a plate with two holes subject to alternating stress. PMID:23564979

  9. Application of genetic algorithms to the maintenance scheduling optimization in a nuclear system basing on reliability

    International Nuclear Information System (INIS)

    Lapa, Celso M. Franklin; Pereira, Claudio M.N.A.; Mol, Antonio C. de Abreu

    1999-01-01

    This paper presents a solution based on genetic algorithm and probabilistic safety analysis that can be applied in the optimization of the preventive maintenance politic of nuclear power plant safety systems. The goal of this approach is to improve the average availability of the system through the optimization of the preventive maintenance scheduling politic. The auxiliary feed water system of a two loops pressurized water reactor is used as a sample case, in order to demonstrate the effectiveness of the proposed method. The results, when compared to those obtained by some standard maintenance politics, reveal quantitative gains and operational safety levels. (author)

  10. Self-Adaptive Operator Scheduling using the Religion-Based EA

    DEFF Research Database (Denmark)

    Thomsen, Rene; Krink, Thiemo

    2002-01-01

    of their application is determined by a constant parameter, such as a fixed mutation rate. However, recent studies have shown that the optimal usage of a variation operator changes during the EA run. In this study, we combined the idea of self-adaptive mutation operator scheduling with the Religion-Based EA (RBEA......), which is an agent model with spatially structured and variable sized subpopulations (religions). In our new model (OSRBEA), we used a selection of different operators, such that each operator type was applied within one specific subpopulation only. Our results indicate that the optimal choice...

  11. 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.

  12. An Effective Scheduling-Based RFID Reader Collision Avoidance Model and Its Resource Allocation via Artificial Immune Network

    OpenAIRE

    Wang, Shanjin; Li, Zhonghua; He, Chunhui; Li, Jianming

    2016-01-01

    Radio frequency identification, that is, RFID, is one of important technologies in Internet of Things. Reader collision does impair the tag identification efficiency of an RFID system. Many developed methods, for example, the scheduling-based series, that are used to avoid RFID reader collision, have been developed. For scheduling-based methods, communication resources, that is, time slots, channels, and power, are optimally assigned to readers. In this case, reader collision avoidance is equ...

  13. Agent-Based Model of Price Competition and Product Differentiation on Congested Networks

    OpenAIRE

    Lei Zhang; David Levinson; Shanjiang Zhu

    2007-01-01

    Using consistent agent-based techniques, this research models the decision-making processes of users and infrastructure owner/operators to explore the welfare consequence of price competition, capacity choice, and product differentiation on congested transportation networks. Component models include: (1) An agent-based travel demand model wherein each traveler has learning capabilities and unique characteristics (e.g. value of time); (2) Econometric facility provision cost models; and (3) Rep...

  14. 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.

  15. Efficient Power Scheduling in Smart Homes Using Hybrid Grey Wolf Differential Evolution Optimization Technique with Real Time and Critical Peak Pricing Schemes

    Directory of Open Access Journals (Sweden)

    Muqaddas Naz

    2018-02-01

    Full Text Available With the emergence of automated environments, energy demand by consumers is increasing rapidly. More than 80% of total electricity is being consumed in the residential sector. This brings a challenging task of maintaining the balance between demand and generation of electric power. In order to meet such challenges, a traditional grid is renovated by integrating two-way communication between the consumer and generation unit. To reduce electricity cost and peak load demand, demand side management (DSM is modeled as an optimization problem, and the solution is obtained by applying meta-heuristic techniques with different pricing schemes. In this paper, an optimization technique, the hybrid gray wolf differential evolution (HGWDE, is proposed by merging enhanced differential evolution (EDE and gray wolf optimization (GWO scheme using real-time pricing (RTP and critical peak pricing (CPP. Load shifting is performed from on-peak hours to off-peak hours depending on the electricity cost defined by the utility. However, there is a trade-off between user comfort and cost. To validate the performance of the proposed algorithm, simulations have been carried out in MATLAB. Results illustrate that using RTP, the peak to average ratio (PAR is reduced to 53.02%, 29.02% and 26.55%, while the electricity bill is reduced to 12.81%, 12.012% and 12.95%, respectively, for the 15-, 30- and 60-min operational time interval (OTI. On the other hand, the PAR and electricity bill are reduced to 47.27%, 22.91%, 22% and 13.04%, 12%, 11.11% using the CPP tariff.

  16. MODELLING TEMPORAL SCHEDULE OF URBAN TRAINS USING AGENT-BASED SIMULATION AND NSGA2-BASED MULTIOBJECTIVE OPTIMIZATION APPROACHES

    Directory of Open Access Journals (Sweden)

    M. Sahelgozin

    2015-12-01

    Full Text Available Increasing distances between locations of residence and services leads to a large number of daily commutes in urban areas. Developing subway systems has been taken into consideration of transportation managers as a response to this huge amount of travel demands. In developments of subway infrastructures, representing a temporal schedule for trains is an important task; because an appropriately designed timetable decreases Total passenger travel times, Total Operation Costs and Energy Consumption of trains. Since these variables are not positively correlated, subway scheduling is considered as a multi-criteria optimization problem. Therefore, proposing a proper solution for subway scheduling has been always a controversial issue. On the other hand, research on a phenomenon requires a summarized representation of the real world that is known as Model. In this study, it is attempted to model temporal schedule of urban trains that can be applied in Multi-Criteria Subway Schedule Optimization (MCSSO problems. At first, a conceptual framework is represented for MCSSO. Then, an agent-based simulation environment is implemented to perform Sensitivity Analysis (SA that is used to extract the interrelations between the framework components. These interrelations is then taken into account in order to construct the proposed model. In order to evaluate performance of the model in MCSSO problems, Tehran subway line no. 1 is considered as the case study. Results of the study show that the model was able to generate an acceptable distribution of Pareto-optimal solutions which are applicable in the real situations while solving a MCSSO is the goal. Also, the accuracy of the model in representing the operation of subway systems was significant.

  17. 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.

  18. 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.

  19. 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

  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. Effective Task Scheduling and IP Mapping Algorithm for Heterogeneous NoC-Based MPSoC

    Directory of Open Access Journals (Sweden)

    Peng-Fei Yang

    2014-01-01

    Full Text Available Quality of task scheduling is critical to define the network communication efficiency and the performance of the entire NoC- (Network-on-Chip- based MPSoC (multiprocessor System-on-Chip. In this paper, the NoC-based MPSoC design process is favorably divided into two steps, that is, scheduling subtasks to processing elements (PEs of appropriate type and quantity and then mapping these PEs onto the switching nodes of NoC topology. When the task model is improved so that it reflects better the real intertask relations, optimized particle swarm optimization (PSO is utilized to achieve the first step with expected less task running and transfer cost as well as the least task execution time. By referring to the topology of NoC and the resultant communication diagram of the first step, the second step is done with the minimal expected network transmission delay as well as less resource consumption and even power consumption. The comparative experiments have shown the preferable resource and power consumption of the algorithm when it is actually adopted in a system design.

  2. An Agent-Based Solution Framework for Inter-Block Yard Crane Scheduling Problems

    Directory of Open Access Journals (Sweden)

    Omor Sharif

    2012-06-01

    Full Text Available The efficiency of yard operations is critical to the overall productivity of a container terminal because the yard serves as the interface between the landside and waterside operations. Most container terminals use yard cranes to transfer containers between the yard and trucks (both external and internal. To facilitate vessel operations, an efficient work schedule for the yard cranes is necessary given varying work volumes among yard blocks with different planning periods. This paper investigated an agent-based approach to assign and relocate yard cranes among yard blocks based on the forecasted work volumes. The goal of our study is to reduce the work volume that remains incomplete at the end of a planning period. We offered several preference functions for yard cranes and blocks which are modeled as agents. These preference functions are designed to find effective schedules for yard cranes. In addition, we examined various rules for the initial assignment of yard cranes to blocks. Our analysis demonstrated that our model can effectively and efficiently reduce the percentage of incomplete work volume for any real-world sized problem.

  3. Stochastic User Equilibrium Assignment in Schedule-Based Transit Networks with Capacity Constraints

    Directory of Open Access Journals (Sweden)

    Wangtu Xu

    2012-01-01

    Full Text Available This paper proposes a stochastic user equilibrium (SUE assignment model for a schedule-based transit network with capacity constraint. We consider a situation in which passengers do not have the full knowledge about the condition of the network and select paths that minimize a generalized cost function encompassing five components: (1 ride time, which is composed of in-vehicle and waiting times, (2 overload delay, (3 fare, (4 transfer constraints, and (5 departure time difference. We split passenger demands among connections which are the space-time paths between OD pairs of the network. All transit vehicles have a fixed capacity and operate according to some preset timetables. When the capacity constraint of the transit line segment is reached, we show that the Lagrange multipliers of the mathematical programming problem are equivalent to the equilibrium passenger overload delay in the congested transit network. The proposed model can simultaneously predict how passengers choose their transit vehicles to minimize their travel costs and estimate the associated costs in a schedule-based congested transit network. A numerical example is used to illustrate the performance of the proposed model.

  4. A QoS-Based Dynamic Queue Length Scheduling Algorithm in Multiantenna Heterogeneous Systems

    Directory of Open Access Journals (Sweden)

    Verikoukis Christos

    2010-01-01

    Full Text Available The use of real-time delay-sensitive applications in wireless systems has significantly grown during the last years. Therefore the designers of wireless systems have faced a challenging issue to guarantee the required Quality of Service (QoS. On the other hand, the recent advances and the extensive use of multiple antennas have already been included in several commercial standards, where the multibeam opportunistic transmission beamforming strategies have been proposed to improve the performance of the wireless systems. A cross-layer-based dynamically tuned queue length scheduler is presented in this paper, for the Downlink of multiuser and multiantenna WLAN systems with heterogeneous traffic requirements. To align with modern wireless systems transmission strategies, an opportunistic scheduling algorithm is employed, while a priority to the different traffic classes is applied. A tradeoff between the maximization of the throughput of the system and the guarantee of the maximum allowed delay is obtained. Therefore, the length of the queue is dynamically adjusted to select the appropriate conditions based on the operator requirements.

  5. A multipopulation PSO based memetic algorithm for permutation flow shop scheduling.

    Science.gov (United States)

    Liu, Ruochen; Ma, Chenlin; Ma, Wenping; Li, Yangyang

    2013-01-01

    The permutation flow shop scheduling problem (PFSSP) is part of production scheduling, which belongs to the hardest combinatorial optimization problem. In this paper, a multipopulation particle swarm optimization (PSO) based memetic algorithm (MPSOMA) is proposed in this paper. In the proposed algorithm, the whole particle swarm population is divided into three subpopulations in which each particle evolves itself by the standard PSO and then updates each subpopulation by using different local search schemes such as variable neighborhood search (VNS) and individual improvement scheme (IIS). Then, the best particle of each subpopulation is selected to construct a probabilistic model by using estimation of distribution algorithm (EDA) and three particles are sampled from the probabilistic model to update the worst individual in each subpopulation. The best particle in the entire particle swarm is used to update the global optimal solution. The proposed MPSOMA is compared with two recently proposed algorithms, namely, PSO based memetic algorithm (PSOMA) and hybrid particle swarm optimization with estimation of distribution algorithm (PSOEDA), on 29 well-known PFFSPs taken from OR-library, and the experimental results show that it is an effective approach for the PFFSP.

  6. A Multipopulation PSO Based Memetic Algorithm for Permutation Flow Shop Scheduling

    Directory of Open Access Journals (Sweden)

    Ruochen Liu

    2013-01-01

    Full Text Available The permutation flow shop scheduling problem (PFSSP is part of production scheduling, which belongs to the hardest combinatorial optimization problem. In this paper, a multipopulation particle swarm optimization (PSO based memetic algorithm (MPSOMA is proposed in this paper. In the proposed algorithm, the whole particle swarm population is divided into three subpopulations in which each particle evolves itself by the standard PSO and then updates each subpopulation by using different local search schemes such as variable neighborhood search (VNS and individual improvement scheme (IIS. Then, the best particle of each subpopulation is selected to construct a probabilistic model by using estimation of distribution algorithm (EDA and three particles are sampled from the probabilistic model to update the worst individual in each subpopulation. The best particle in the entire particle swarm is used to update the global optimal solution. The proposed MPSOMA is compared with two recently proposed algorithms, namely, PSO based memetic algorithm (PSOMA and hybrid particle swarm optimization with estimation of distribution algorithm (PSOEDA, on 29 well-known PFFSPs taken from OR-library, and the experimental results show that it is an effective approach for the PFFSP.

  7. Drug scheduling of cancer chemotherapy based on natural actor-critic approach.

    Science.gov (United States)

    Ahn, Inkyung; Park, Jooyoung

    2011-11-01

    Recently, reinforcement learning methods have drawn significant interests in the area of artificial intelligence, and have been successfully applied to various decision-making problems. In this paper, we study the applicability of the NAC (natural actor-critic) approach, a state-of-the-art reinforcement learning method, to the drug scheduling of cancer chemotherapy for an ODE (ordinary differential equation)-based tumor growth model. ODE-based cancer dynamics modeling is an active research area, and many different mathematical models have been proposed. Among these, we use the model proposed by de Pillis and Radunskaya (2003), which considers the growth of tumor cells and their interaction with normal cells and immune cells. The NAC approach is applied to this ODE model with the goal of minimizing the tumor cell population and the drug amount while maintaining the adequate population levels of normal cells and immune cells. In the framework of the NAC approach, the drug dose is regarded as the control input, and the reward signal is defined as a function of the control input and the cell populations of tumor cells, normal cells, and immune cells. According to the control policy found by the NAC approach, effective drug scheduling in cancer chemotherapy for the considered scenarios has turned out to be close to the strategy of continuing drug injection from the beginning until an appropriate time. Also, simulation results showed that the NAC approach can yield better performance than conventional pulsed chemotherapy. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  8. Energy-saving scheme based on downstream packet scheduling in ethernet passive optical networks

    Science.gov (United States)

    Zhang, Lincong; Liu, Yejun; Guo, Lei; Gong, Xiaoxue

    2013-03-01

    With increasing network sizes, the energy consumption of Passive Optical Networks (PONs) has grown significantly. Therefore, it is important to design effective energy-saving schemes in PONs. Generally, energy-saving schemes have focused on sleeping the low-loaded Optical Network Units (ONUs), which tends to bring large packet delays. Further, the traditional ONU sleep modes are not capable of sleeping the transmitter and receiver independently, though they are not required to transmit or receive packets. Clearly, this approach contributes to wasted energy. Thus, in this paper, we propose an Energy-Saving scheme that is based on downstream Packet Scheduling (ESPS) in Ethernet PON (EPON). First, we design both an algorithm and a rule for downstream packet scheduling at the inter- and intra-ONU levels, respectively, to reduce the downstream packet delay. After that, we propose a hybrid sleep mode that contains not only ONU deep sleep mode but also independent sleep modes for the transmitter and the receiver. This ensures that the energy consumed by the ONUs is minimal. To realize the hybrid sleep mode, a modified GATE control message is designed that involves 10 time points for sleep processes. In ESPS, the 10 time points are calculated according to the allocated bandwidths in both the upstream and the downstream. The simulation results show that ESPS outperforms traditional Upstream Centric Scheduling (UCS) scheme in terms of energy consumption and the average delay for both real-time and non-real-time packets downstream. The simulation results also show that the average energy consumption of each ONU in larger-sized networks is less than that in smaller-sized networks; hence, our ESPS is better suited for larger-sized networks.

  9. Improved teaching-learning-based and JAYA optimization algorithms for solving flexible flow shop scheduling problems

    Science.gov (United States)

    Buddala, Raviteja; Mahapatra, Siba Sankar

    2017-11-01

    Flexible flow shop (or a hybrid flow shop) scheduling problem is an extension of classical flow shop scheduling problem. In a simple flow shop configuration, a job having `g' operations is performed on `g' operation centres (stages) with each stage having only one machine. If any stage contains more than one machine for providing alternate processing facility, then the problem becomes a flexible flow shop problem (FFSP). FFSP which contains all the complexities involved in a simple flow shop and parallel machine scheduling problems is a well-known NP-hard (Non-deterministic polynomial time) problem. Owing to high computational complexity involved in solving these problems, it is not always possible to obtain an optimal solution in a reasonable computation time. To obtain near-optimal solutions in a reasonable computation time, a large variety of meta-heuristics have been proposed in the past. However, tuning algorithm-specific parameters for solving FFSP is rather tricky and time consuming. To address this limitation, teaching-learning-based optimization (TLBO) and JAYA algorithm are chosen for the study because these are not only recent meta-heuristics but they do not require tuning of algorithm-specific parameters. Although these algorithms seem to be elegant, they lose solution diversity after few iterations and get trapped at the local optima. To alleviate such drawback, a new local search procedure is proposed in this paper to improve the solution quality. Further, mutation strategy (inspired from genetic algorithm) is incorporated in the basic algorithm to maintain solution diversity in the population. Computational experiments have been conducted on standard benchmark problems to calculate makespan and computational time. It is found that the rate of convergence of TLBO is superior to JAYA. From the results, it is found that TLBO and JAYA outperform many algorithms reported in the literature and can be treated as efficient methods for solving the FFSP.

  10. 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

  11. Efficient Pricing of European-Style Asian Options under Exponential Lévy Processes Based on Fourier Cosine Expansions

    NARCIS (Netherlands)

    Zhang, B.; Oosterlee, C.W.

    2013-01-01

    We propose an efficient pricing method for arithmetic and geometric Asian options under exponential Lévy processes based on Fourier cosine expansions and Clenshaw–Curtis quadrature. The pricing method is developed for both European style and American-style Asian options and for discretely and

  12. Price Conduction Mechanism of China’s Wheat Industry Chain Based on VECM

    OpenAIRE

    ZHU, Haiyan

    2015-01-01

    With the aid of the VECM (vector error correction model), this paper studied dynamic effect of wheat price and flour price conduction mechanism in the wheat industry chain. Study results indicate that in a long term, wheat price and flour price have equilibrium relationship. Through threshold co-integration test, it found that there is no threshold co-integration relationship between wheat price and flour price. This can be adjusted using the linear error correction mode (LECM). In a short te...

  13. 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.

  14. 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

  15. 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.

  16. A simple rule based model for scheduling farm management operations in SWAT

    Science.gov (United States)

    Schürz, Christoph; Mehdi, Bano; Schulz, Karsten

    2016-04-01

    For many interdisciplinary questions at the watershed scale, the Soil and Water Assessment Tool (SWAT; Arnold et al., 1998) has become an accepted and widely used tool. Despite its flexibility, the model is highly demanding when it comes to input data. At SWAT's core the water balance and the modeled nutrient cycles are plant growth driven (implemented with the EPIC crop growth model). Therefore, land use and crop data with high spatial and thematic resolution, as well as detailed information on cultivation and farm management practices are required. For many applications of the model however, these data are unavailable. In order to meet these requirements, SWAT offers the option to trigger scheduled farm management operations by applying the Potential Heat Unit (PHU) concept. The PHU concept solely takes into account the accumulation of daily mean temperature for management scheduling. Hence, it contradicts several farming strategies that take place in reality; such as: i) Planting and harvesting dates are set much too early or too late, as the PHU concept is strongly sensitivity to inter-annual temperature fluctuations; ii) The timing of fertilizer application, in SWAT this often occurs simultaneously on the same date in in each field; iii) and can also coincide with precipitation events. Particularly, the latter two can lead to strong peaks in modeled nutrient loads. To cope with these shortcomings we propose a simple rule based model (RBM) to schedule management operations according to realistic farmer management practices in SWAT. The RBM involves simple strategies requiring only data that are input into the SWAT model initially, such as temperature and precipitation data. The user provides boundaries of time periods for operation schedules to take place for all crops in the model. These data are readily available from the literature or from crop variety trials. The RBM applies the dates by complying with the following rules: i) Operations scheduled in the

  17. The bases for optimisation of scheduled repairs and tests of safety systems to improve the NPP productive efficiency

    International Nuclear Information System (INIS)

    Bilej, D.V.; Vasil'chenko, S.V.; Vlasenko, N.I.; Vasil'chenko, V.N.; Skalozubov, V.I.

    2004-01-01

    In the frames of risk-informed approaches the paper proposed the theoretical bases for methods of optimisation of scheduled repairs and tests of safety systems at nuclear power plants. The optimisation criterion is the objective risk function minimising. This function depends on the scheduled repairs/tests periodicity and the allowed time to bring the system channel to a state of non-operability. The main optimisation direct is to reduce the repair time with the purpose of enhancement of productive efficiency

  18. A Novel Energy Efficient Topology Control Scheme Based on a Coverage-Preserving and Sleep Scheduling Model for Sensor Networks

    OpenAIRE

    Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng

    2016-01-01

    In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical d...

  19. 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...

  20. Emergence of Opinion Leaders Based on Agent Model and Its Impact to Stock Prices

    Science.gov (United States)

    Misawa, Tadanobu; Suzuki, Kyoko; Okano, Yoshitaka; Shimokawa, Tetsuya

    Recently, we can be able to get a lot of information easily because information technology has been developed. Therefore, it is thought that the impact to a society by communication of information such as word of mouth has been growing. In this paper, we propose a model of emergence of opinion leader based on word of mouth in artificial stock market. Moreover, the process of emergence of opinion leader and impact to stock prices by opinion leader are verified by simulation.

  1. Perceived benefits of adopting Standard – Based pricing mechanism for mechanical and electrical services installations

    OpenAIRE

    Ganiyu Amuda Yusuf; Sarajul Fikri Mohamed

    2014-01-01

    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 meth...

  2. Transfer Pricing In Transnational Operations: A Case- And Literature-Based Analysis

    OpenAIRE

    Virginia A. Taylor; E.J. (Roy) Knaus; William E. Matthews

    2011-01-01

    This paper represents a combined case- and literature-based analysis of transnational pricing and highlights the difference in the issues and perspectives of the business and academic environments. Following an introduction to the issue (noting the growing importance of the transfer of goods from one organizational entity to another within a multinational firm), a short case - The Henderson Company - illustrates how a relatively simple announcement can lead to a lengthy and heated discussion ...

  3. 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.

  4. A Reputation-based Distributed District Scheduling Algorithm for Smart Grids

    Directory of Open Access Journals (Sweden)

    D. Borra

    2015-05-01

    Full Text Available In this paper we develop and test a distributed algorithm providing Energy Consumption Schedules (ECS in smart grids for a residential district. The goal is to achieve a given aggregate load prole. The NP-hard constrained optimization problem reduces to a distributed unconstrained formulation by means of Lagrangian Relaxation technique, and a meta-heuristic algorithm based on a Quantum inspired Particle Swarm with Levy flights. A centralized iterative reputation-reward mechanism is proposed for end-users to cooperate to avoid power peaks and reduce global overload, based on random distributions simulating human behaviors and penalties on the eective ECS diering from the suggested ECS. Numerical results show the protocols eectiveness.

  5. A novel integrated condition-based maintenance and stochastic flexible job shop scheduling problem

    DEFF Research Database (Denmark)

    Rahmati, Seyed Habib A.; Ahmadi, Abbas; Govindan, Kannan

    2018-01-01

    the level of the system optimization. By means of this equipment, managers can benefit from a condition-based maintenance (CBM) for monitoring and managing their system. The chief aim of the paper is to develop a stochastic maintenance problem based on CBM activities engaged with a complex applied......Integrated consideration of production planning and maintenance processes is a real world assumption. Specifically, by improving the monitoring equipment such as various sensors or product-embedded information devices in recent years, joint assessment of these processes is inevitable for enhancing...... production problem called flexible job shop scheduling problem (FJSP). This integrated problem considers two maintenance scenarios in terms of corrective maintenance (CM) and preventive maintenance (PM). The activation of scenario is done by monitoring the degradation condition of the system and comparing...

  6. Culture belief based multi-objective hybrid differential evolutionary algorithm in short term hydrothermal scheduling

    International Nuclear Information System (INIS)

    Zhang Huifeng; Zhou Jianzhong; Zhang Yongchuan; Lu Youlin; Wang Yongqiang

    2013-01-01

    Highlights: ► Culture belief is integrated into multi-objective differential evolution. ► Chaotic sequence is imported to improve evolutionary population diversity. ► The priority of convergence rate is proved in solving hydrothermal problem. ► The results show the quality and potential of proposed algorithm. - Abstract: A culture belief based multi-objective hybrid differential evolution (CB-MOHDE) is presented to solve short term hydrothermal optimal scheduling with economic emission (SHOSEE) problem. This problem is formulated for compromising thermal cost and emission issue while considering its complicated non-linear constraints with non-smooth and non-convex characteristics. The proposed algorithm integrates a modified multi-objective differential evolutionary algorithm into the computation model of culture algorithm (CA) as well as some communication protocols between population space and belief space, three knowledge structures in belief space are redefined according to these problem-solving characteristics, and in the differential evolution a chaotic factor is embedded into mutation operator for avoiding the premature convergence by enlarging the search scale when the search trajectory reaches local optima. Furthermore, a new heuristic constraint-handling technique is utilized to handle those complex equality and inequality constraints of SHOSEE problem. After the application on hydrothermal scheduling system, the efficiency and stability of the proposed CB-MOHDE is verified by its more desirable results in comparison to other method established recently, and the simulation results also reveal that CB-MOHDE can be a promising alternative for solving SHOSEE.

  7. Broadcast Scheduling Strategy Based on the Priority of Real- Time Data in a Mobile Environment

    Institute of Scientific and Technical Information of China (English)

    Yang Jin-cai; Liu Yun-sheng

    2003-01-01

    Data broadcast is an important data dissemina-tion approach in mobile environment. On broadcast channel,scalability and efficiency of data transmission are satisfied. In a mobile environment, there exists a kind of real-time data-base application in which both the transactions and data can have their timing constraints and priorities of different levels.In order to meet the requirement of real-time data dissemina-ting and retrieving, a broadcast scheduling strategy HPF-ED F(Highest Priority First with Earlier Deadline and Frequen-cy) is proposed under the BoD (Broadcast on Demand) mod-el. Using the strategy, data items are scheduled according to their priority the transaction imposed on them or system set for them. The strategy also considers other characteristics ofdata items such as deadline and popularity of data. The exten-sive simulation experiments have been conducted to evaluate the performance of the proposed algorithm. Results show that it can achieve excellent performance compared with existing strategies.

  8. Correlation between Chinese and international energy prices based on a HP filter and time difference analysis

    International Nuclear Information System (INIS)

    He, Yongxiu; Wang, Bing; Wang, Jianhui; Xiong, Wei; Xia, Tian

    2013-01-01

    To establish a reasonable system and mechanism for Chinese energy prices, we use the Granger causality test, Hodrick–Prescott (HP) filter and time difference analysis to research the pricing relationship between Chinese and international energy prices. We find that Chinese and international crude oil prices changed synchronously while Chinese refined oil prices follow the changes of international oil prices with the time difference being about 1 month to 2 months. Further, Australian coal prices Granger causes Chinese coal prices, and there is a high correlation between them. The U.S. electricity price is influenced by the WTI crude oil price, the U.S. gasoline price and the HenryHub gas price. Due to the unreasonable price-setting mechanism and regulation from the central government, China′s terminal market prices for both electricity and natural gas do not reflect the real supply–demand situation. This paper provides quantitative results on the correlation between Chinese and international energy prices to better predict the impact of international energy price fluctuations on China′s domestic energy supply and guide the design of more efficient energy pricing policies. Moreover, it provides references for developing countries to improve their energy market systems and trading, and to coordinate domestic and international energy markets. -- Highlights: •The Hodrick-Prescott filter and time difference analysis are used to research the correlation among energy prices. •Our study finds that the U.S. and British refined oil prices Granger cause the Chinese refined oil price. •Both Chinese and the Australian coal prices play an important role in the international coal market. •The Chinese terminal electric power and terminal natural gas prices are not highly correlated. •The results are useful for guiding the design of more efficient energy pricing policies in China

  9. An Enhanced Feedback-Base Downlink Packet Scheduling Algorithm for Mobile TV in WIMAX Networks

    Directory of Open Access Journals (Sweden)

    Joseph Oyewale

    2013-06-01

    Full Text Available With high speed access network technology like WIMAX, there is the need for efficient management of radio resources where the throughput and Qos requirements for Multicasting Broadcasting Services (MBS for example TV are to be met. An enhanced  feedback-base downlink Packet scheduling algorithm  that can be used in IEEE 802.16d/e networks for mobile TV “one way traffic”(MBS is needed to support many users utilizing multiuser diversity of the  broadband of WIMAX systems where a group of users(good/worst channels share allocated resources (bandwidth. This paper proposes a WIMAX framework feedback-base (like a channel-awareness downlink packet scheduling algorithm for Mobile TV traffics in IEEE806.16, in which network Physical Timing Slots (PSs resource blocks are allocated in a dynamic way to mobile TV subscribers based on the Channel State information (CSI feedback, and then considering users with worst channels with the aim of improving system throughput while system coverage is being guaranteed. The algorithm was examined by changing the PSs bandwidth allocation of the users and different number of users of a cell. Simulation results show our proposed algorithm performed better than other algorithms (blind algorithms in terms of improvement in system throughput performance. /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso

  10. 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...

  11. 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

  12. 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

  13. 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...

  14. Understanding the cost bases of Space Shuttle pricing policies for commercial and foreign customers

    Science.gov (United States)

    Stone, Barbara A.

    1984-01-01

    The principles and underlying cost bases of the 1977 and 1982 Space Shuttle Reimbursement Policies are compared and contrasted. Out-of-pocket cost recovery has been chosen as the base of the price for the 1986-1988 time period. With this cost base, it is NASA's intent to recover the total cost of consumables and the launch and flight operations costs added by commercial and foreign customers over the 1986-1988 time period. Beyond 1988, NASA intends to return to its policy of full cost recovery.

  15. 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.

  16. Data Model Approach And Markov Chain Based Analysis Of Multi-Level Queue Scheduling

    Directory of Open Access Journals (Sweden)

    Diwakar Shukla

    2010-01-01

    Full Text Available There are many CPU scheduling algorithms inliterature like FIFO, Round Robin, Shortest-Job-First and so on.The Multilevel-Queue-Scheduling is superior to these due to itsbetter management of a variety of processes. In this paper, aMarkov chain model is used for a general setup of Multilevelqueue-scheduling and the scheduler is assumed to performrandom movement on queue over the quantum of time.Performance of scheduling is examined through a rowdependent data model. It is found that with increasing value of αand d, the chance of system going over the waiting state reduces.At some of the interesting combinations of α and d, it diminishesto zero, thereby, provides us some clue regarding better choice ofqueues over others for high priority jobs. It is found that ifqueue priorities are added in the scheduling intelligently thenbetter performance could be obtained. Data model helpschoosing appropriate preferences.

  17. 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.

  18. Three hybridization models based on local search scheme for job shop scheduling problem

    Science.gov (United States)

    Balbi Fraga, Tatiana

    2015-05-01

    This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. An effective PSO-based memetic algorithm for flow shop scheduling.

    Science.gov (United States)

    Liu, Bo; Wang, Ling; Jin, Yi-Hui

    2007-02-01

    This paper proposes an effective particle swarm optimization (PSO)-based memetic algorithm (MA) for the permutation flow shop scheduling problem (PFSSP) with the objective to minimize the maximum completion time, which is a typical non-deterministic polynomial-time (NP) hard combinatorial optimization problem. In the proposed PSO-based MA (PSOMA), both PSO-based searching operators and some special local searching operators are designed to balance the exploration and exploitation abilities. In particular, the PSOMA applies the evolutionary searching mechanism of PSO, which is characterized by individual improvement, population cooperation, and competition to effectively perform exploration. On the other hand, the PSOMA utilizes several adaptive local searches to perform exploitation. First, to make PSO suitable for solving PFSSP, a ranked-order value rule based on random key representation is presented to convert the continuous position values of particles to job permutations. Second, to generate an initial swarm with certain quality and diversity, the famous Nawaz-Enscore-Ham (NEH) heuristic is incorporated into the initialization of population. Third, to balance the exploration and exploitation abilities, after the standard PSO-based searching operation, a new local search technique named NEH_1 insertion is probabilistically applied to some good particles selected by using a roulette wheel mechanism with a specified probability. Fourth, to enrich the searching behaviors and to avoid premature convergence, a simulated annealing (SA)-based local search with multiple different neighborhoods is designed and incorporated into the PSOMA. Meanwhile, an effective adaptive meta-Lamarckian learning strategy is employed to decide which neighborhood to be used in SA-based local search. Finally, to further enhance the exploitation ability, a pairwise-based local search is applied after the SA-based search. Simulation results based on benchmarks demonstrate the effectiveness

  4. Day-Ahead Crude Oil Price Forecasting Using a Novel Morphological Component Analysis Based Model

    Directory of Open Access Journals (Sweden)

    Qing Zhu

    2014-01-01

    Full Text Available As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data characteristics in the time scale domain during the modelling process can lead to significant performance improvement. This paper proposes a novel morphological component analysis based hybrid methodology for modeling the multiscale heterogeneous characteristics of the price movement in the crude oil markets. Empirical studies in two representative benchmark crude oil markets reveal the existence of multiscale heterogeneous microdata structure. The significant performance improvement of the proposed algorithm incorporating the heterogeneous data characteristics, against benchmark random walk, ARMA, and SVR models, is also attributed to the innovative methodology proposed to incorporate this important stylized fact during the modelling process. Meanwhile, work in this paper offers additional insights into the heterogeneous market microstructure with economic viable interpretations.

  5. 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.

  6. The Optimal Confidence Intervals for Agricultural Products’ Price Forecasts Based on Hierarchical Historical Errors

    Directory of Open Access Journals (Sweden)

    Yi Wang

    2016-12-01

    Full Text Available With the levels of confidence and system complexity, interval forecasts and entropy analysis can deliver more information than point forecasts. In this paper, we take receivers’ demands as our starting point, use the trade-off model between accuracy and informativeness as the criterion to construct the optimal confidence interval, derive the theoretical formula of the optimal confidence interval and propose a practical and efficient algorithm based on entropy theory and complexity theory. In order to improve the estimation precision of the error distribution, the point prediction errors are STRATIFIED according to prices and the complexity of the system; the corresponding prediction error samples are obtained by the prices stratification; and the error distributions are estimated by the kernel function method and the stability of the system. In a stable and orderly environment for price forecasting, we obtain point prediction error samples by the weighted local region and RBF (Radial basis function neural network methods, forecast the intervals of the soybean meal and non-GMO (Genetically Modified Organism soybean continuous futures closing prices and implement unconditional coverage, independence and conditional coverage tests for the simulation results. The empirical results are compared from various interval evaluation indicators, different levels of noise, several target confidence levels and different point prediction methods. The analysis shows that the optimal interval construction method is better than the equal probability method and the shortest interval method and has good anti-noise ability with the reduction of system entropy; the hierarchical estimation error method can obtain higher accuracy and better interval estimation than the non-hierarchical method in a stable system.

  7. The transmission of fluctuant patterns of the forex burden based on international crude oil prices

    International Nuclear Information System (INIS)

    Gao, Xiangyun; An, Haizhong; Fang, Wei; Li, Huajiao

    2014-01-01

    For a country that imports crude oil, the forex burden is always fluctuant due to the fluctuation of international crude oil prices and exchange rates over time. The gap discovered between international crude oil prices and the crude oil price based on exchange rates may indicate the fluctuation of the forex burden. There exist different fluctuant patterns in the fluctuation process of the forex burden in different periods. Hence, we proposed an approach combining econometrics and complex network theory to explore the transmission mechanism of these fluctuant patterns. In this study, we defined the forex burden and the fluctuant patterns by normalization, sliding windows of data and econometric models. And then we set the fluctuant patterns as nodes and the transformation between patterns as edges; in this way, the transmission complex network is constructed. The results show that different major fluctuant patterns with different probabilities appear in different scales. The fluctuant patterns transferred into each other conveniently. And the transmission medium can help to identify the transitional periods in the process of the transmission. The contribution of this study to the energy policy decision-making is that the formulations of related policies under different period lengths require different reference standards. - Highlights: • Small “gap” between crude oil price and exchange rate can make great forex fluctuation. • We defined the fluctuant patterns of forex burden through data sliding windows. • We constructed the transmission network models of fluctuant patterns of forex burden. • The transitional periods can be identified by media capabilities of fluctuant patterns. • Energy policies making for different lengths of period should reference different scales standards

  8. The transmission of fluctuant patterns of the forex burden based on international crude oil prices

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Xiangyun [School of Humanities and Economic Management, China University of Geosciences, Beijing 100083 (China); Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land and Resources (Chinese Academy of Land and Resource Economics, China University of Geosciences Beijing), Beijing 100083 (China); Lab of Resources and Environmental Management, China University of Geosciences, Beijing 100083 (China); Department of Earth and Environmental Sciences, University of Waterloo, ON N2L 3G1 (Canada); An, Haizhong [School of Humanities and Economic Management, China University of Geosciences, Beijing 100083 (China); Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land and Resources (Chinese Academy of Land and Resource Economics, China University of Geosciences Beijing), Beijing 100083 (China); Lab of Resources and Environmental Management, China University of Geosciences, Beijing 100083 (China); Fang, Wei [School of Humanities and Economic Management, China University of Geosciences, Beijing 100083 (China); Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land and Resources (Chinese Academy of Land and Resource Economics, China University of Geosciences Beijing), Beijing 100083 (China); Lab of Resources and Environmental Management, China University of Geosciences, Beijing 100083 (China); Li, Huajiao [School of Humanities and Economic Management, China University of Geosciences, Beijing 100083 (China); Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land and Resources (Chinese Academy of Land and Resource Economics, China University of Geosciences Beijing), Beijing 100083 (China); Lab of Resources and Environmental Management, China University of Geosciences, Beijing 100083 (China); others, and

    2014-08-14

    For a country that imports crude oil, the forex burden is always fluctuant due to the fluctuation of international crude oil prices and exchange rates over time. The gap discovered between international crude oil prices and the crude oil price based on exchange rates may indicate the fluctuation of the forex burden. There exist different fluctuant patterns in the fluctuation process of the forex burden in different periods. Hence, we proposed an approach combining econometrics and complex network theory to explore the transmission mechanism of these fluctuant patterns. In this study, we defined the forex burden and the fluctuant patterns by normalization, sliding windows of data and econometric models. And then we set the fluctuant patterns as nodes and the transformation between patterns as edges; in this way, the transmission complex network is constructed. The results show that different major fluctuant patterns with different probabilities appear in different scales. The fluctuant patterns transferred into each other conveniently. And the transmission medium can help to identify the transitional periods in the process of the transmission. The contribution of this study to the energy policy decision-making is that the formulations of related policies under different period lengths require different reference standards. - Highlights: • Small “gap” between crude oil price and exchange rate can make great forex fluctuation. • We defined the fluctuant patterns of forex burden through data sliding windows. • We constructed the transmission network models of fluctuant patterns of forex burden. • The transitional periods can be identified by media capabilities of fluctuant patterns. • Energy policies making for different lengths of period should reference different scales standards.

  9. Pricing index-based catastrophe bonds: Part 2: Object-oriented design issues and sensitivity analysis

    Science.gov (United States)

    Unger, André J. A.

    2010-02-01

    This work is the second installment in a two-part series, and focuses on object-oriented programming methods to implement an augmented-state variable approach to aggregate the PCS index and introduce the Bermudan-style call feature into the proposed CAT bond model. The PCS index is aggregated quarterly using a discrete Asian running-sum formulation. The resulting aggregate PCS index augmented-state variable is used to specify the payoff (principle) on the CAT bond based on reinsurance layers. The purpose of the Bermudan-style call option is to allow the reinsurer to minimize their interest rate risk exposure on making fixed coupon payments under prevailing interest rates. A sensitivity analysis is performed to determine the impact of uncertainty in the frequency and magnitude of hurricanes on the price of the CAT bond. Results indicate that while the CAT bond is highly sensitive to the natural variability in the frequency of landfalling hurricanes between El Ninõ and non-El Ninõ years, it remains relatively insensitive to uncertainty in the magnitude of damages. In addition, results indicate that the maximum price of the CAT bond is insensitive to whether it is engineered to cover low frequency high magnitude events in a 'high' reinsurance layer relative to high frequency low magnitude events in a 'low' reinsurance layer. Also, while it is possible for the reinsurer to minimize their interest rate risk exposure on the fixed coupon payments, the impact of this risk on the price of the CAT bond appears small relative to the natural variability in the CAT bond price, and consequently catastrophic risk, due to uncertainty in the frequency and magnitude of landfalling hurricanes.

  10. Affordability Challenges to Value-Based Pricing: Mass Diseases, Orphan Diseases, and Cures.

    Science.gov (United States)

    Danzon, Patricia M

    2018-03-01

    To analyze how value-based pricing (VBP), which grounds the price paid for pharmaceuticals in their value, can manage "affordability" challenges, defined as drugs that meet cost-effectiveness thresholds but are "unaffordable" within the short-run budget. Three specific contexts are examined, drawing on recent experience. First, an effective new treatment for a chronic, progressive disease, such as hepatitis C, creates a budget spike that is transitory because initial prevalence is high, relative to current incidence. Second, "cures" that potentially provide lifetime benefits may claim abnormally high VBP prices, with high immediate budget impact potentially/partially offset by deferred cost savings. Third, although orphan drugs in principle target rare diseases, in aggregate they pose affordability concerns because of the growing number of orphan indications and increasingly high prices. For mass diseases, the transitory budget impact of treating the accumulated patient stock can be managed by stratified rollout that delays treatment of stable patients and prioritizes patients at high risk of deterioration. Delay spreads the budget impact and permits potential savings from launch of competing treatments. For cures, installment payments contingent on outcomes could align payment flows and appropriately shift risk to producers. This approach, however, entails high administrative and incentive costs, especially if applied across multiple payers in the United States. For orphan drugs, the available evidence on research and development trends and returns argues against the need for a higher VBP threshold to incentivize research and development in orphan drugs, given existing statutory benefits under orphan drug legislation. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  11. 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.

  12. A cloud-based electronic medical record for scheduling, tracking, and documenting examinations and treatment of retinopathy of prematurity.

    Science.gov (United States)

    Arnold, Robert W; Jacob, Jack; Matrix, Zinnia

    2012-01-01

    Screening by neonatologists and staging by ophthalmologists is a cost-effective intervention, but inadvertent missed examinations create a high liability. Paper tracking, bedside schedule reminders, and a computer scheduling and reminder program were compared for speed of input and retrospective missed examination rate. A neonatal intensive care unit (NICU) process was then programmed for cloud-based distribution for inpatient and outpatient retinopathy of prematurity monitoring. Over 11 years, 367 premature infants in one NICU were prospectively monitored. The initial paper system missed 11% of potential examinations, the Windows server-based system missed 2%, and the current cloud-based system missed 0% of potential inpatient and outpatient examinations. Computer input of examinations took the same or less time than paper recording. A computer application with a deliberate NICU process improved the proportion of eligible neonates getting their scheduled eye examinations in a timely manner. Copyright 2012, SLACK Incorporated.

  13. 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

  14. 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

  15. Analysis of Performance Factors in Customer-Led Supply Chains Based on Option Pricing Optimization%逆向主导型供应链期权定价优化的绩效影响因素分析

    Institute of Scientific and Technical Information of China (English)

    赵金实; 霍佳震; 赵莹; 段永瑞

    2011-01-01

    在包含市场利率、现货价格波动率和期权期限三个重要期权定价影响因素的逆向主导型供应链期权协作模型基础上,通过对模型决策优化机制的分析和灵敏度分析的方法,借助Matlab软件工具,研究市场利率和现货价格波动率对期权定价和供应链绩效的影响.通过数值仿真分析,进一步计算市场利率和现货价格波动率对期权定价和供应链绩效影响的规律和临界值.获得对企业制定供应链期权契约具有指导意义的研究结论.%Companies are increasingly constructing customer-centric supply chains in order to cope with the unrelenting pressure of cost reduction. The customer-centric supply chain strategy emphasizes improvement of key factors such as market rates, volatility and option pricing terms via the coordination of supply chain partners. A review of literature on supply chain management shows that other factors,such as product production cost, product selling price and the relationship between supply chain partners, have been considered.Globalization requires that companies be more flexible and adaptive to the changes of market environment because of increased factor mobility and market access. Therefore, a company needs to consider many relevant factors, such as the cost of funds, the opportunity cost of scheduled capacity and the uncertainty risk of product price fluctuations, when constructing a customer-centric supply chain. This study proposes an option pricing optimization model to help a company manage its customer-centric supply chains. This option pricing optimization model considers the importance of market interest rates, product price volatility and option deadline. As a result,instead of managing supply chains from supplier's perspectives this model offers the possibility of managing supply chains from customer's perspectives. Our work places emphasis on the synergy of a B-S option pricing model and supply chain operation mechanisms

  16. [Prudent use price controls in Chinese medicines market: based on statistical data analysis].

    Science.gov (United States)

    Yang, Guang; Wang, Nuo; Huang, Lu-Qi; Qiu, Hong-Yan; Guo, Lan-Ping

    2014-01-01

    A dispute about the decreasing-price problem of traditional Chinese medicine (TCM) has recently arisen. This article analyzes the statistical data of 1995-2011 in China, the results showed that the main responsibility of expensive health care has no direct relationship with the drug price. The price index of TCM rose significantly slower than the medicine prices, the production margins of TCM affected by the material prices has been diminishing since 1995, continuous price reduction will further depress profits of the TCM industry. Considering the pros and cons of raw materials vary greatly in price, decreasing medicine price behavior will force enterprises to use inferior materials in order to maintain corporate profits. The results have the guiding meaning to medicine price management.

  17. 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.

  18. Processing time tolerance-based ACO algorithm for solving job-shop scheduling problem

    Science.gov (United States)

    Luo, Yabo; Waden, Yongo P.

    2017-06-01

    Ordinarily, Job Shop Scheduling Problem (JSSP) is known as NP-hard problem which has uncertainty and complexity that cannot be handled by a linear method. Thus, currently studies on JSSP are concentrated mainly on applying different methods of improving the heuristics for optimizing the JSSP. However, there still exist many problems for efficient optimization in the JSSP, namely, low efficiency and poor reliability, which can easily trap the optimization process of JSSP into local optima. Therefore, to solve this problem, a study on Ant Colony Optimization (ACO) algorithm combined with constraint handling tactics is carried out in this paper. Further, the problem is subdivided into three parts: (1) Analysis of processing time tolerance-based constraint features in the JSSP which is performed by the constraint satisfying model; (2) Satisfying the constraints by considering the consistency technology and the constraint spreading algorithm in order to improve the performance of ACO algorithm. Hence, the JSSP model based on the improved ACO algorithm is constructed; (3) The effectiveness of the proposed method based on reliability and efficiency is shown through comparative experiments which are performed on benchmark problems. Consequently, the results obtained by the proposed method are better, and the applied technique can be used in optimizing JSSP.

  19. 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.

  20. 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.

  1. Multi-Agent Based Beam Search for Real-Time Production Scheduling and Control Method, Software and Industrial Application

    CERN Document Server

    Kang, Shu Gang

    2013-01-01

    The Multi-Agent Based Beam Search (MABBS) method systematically integrates four major requirements of manufacturing production - representation capability, solution quality, computation efficiency, and implementation difficulty - within a unified framework to deal with the many challenges of complex real-world production planning and scheduling problems. Multi-agent Based Beam Search for Real-time Production Scheduling and Control introduces this method, together with its software implementation and industrial applications.  This book connects academic research with industrial practice, and develops a practical solution to production planning and scheduling problems. To simplify implementation, a reusable software platform is developed to build the MABBS method into a generic computation engine.  This engine is integrated with a script language, called the Embedded Extensible Application Script Language (EXASL), to provide a flexible and straightforward approach to representing complex real-world problems. ...

  2. Electricity storages - optimised operation based on spot market prices; Stromspeicher. Optimierte Fahrweise auf Basis der Spotmarktpreise

    Energy Technology Data Exchange (ETDEWEB)

    Bernhard, Dominik; Roon, Serafin von [FfE Forschungsstelle fuer Energiewirtschaft e.V., Muenchen (Germany)

    2010-06-15

    With its integrated energy and climate package the last federal government set itself ambitious goals for the improvement of energy efficiency and growth of renewable energy production. These goals were confirmed by the new government in its coalition agreement. However, they can only be realised if the supply of electricity from fluctuating renewable sources can be made to coincide with electricity demand. Electricity storages are therefore an indispensable component of the future energy supply system. This article studies the optimised operation of an electricity storage based on spot market prices and the influence of wind power production up to the year 2020.

  3. A three-stage strategy for optimal price offering by a retailer based on clustering techniques

    International Nuclear Information System (INIS)

    Mahmoudi-Kohan, N.; Shayesteh, E.; Moghaddam, M. Parsa; Sheikh-El-Eslami, M.K.

    2010-01-01

    In this paper, an innovative strategy for optimal price offering to customers for maximizing the profit of a retailer is proposed. This strategy is based on load profile clustering techniques and includes three stages. For the purpose of clustering, an improved weighted fuzzy average K-means is proposed. Also, in this paper a new acceptance function for increasing the profit of the retailer is proposed. The new method is evaluated by implementation on a group of 300 customers of a 20 kV distribution network. (author)

  4. A three-stage strategy for optimal price offering by a retailer based on clustering techniques

    Energy Technology Data Exchange (ETDEWEB)

    Mahmoudi-Kohan, N.; Shayesteh, E. [Islamic Azad University (Garmsar Branch), Garmsar (Iran); Moghaddam, M. Parsa; Sheikh-El-Eslami, M.K. [Tarbiat Modares University, Tehran (Iran)

    2010-12-15

    In this paper, an innovative strategy for optimal price offering to customers for maximizing the profit of a retailer is proposed. This strategy is based on load profile clustering techniques and includes three stages. For the purpose of clustering, an improved weighted fuzzy average K-means is proposed. Also, in this paper a new acceptance function for increasing the profit of the retailer is proposed. The new method is evaluated by implementation on a group of 300 customers of a 20 kV distribution network. (author)

  5. Downward Price-Based Brand Line Extensions Effects on Luxury Brands

    OpenAIRE

    Royo-Vela, Marcelo; Voss, Eileen

    2015-01-01

    This study tries to examine the brand concept consistency, the self-concept congruence and the resulting loyalty status of the consumers in order to evaluate whether a downward price-based line extensions in the luxury goods market has any negative or positive effect on them. By conducting focus group and in-depth interviews it was tried to filter out how brand concepts of luxury brands are perceived before and after a line extension. Results revealed that a crucial aspect for the evaluation ...

  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. Constraint based scheduling for the Goddard Space Flight Center distributed Active Archive Center's data archive and distribution system

    Science.gov (United States)

    Short, Nick, Jr.; Bedet, Jean-Jacques; Bodden, Lee; Boddy, Mark; White, Jim; Beane, John

    1994-01-01

    The Goddard Space Flight Center (GSFC) Distributed Active Archive Center (DAAC) has been operational since October 1, 1993. Its mission is to support the Earth Observing System (EOS) by providing rapid access to EOS data and analysis products, and to test Earth Observing System Data and Information System (EOSDIS) design concepts. One of the challenges is to ensure quick and easy retrieval of any data archived within the DAAC's Data Archive and Distributed System (DADS). Over the 15-year life of EOS project, an estimated several Petabytes (10(exp 15)) of data will be permanently stored. Accessing that amount of information is a formidable task that will require innovative approaches. As a precursor of the full EOS system, the GSFC DAAC with a few Terabits of storage, has implemented a prototype of a constraint-based task and resource scheduler to improve the performance of the DADS. This Honeywell Task and Resource Scheduler (HTRS), developed by Honeywell Technology Center in cooperation the Information Science and Technology Branch/935, the Code X Operations Technology Program, and the GSFC DAAC, makes better use of limited resources, prevents backlog of data, provides information about resources bottlenecks and performance characteristics. The prototype which is developed concurrently with the GSFC Version 0 (V0) DADS, models DADS activities such as ingestion and distribution with priority, precedence, resource requirements (disk and network bandwidth) and temporal constraints. HTRS supports schedule updates, insertions, and retrieval of task information via an Application Program Interface (API). The prototype has demonstrated with a few examples, the substantial advantages of using HTRS over scheduling algorithms such as a First In First Out (FIFO) queue. The kernel scheduling engine for HTRS, called Kronos, has been successfully applied to several other domains such as space shuttle mission scheduling, demand flow manufacturing, and avionics communications

  8. A Novel Memetic Algorithm Based on Decomposition for Multiobjective Flexible Job Shop Scheduling Problem

    Directory of Open Access Journals (Sweden)

    Chun Wang

    2017-01-01

    Full Text Available A novel multiobjective memetic algorithm based on decomposition (MOMAD is proposed to solve multiobjective flexible job shop scheduling problem (MOFJSP, which simultaneously minimizes makespan, total workload, and critical workload. Firstly, a population is initialized by employing an integration of different machine assignment and operation sequencing strategies. Secondly, multiobjective memetic algorithm based on decomposition is presented by introducing a local search to MOEA/D. The Tchebycheff approach of MOEA/D converts the three-objective optimization problem to several single-objective optimization subproblems, and the weight vectors are grouped by K-means clustering. Some good individuals corresponding to different weight vectors are selected by the tournament mechanism of a local search. In the experiments, the influence of three different aggregation functions is first studied. Moreover, the effect of the proposed local search is investigated. Finally, MOMAD is compared with eight state-of-the-art algorithms on a series of well-known benchmark instances and the experimental results show that the proposed algorithm outperforms or at least has comparative performance to the other algorithms.

  9. Chaotic Multiobjective Evolutionary Algorithm Based on Decomposition for Test Task Scheduling Problem

    Directory of Open Access Journals (Sweden)

    Hui Lu

    2014-01-01

    Full Text Available Test task scheduling problem (TTSP is a complex optimization problem and has many local optima. In this paper, a hybrid chaotic multiobjective evolutionary algorithm based on decomposition (CMOEA/D is presented to avoid becoming trapped in local optima and to obtain high quality solutions. First, we propose an improving integrated encoding scheme (IES to increase the efficiency. Then ten chaotic maps are applied into the multiobjective evolutionary algorithm based on decomposition (MOEA/D in three phases, that is, initial population and crossover and mutation operators. To identify a good approach for hybrid MOEA/D and chaos and indicate the effectiveness of the improving IES several experiments are performed. The Pareto front and the statistical results demonstrate that different chaotic maps in different phases have different effects for solving the TTSP especially the circle map and ICMIC map. The similarity degree of distribution between chaotic maps and the problem is a very essential factor for the application of chaotic maps. In addition, the experiments of comparisons of CMOEA/D and variable neighborhood MOEA/D (VNM indicate that our algorithm has the best performance in solving the TTSP.

  10. Performance analysis of switch-based multiuser scheduling schemes with adaptive modulation in spectrum sharing systems

    KAUST Repository

    Qaraqe, Marwa

    2014-04-01

    This paper focuses on the development of multiuser access schemes for spectrum sharing systems whereby secondary users are allowed to share the spectrum with primary users under the condition that the interference observed at the primary receiver is below a predetermined threshold. In particular, two scheduling schemes are proposed for selecting a user among those that satisfy the interference constraint and achieve an acceptable signal-to-noise ratio level. The first scheme focuses on optimizing the average spectral efficiency by selecting the user that reports the best channel quality. In order to alleviate the relatively high feedback required by the first scheme, a second scheme based on the concept of switched diversity is proposed, where the base station (BS) scans the secondary users in a sequential manner until a user whose channel quality is above an acceptable predetermined threshold is found. We develop expressions for the statistics of the signal-to-interference and noise ratio as well as the average spectral efficiency, average feedback load, and the delay at the secondary BS. We then present numerical results for the effect of the number of users and the interference constraint on the optimal switching threshold and the system performance and show that our analysis results are in perfect agreement with the numerical results. © 2014 John Wiley & Sons, Ltd.

  11. A comprehensive market-based scheme for VAR management and pricing in the electricity markets

    Energy Technology Data Exchange (ETDEWEB)

    El-Araby, E.E. [Qassim Univ., Alqassim, Meldia (Saudi Arabia). Dept. of Electrical Engineering

    2009-07-01

    In order to enable a power system to operate within an acceptable degree of reliability and security, the provision of VAR ancillary services from the VAR sources in electricity markets is the most effective method. The procurement of VAR services is particularly problematic for transmission operators as it relates to pricing mechanism and various technical issues during system operation. This paper proposed an integrated market-based approach for pricing VAR service in the electricity market. The paper was an extension of the authors' proposal for the provision of the VAR service from dynamic VAR sources in a competitive market-based environment. The formulation was modified to include VAR utilization payment and possible power system transition states multiple base cases and contingencies with their associated occurrence probabilities. The paper discussed the basic terms of the proposed approach including the VAR market objective and generator VAR output and its compensation. The mathematical formulation that considered VAR capacity payment, utilization payment and operating costs under the previous transition states in a unified single problem were introduced. The overall problem formulation and solution algorithm were also presented as a large-scale mixed integer nonlinear optimization problem. It was concluded that the proposed method was suited for the simulation and analysis of the existing VAR market. 8 refs., 3 tabs., 5 figs., 2 appendices.

  12. Distribution Locational Real-Time Pricing Based Smart Building Control and Management

    Energy Technology Data Exchange (ETDEWEB)

    Hao, Jun; Dai, Xiaoxiao; Zhang, Yingchen; Zhang, Jun; Gao, Wenzhong

    2016-11-21

    This paper proposes an real-virtual parallel computing scheme for smart building operations aiming at augmenting overall social welfare. The University of Denver's campus power grid and Ritchie fitness center is used for demonstrating the proposed approach. An artificial virtual system is built in parallel to the real physical system to evaluate the overall social cost of the building operation based on the social science based working productivity model, numerical experiment based building energy consumption model and the power system based real-time pricing mechanism. Through interactive feedback exchanged between the real and virtual system, enlarged social welfare, including monetary cost reduction and energy saving, as well as working productivity improvements, can be achieved.

  13. Comprehensive optimisation of China’s energy prices, taxes and subsidy policies based on the dynamic computable general equilibrium model

    International Nuclear Information System (INIS)

    He, Y.X.; Liu, Y.Y.; Du, M.; Zhang, J.X.; Pang, Y.X.

    2015-01-01

    Highlights: • Energy policy is defined as a complication of energy price, tax and subsidy policies. • The maximisation of total social benefit is the optimised objective. • A more rational carbon tax ranges from 10 to 20 Yuan/ton under the current situation. • The optimal coefficient pricing is more conducive to maximise total social benefit. - Abstract: Under the condition of increasingly serious environmental pollution, rational energy policy plays an important role in the practical significance of energy conservation and emission reduction. This paper defines energy policies as the compilation of energy prices, taxes and subsidy policies. Moreover, it establishes the optimisation model of China’s energy policy based on the dynamic computable general equilibrium model, which maximises the total social benefit, in order to explore the comprehensive influences of a carbon tax, the sales pricing mechanism and the renewable energy fund policy. The results show that when the change rates of gross domestic product and consumer price index are ±2%, ±5% and the renewable energy supply structure ratio is 7%, the more reasonable carbon tax ranges from 10 to 20 Yuan/ton, and the optimal coefficient pricing mechanism is more conducive to the objective of maximising the total social benefit. From the perspective of optimising the overall energy policies, if the upper limit of change rate in consumer price index is 2.2%, the existing renewable energy fund should be improved

  14. Towards a Framework for Knowledge-based Pricing Services Improving Operational Agility in the Retail Industry

    OpenAIRE

    Kowatsch, Tobias; Maass, Wolfgang

    2009-01-01

    Marketing research has identified several benefits of dynamic pricing models. For example, dynamic pricing in terms of inventory considerations and time horizons, bundling or personalized offerings has been found to increase sales volume, customer satisfaction and to skim reservation prices. However, today's retailers lack the capability to apply dynamic pricing models because of missing services that realize them and technologies such as smart product infrastructures that deliver the resu...

  15. A Chaotic Particle Swarm Optimization-Based Heuristic for Market-Oriented Task-Level Scheduling in Cloud Workflow Systems.

    Science.gov (United States)

    Li, Xuejun; Xu, Jia; Yang, Yun

    2015-01-01

    Cloud workflow system is a kind of platform service based on cloud computing. It facilitates the automation of workflow applications. Between cloud workflow system and its counterparts, market-oriented business model is one of the most prominent factors. The optimization of task-level scheduling in cloud workflow system is a hot topic. As the scheduling is a NP problem, Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) have been proposed to optimize the cost. However, they have the characteristic of premature convergence in optimization process and therefore cannot effectively reduce the cost. To solve these problems, Chaotic Particle Swarm Optimization (CPSO) algorithm with chaotic sequence and adaptive inertia weight factor is applied to present the task-level scheduling. Chaotic sequence with high randomness improves the diversity of solutions, and its regularity assures a good global convergence. Adaptive inertia weight factor depends on the estimate value of cost. It makes the scheduling avoid premature convergence by properly balancing between global and local exploration. The experimental simulation shows that the cost obtained by our scheduling is always lower than the other two representative counterparts.

  16. A Chaotic Particle Swarm Optimization-Based Heuristic for Market-Oriented Task-Level Scheduling in Cloud Workflow Systems

    Directory of Open Access Journals (Sweden)

    Xuejun Li

    2015-01-01

    Full Text Available Cloud workflow system is a kind of platform service based on cloud computing. It facilitates the automation of workflow applications. Between cloud workflow system and its counterparts, market-oriented business model is one of the most prominent factors. The optimization of task-level scheduling in cloud workflow system is a hot topic. As the scheduling is a NP problem, Ant Colony Optimization (ACO and Particle Swarm Optimization (PSO have been proposed to optimize the cost. However, they have the characteristic of premature convergence in optimization process and therefore cannot effectively reduce the cost. To solve these problems, Chaotic Particle Swarm Optimization (CPSO algorithm with chaotic sequence and adaptive inertia weight factor is applied to present the task-level scheduling. Chaotic sequence with high randomness improves the diversity of solutions, and its regularity assures a good global convergence. Adaptive inertia weight factor depends on the estimate value of cost. It makes the scheduling avoid premature convergence by properly balancing between global and local exploration. The experimental simulation shows that the cost obtained by our scheduling is always lower than the other two representative counterparts.

  17. Efficient Pricing of Early : Exercise and Exotic Options Based on Fourier Cosine Expansions

    NARCIS (Netherlands)

    Zhang, B.

    2012-01-01

    In the financial world, two tasks are of prime importance: model calibration and portfolio hedging. For both tasks, efficient option pricing is necessary, particularly for the calibration where many options with different strike prices and different maturities need to be priced at the same time.

  18. A software-based technique enabling composable hierarchical preemptive scheduling for time-triggered applications

    NARCIS (Netherlands)

    Nejad, A.B.; Molnos, A.; Goossens, K.G.W.

    2013-01-01

    Many embedded real-time applications are typically time-triggered and preemptive schedulers are used to execute tasks of such applications. Orthogonally, composable partitioned embedded platforms use preemptive time-division multiplexing mechanism to isolate applications. Existing composable systems

  19. Simulated Annealing Genetic Algorithm Based Schedule Risk Management of IT Outsourcing Project

    Directory of Open Access Journals (Sweden)

    Fuqiang Lu

    2017-01-01

    Full Text Available IT outsourcing is an effective way to enhance the core competitiveness for many enterprises. But the schedule risk of IT outsourcing project may cause enormous economic loss to enterprise. In this paper, the Distributed Decision Making (DDM theory and the principal-agent theory are used to build a model for schedule risk management of IT outsourcing project. In addition, a hybrid algorithm combining simulated annealing (SA and genetic algorithm (GA is designed, namely, simulated annealing genetic algorithm (SAGA. The effect of the proposed model on the schedule risk management problem is analyzed in the simulation experiment. Meanwhile, the simulation results of the three algorithms GA, SA, and SAGA show that SAGA is the most superior one to the other two algorithms in terms of stability and convergence. Consequently, this paper provides the scientific quantitative proposal for the decision maker who needs to manage the schedule risk of IT outsourcing project.

  20. Cloud computing task scheduling strategy based on improved differential evolution algorithm

    Science.gov (United States)

    Ge, Junwei; He, Qian; Fang, Yiqiu

    2017-04-01

    In order to optimize the cloud computing task scheduling scheme, an improved differential evolution algorithm for cloud computing task scheduling is proposed. Firstly, the cloud computing task scheduling model, according to the model of the fitness function, and then used improved optimization calculation of the fitness function of the evolutionary algorithm, according to the evolution of generation of dynamic selection strategy through dynamic mutation strategy to ensure the global and local search ability. The performance test experiment was carried out in the CloudSim simulation platform, the experimental results show that the improved differential evolution algorithm can reduce the cloud computing task execution time and user cost saving, good implementation of the optimal scheduling of cloud computing tasks.

  1. Analytical Evaluation of the Performance of Proportional Fair Scheduling in OFDMA-Based Wireless Systems

    Directory of Open Access Journals (Sweden)

    Mohamed H. Ahmed

    2012-01-01

    Full Text Available This paper provides an analytical evaluation of the performance of proportional fair (PF scheduling in Orthogonal Frequency-Division Multiple Access (OFDMA wireless systems. OFDMA represents a promising multiple access scheme for transmission over wireless channels, as it combines the orthogonal frequency division multiplexing (OFDM modulation and subcarrier allocation. On the other hand, the PF scheduling is an efficient resource allocation scheme with good fairness characteristics. Consequently, OFDMA with PF scheduling represents an attractive solution to deliver high data rate services to multiple users simultaneously with a high degree of fairness. We investigate a two-dimensional (time slot and frequency subcarrier PF scheduling algorithm for OFDMA systems and evaluate its performance analytically and by simulations. We derive approximate closed-form expressions for the average throughput, throughput fairness index, and packet delay. Computer simulations are used for verification. The analytical results agree well with the results from simulations, which show the good accuracy of the analytical expressions.

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

    KAUST Repository

    Tabassum, Hina; Yilmaz, Ferkan; Dawy, Zaher; Alouini, Mohamed-Slim

    2012-01-01

    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

  3. Scheduled power tracking control of the wind-storage hybrid system based on the reinforcement learning theory

    Science.gov (United States)

    Li, Ze

    2017-09-01

    In allusion to the intermittency and uncertainty of the wind electricity, energy storage and wind generator are combined into a hybrid system to improve the controllability of the output power. A scheduled power tracking control method is proposed based on the reinforcement learning theory and Q-learning algorithm. In this method, the state space of the environment is formed with two key factors, i.e. the state of charge of the energy storage and the difference value between the actual wind power and scheduled power, the feasible action is the output power of the energy storage, and the corresponding immediate rewarding function is designed to reflect the rationality of the control action. By interacting with the environment and learning from the immediate reward, the optimal control strategy is gradually formed. After that, it could be applied to the scheduled power tracking control of the hybrid system. Finally, the rationality and validity of the method are verified through simulation examples.

  4. Recent Research Trends in Genetic Algorithm Based Flexible Job Shop Scheduling Problems

    OpenAIRE

    Amjad, Muhammad Kamal; Butt, Shahid Ikramullah; Kousar, Rubeena; Ahmad, Riaz; Agha, Mujtaba Hassan; Faping, Zhang; Anjum, Naveed; Asgher, Umer

    2018-01-01

    Flexible Job Shop Scheduling Problem (FJSSP) is an extension of the classical Job Shop Scheduling Problem (JSSP). The FJSSP is known to be NP-hard problem with regard to optimization and it is very difficult to find reasonably accurate solutions of the problem instances in a rational time. Extensive research has been carried out in this area especially over the span of the last 20 years in which the hybrid approaches involving Genetic Algorithm (GA) have gained the most popularity. Keeping in...

  5. Price-based Energy Control for V2G Networks in the Industrial Smart Grid

    Directory of Open Access Journals (Sweden)

    Rong Yu

    2015-08-01

    Full Text Available The energy crisis and global warming call for a new industrial revolution in production and distribution of renewable energy. Distributed power generation will be well developed in the new smart electricity distribution grid, in which robust power distribution will be the key technology. In this paper, we present a new vehicle-to-grid (V2G network for energy transfer, in which distributed renewable energy helps the power grid balance demand and supply. Plug-in hybrid electric vehicles (PHEVs will act as transporters of electricity for distributed renewable energy dispatching. We formulate and analyze the V2G network within the theoretical framework of complex network. We also employ the generalized synchronization method to study the dynamic behavior of V2G networks. Furthermore, we develop a new price-based energy control method to stimulate the PHEV's behavior of charging and discharging. Simulation results indicate that the V2G network can achieve synchronization and each region is able to balance energy supply and demand through price-based control.

  6. An annual framework for clustering-based pricing for an electricity retailer

    International Nuclear Information System (INIS)

    Mahmoudi-Kohan, N.; Moghaddam, M. Parsa; Sheikh-El-Eslami, M.K.

    2010-01-01

    In the competitive environment, it is necessary for a retailer to increase his/her profit as much as possible. There are few researches focused on the subjects related to the retailer and the retail market. In addition, those researches have mostly focused on the participation of the retailer in the wholesale market. In order to determine the optimal selling price, the knowledge of how and when consumers use electricity is essential to the retailer. This type of information can be found in load profiles of customers. In this paper, an annual framework for optimal price offering by a retailer is proposed which is based on clustering technique. For this purpose, load profiles of customers are used as their consumption patterns. Also, a profit function is defined as the objective of optimization problem based on the load profile considering conditional value at risk (CVaR) for risk modeling. Also, a new acceptance function is proposed to overcome drawbacks of the traditional ones. The objective function is a mixed-integer nonlinear problem which is solved by GAMS software. (author)

  7. Reliability-Based Marginal Cost Pricing Problem Case with Both Demand Uncertainty and Travelers’ Perception Errors

    Directory of Open Access Journals (Sweden)

    Shaopeng Zhong

    2013-01-01

    Full Text Available Focusing on the first-best marginal cost pricing (MCP in a stochastic network with both travel demand uncertainty and stochastic perception errors within the travelers’ route choice decision processes, this paper develops a perceived risk-based stochastic network marginal cost pricing (PRSN-MCP model. Numerical examples based on an integrated method combining the moment analysis approach, the fitting distribution method, and the reliability measures are also provided to demonstrate the importance and properties of the proposed model. The main finding is that ignoring the effect of travel time reliability and travelers’ perception errors may significantly reduce the performance of the first-best MCP tolls, especially under high travelers’ confidence and network congestion levels. The analysis result could also enhance our understanding of (1 the effect of stochastic perception error (SPE on the perceived travel time distribution and the components of road toll; (2 the effect of road toll on the actual travel time distribution and its reliability measures; (3 the effect of road toll on the total network travel time distribution and its statistics; and (4 the effect of travel demand level and the value of reliability (VoR level on the components of road toll.

  8. 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....

  9. Dependence and risk assessment for oil prices and exchange rate portfolios: A wavelet based approach

    Science.gov (United States)

    Aloui, Chaker; Jammazi, Rania

    2015-10-01

    In this article, we propose a wavelet-based approach to accommodate the stylized facts and complex structure of financial data, caused by frequent and abrupt changes of markets and noises. Specifically, we show how the combination of both continuous and discrete wavelet transforms with traditional financial models helps improve portfolio's market risk assessment. In the empirical stage, three wavelet-based models (wavelet-EGARCH with dynamic conditional correlations, wavelet-copula, and wavelet-extreme value) are considered and applied to crude oil price and US dollar exchange rate data. Our findings show that the wavelet-based approach provides an effective and powerful tool for detecting extreme moments and improving the accuracy of VaR and Expected Shortfall estimates of oil-exchange rate portfolios after noise is removed from the original data.

  10. Evaluation of the Terminal Area Precision Scheduling and Spacing System for Performance-Based Navigation Arrivals

    Science.gov (United States)

    Jung, Jaewoo; Swenson, Harry; Thipphavong, Jane; Martin, Lynne Hazel; Chen, Liang; Nguyen, Jimmy

    2013-01-01

    The growth of global demand for air transportation has put increasing strain on the nation's air traffic management system. To relieve this strain, the International Civil Aviation Organization has urged all nations to adopt Performance-Based Navigation (PBN), which can help to reduce air traffic congestion, decrease aviation fuel consumption, and protect the environment. NASA has developed a Terminal Area Precision Scheduling and Spacing (TAPSS) system that can support increased use of PBN during periods of high traffic, while supporting fuel-efficient, continuous descent approaches. In the original development of this system, arrival aircraft are assigned fuel-efficient Area Navigation (RNAV) Standard Terminal Arrival Routes before their initial descent from cruise, with routing defined to a specific runway. The system also determines precise schedules for these aircraft that facilitate continuous descent through the assigned routes. To meet these schedules, controllers are given a set of advisory tools to precisely control aircraft. The TAPSS system has been evaluated in a series of human-in-the-loop (HITL) air traffic simulations during 2010 and 2011. Results indicated increased airport arrival throughput up to 10 over current operations, and maintained fuel-efficient aircraft decent profiles from the initial descent to landing with reduced controller workload. This paper focuses on results from a joint NASA and FAA HITL simulation conducted in 2012. Due to the FAA rollout of the advance terminal area PBN procedures at mid-sized airports first, the TAPSS system was modified to manage arrival aircraft as they entered Terminal Radar Approach Control (TRACON). Dallas-Love Field airport (DAL) was selected by the FAA as a representative mid-sized airport within a constrained TRACON airspace due to the close proximity of a major airport, in this case Dallas-Ft Worth International Airport, one of the busiest in the world. To address this constraint, RNAV routes and

  11. WGC Based Robust and Gain Scheduling PI Controller Design for Condensing Boilers

    Directory of Open Access Journals (Sweden)

    Cem Onat

    2014-05-01

    Full Text Available This paper addresses the water temperature PI control in condensing domestic boilers. The main challenge of this process under the controller design perspective is the fact that the dynamics of condensing boilers are strongly affected by the demanded water flow rate. First, a robust PI controller based on weighted geometrical center method is designed that stabilizes and achieves good performance for closed-loop system for a wide range of the water flow rate. Then, it is shown that if the water flow rate information is used to update the controller gains, through a technique known as gain scheduled control, the performance can be significantly improved. Important characteristics of these PI design approaches are that the resulting parameters are calculated numerically without using any graphical method or iterative optimization process and that it guarantees the stability of the closed-loop. Significantly, simulation results have demonstrated that the proposed tuning techniques can perform better for set point changes and load disturbance than other available methods in the literature.

  12. A Decision Support System Based on Genetic Algorithm (Case Study: Scheduling in Supply Chain

    Directory of Open Access Journals (Sweden)

    Mohammad Ali Beheheshtinia

    2016-10-01

    Full Text Available Nowadays, the application of effective and efficient decisions on complex issues require the use of decision support systems. This Paper provided a decision support system based on the genetic algorithm for production and transportation scheduling problem in a supply chain. It is assumed that there are number of orders that should be produced by suppliers and should be transported to the plant by a transportation fleet. The aim is to assign orders to the suppliers, specify the order of their production, allocate processed orders to the vehicles for transport and to arrange them in a way that minimizes the total delivery time. It has been shown that the complexity of the problem was related to Np-hard and there was no possibility of using accurate methods to solve the problem in a reasonable time. So, the genetic algorithm was used in this paper to solve the problem. By using this decision support system, a new approach to supply chain management was proposed. The analysis of the approach proposed in this study compared to the conventional approaches by the decision support system indicated the preference of our proposed approach

  13. Model predictive control-based scheduler for repetitive discrete event systems with capacity constraints

    Directory of Open Access Journals (Sweden)

    Hiroyuki Goto

    2013-07-01

    Full Text Available A model predictive control-based scheduler for a class of discrete event systems is designed and developed. We focus on repetitive, multiple-input, multiple-output, and directed acyclic graph structured systems on which capacity constraints can be imposed. The target system’s behaviour is described by linear equations in max-plus algebra, referred to as state-space representation. Assuming that the system’s performance can be improved by paying additional cost, we adjust the system parameters and determine control inputs for which the reference output signals can be observed. The main contribution of this research is twofold, 1: For systems with capacity constraints, we derived an output prediction equation as functions of adjustable variables in a recursive form, 2: Regarding the construct for the system’s representation, we improved the structure to accomplish general operations which are essential for adjusting the system parameters. The result of numerical simulation in a later section demonstrates the effectiveness of the developed controller.

  14. 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

  15. Dosage and dose schedule screening of drug combinations in agent-based models reveals hidden synergies

    Directory of Open Access Journals (Sweden)

    Lisa Corina Barros de Andrade e Sousa1

    2016-01-01

    Full Text Available The fungus Candida albicans is the most common causative agent of human fungal infections and better drugs or drug combination strategies are urgently needed. Here, we present an agent-based model of the interplay of C. albicans with the host immune system and with the microflora of the host. We took into account the morphological change of C. albicans from the yeast to hyphae form and its dynamics during infection. The model allowed us to follow the dynamics of fungal growth and morphology, of the immune cells and of microflora in different perturbing situations. We specifically focused on the consequences of microflora reduction following antibiotic treatment. Using the agent-based model, different drug types have been tested for their effectiveness, namely drugs that inhibit cell division and drugs that constrain the yeast-to-hyphae transition. Applied individually, the division drug turned out to successfully decrease hyphae while the transition drug leads to a burst in hyphae after the end of the treatment. To evaluate the effect of different drug combinations, doses, and schedules, we introduced a measure for the return to a healthy state, the infection score. Using this measure, we found that the addition of a transition drug to a division drug treatment can improve the treatment reliability while minimizing treatment duration and drug dosage. In this work we present a theoretical study. Although our model has not been calibrated to quantitative experimental data, the technique of computationally identifying synergistic treatment combinations in an agent based model exemplifies the importance of computational techniques in translational research.

  16. EVALUATION OF LAND BASED ON MARKET PRICE OBJECTS OF REAL ESTATE IN UKRAINE: PROBLEMS AND WAYS OF THEIR SOLUTIONS

    Directory of Open Access Journals (Sweden)

    MARTYN А. G.

    2017-03-01

    Full Text Available Summary. Raising of problem. During the reform of land and property relations, has been carried out in Ukraine since the early 1990s, land plots and buildings received the status of goods, participate in economic turnover, have value and price. At the same time, not the most important prerequisite for the introduction in Ukraine of a mass valuation of real estate, which is intended to become a base for the fair taxation of land plots and other real estate, should be the systematic collection of mass data on the market prices of real estate. Constant changes, additions and improvements to the current normative monetary assessment of land do not give a real change in the methodology of assessment because it is based on regulatory indicators, there is a non-market based assessment. This approach does not give positive results and in the overwhelming majority we distort the evaluation indicators. As a result, there is a situation where in some places the price of a square meter is much lower than the market (real price, while in others it is much higher than the actual price. Thus, the transition to the use of monetary land valuation, which is based on mass market indicators (mass valuation, will get rid of the regulatory indicators by introducing a market valuation base. Purpose. Conduct an analysis of the current state of monetary valuation of land in Ukraine, form the main problems of the modern land assessment area and guide the ways to improve and transition to market valuation of land based on widespread use of mass data on market prices of real estate. Conclusion. The analysis of the current state of the monetary valuation of land shows a significant deviation of the evaluation results with real market prices, indicating the imperfection of the existing method of normative monetary evaluation. Mass evaluation in the short term can solve the problems with the reliability of the estimates and improve the system of land taxation.

  17. Quantifying immediate price impact of trades based on the k-shell decomposition of stock trading networks

    Science.gov (United States)

    Xie, Wen-Jie; Li, Ming-Xia; Xu, Hai-Chuan; Chen, Wei; Zhou, Wei-Xing; Stanley, H. Eugene

    2016-10-01

    Traders in a stock market exchange stock shares and form a stock trading network. Trades at different positions of the stock trading network may contain different information. We construct stock trading networks based on the limit order book data and classify traders into k classes using the k-shell decomposition method. We investigate the influences of trading behaviors on the price impact by comparing a closed national market (A-shares) with an international market (B-shares), individuals and institutions, partially filled and filled trades, buyer-initiated and seller-initiated trades, and trades at different positions of a trading network. Institutional traders professionally use some trading strategies to reduce the price impact and individuals at the same positions in the trading network have a higher price impact than institutions. We also find that trades in the core have higher price impacts than those in the peripheral shell.

  18. Forecasting short-term power prices in the Ontario Electricity Market (OEM) with a fuzzy logic based inference system

    International Nuclear Information System (INIS)

    Arciniegas, Alvaro I.; Arciniegas Rueda, Ismael E.

    2008-01-01

    The Ontario Electricity Market (OEM), which opened in May 2002, is relatively new and is still under change. In addition, the bidding strategies of the participants are such that the relationships between price and fundamentals are non-linear and dynamic. The lack of market maturity and high complexity hinders the use of traditional statistical methodologies (e.g., regression analysis) for price forecasting. Therefore, a flexible model is needed to achieve good forecasting in OEM. This paper uses a Takagi-Sugeno-Kang (TSK) fuzzy inference system in forecasting the one-day-ahead real-time peak price of the OEM. The forecasting results of TSK are compared with those obtained by traditional statistical and neural network based forecasting. The comparison suggests that TSK has considerable value in forecasting one-day-ahead peak price in OEM. (author)

  19. Three-Phase AC Optimal Power Flow Based Distribution Locational Marginal Price: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Rui; Zhang, Yingchen

    2017-05-17

    Designing market mechanisms for electricity distribution systems has been a hot topic due to the increased presence of smart loads and distributed energy resources (DERs) in distribution systems. The distribution locational marginal pricing (DLMP) methodology is one of the real-time pricing methods to enable such market mechanisms and provide economic incentives to active market participants. Determining the DLMP is challenging due to high power losses, the voltage volatility, and the phase imbalance in distribution systems. Existing DC Optimal Power Flow (OPF) approaches are unable to model power losses and the reactive power, while single-phase AC OPF methods cannot capture the phase imbalance. To address these challenges, in this paper, a three-phase AC OPF based approach is developed to define and calculate DLMP accurately. The DLMP is modeled as the marginal cost to serve an incremental unit of demand at a specific phase at a certain bus, and is calculated using the Lagrange multipliers in the three-phase AC OPF formulation. Extensive case studies have been conducted to understand the impact of system losses and the phase imbalance on DLMPs as well as the potential benefits of flexible resources.

  20. Fuzzy time-series based on Fibonacci sequence for stock price forecasting

    Science.gov (United States)

    Chen, Tai-Liang; Cheng, Ching-Hsue; Jong Teoh, Hia

    2007-07-01

    Time-series models have been utilized to make reasonably accurate predictions in the areas of stock price movements, academic enrollments, weather, etc. For promoting the forecasting performance of fuzzy time-series models, this paper proposes a new model, which incorporates the concept of the Fibonacci sequence, the framework of Song and Chissom's model and the weighted method of Yu's model. This paper employs a 5-year period TSMC (Taiwan Semiconductor Manufacturing Company) stock price data and a 13-year period of TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) stock index data as experimental datasets. By comparing our forecasting performances with Chen's (Forecasting enrollments based on fuzzy time-series. Fuzzy Sets Syst. 81 (1996) 311-319), Yu's (Weighted fuzzy time-series models for TAIEX forecasting. Physica A 349 (2004) 609-624) and Huarng's (The application of neural networks to forecast fuzzy time series. Physica A 336 (2006) 481-491) models, we conclude that the proposed model surpasses in accuracy these conventional fuzzy time-series models.

  1. Research on Price of Railway Freight Based on Low-Carbon Economy

    Directory of Open Access Journals (Sweden)

    Fenling Feng

    2016-01-01

    Full Text Available Transportation is one of the major energy consumption and carbon emission industries. Railway transport is a typical low-carbon transport. To accelerate the green low-carbon transportation development and improve the railway market share, this paper defines the concept of carbon saving profit to study the price of railway freight after the government functions were separated from railway enterprise management. First, taking full account of market factors and on the principle of utility maximization and maximum likelihood method, the sharing ratio model of transportation modes is established. Then consideration is given to both the profit of railway enterprises and social benefits, and income maximization model of railway freight based on low-carbon economy is established. The model can scientifically guide the transportation users who prefer to use resource-saving and environmental-friendly transportation modes, optimize transportation structure, and comprehensively improve the efficiency of transportation system. Finally, case analysis is conducted to verify the rationality and validity of the model, and reference for the rail freight pricing is provided.

  2. Demand Response Design and Use Based on Network Locational Marginal Prices

    DEFF Research Database (Denmark)

    Morais, Hugo; Faria, Pedro; Vale, Zita

    2014-01-01

    Power systems have been experiencing huge changes mainly due to the substantial increase of distributed generation (DG) and the operation in competitive environments. Virtual Power Players (VPP) can aggregate several players, namely a diversity of energy resources, including distributed generation...... (DG) based on several technologies, electric storage systems (ESS) and demand response (DR). Energy resources management gains an increasing relevance in this competitive context. This makes the DR use more interesting and flexible, giving place to a wide range of new opportunities. This paper...... proposes a methodology to support VPPs in the DR programs’ management, considering all the existing energy resources (generation and storage units) and the distribution network. The proposed method is based on locational marginal prices (LMP) values. The evaluation of the impact of using DR specific...

  3. 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.

  4. Impact of load management on the energy management strategy of a wind-short hydro hybrid system in frequency based pricing

    International Nuclear Information System (INIS)

    Malakar, T.; Goswami, S.K.; Sinha, A.K.

    2014-01-01

    Highlights: • This paper presents a new profit centric operating strategy of a hybrid power system under market environment. • The profit is ensured by optimal coordination of RES and load management approach. • The problem is formulated as dynamic optimization problem and solved using ABC algorithm. • Comparison shows that the proposed approach results more profit for the hybrid system. - Abstract: In the post restructuring era of electrical power system, each of the generating farm or utility has its own business strategy in terms of generation planning, load management and for other decisions. The basic objective of the utility is to maximize the operational profit for a given period of time. Generation scheduling for a utility with wind farm largely depends on the accuracy of wind power prediction. Therefore, it is important to explore the suitability of load management approach in coordination with the use of energy storage facility to compensate the uncertainty in wind power generation. This paper focuses mainly the operating strategy of a grid connected small hybrid power system to maximize its profit by adopting coordination between load management technique and utilization of storage plant under frequency based pricing. The optimum load scheduling has been implemented to utilities own local load. An hourly-discretized optimization algorithm is proposed and solved using artificial bee colony algorithm. To verify the effectiveness of the proposed method, the optimization problem is solved for varied wind power scenarios with different demand expectations cases in a day ahead Indian electricity market. It is noted that the proposed load management approach results more profit for the hybrid system because of better power management compared to the case when load scheduling has not been incorporated. The solution of the proposed optimization algorithm gives the strategies to be followed by the hybrid system how to operate its pump storage unit and to

  5. 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.

  6. New heating schedule in hydrogen annealing furnace based on process simulation for less energy consumption

    International Nuclear Information System (INIS)

    Saboonchi, Ahmad; Hassanpour, Saeid; Abbasi, Shahram

    2008-01-01

    Cold rolled steel coils are annealed in batch furnaces to obtain desirable mechanical properties. Annealing operations involve heating and cooling cycles which take long due to high weight of the coils under annealing. To reduce annealing time, a simulation code was developed that is capable of evaluating more effective schedules for annealing coils during the heating process. This code is additionally capable of accurate determination of furnace turn-off time for different coil weights and charge dimensions. After studying many heating schedules and considering heat transfer mechanism in the annealing furnace, a new schedule with the most advantages was selected as the new operation conditions in the hydrogen annealing plant. The performance of all the furnaces were adjusted to the new heating schedule after experiments had been carried out to ensure the accuracy of the code and the fitness of the new operation condition. Comparison of similar yield of cold rolled coils over two months revealed that specific energy consumption of furnaces under the new heating schedule decreased by 11%, heating cycle time by 16%, and the hydrogen consumption by 14%

  7. New heating schedule in hydrogen annealing furnace based on process simulation for less energy consumption

    Energy Technology Data Exchange (ETDEWEB)

    Saboonchi, Ahmad [Department of Mechanical Engineering, Isfahan University of Technology, Isfahan 84154 (Iran); Hassanpour, Saeid [Rayan Tahlil Sepahan Co., Isfahan Science and Technology Town, Isfahan 84155 (Iran); Abbasi, Shahram [R and D Department, Mobarakeh Steel Complex, Isfahan (Iran)

    2008-11-15

    Cold rolled steel coils are annealed in batch furnaces to obtain desirable mechanical properties. Annealing operations involve heating and cooling cycles which take long due to high weight of the coils under annealing. To reduce annealing time, a simulation code was developed that is capable of evaluating more effective schedules for annealing coils during the heating process. This code is additionally capable of accurate determination of furnace turn-off time for different coil weights and charge dimensions. After studying many heating schedules and considering heat transfer mechanism in the annealing furnace, a new schedule with the most advantages was selected as the new operation conditions in the hydrogen annealing plant. The performance of all the furnaces were adjusted to the new heating schedule after experiments had been carried out to ensure the accuracy of the code and the fitness of the new operation condition. Comparison of similar yield of cold rolled coils over two months revealed that specific energy consumption of furnaces under the new heating schedule decreased by 11%, heating cycle time by 16%, and the hydrogen consumption by 14%. (author)

  8. Planning Risk-Based SQC Schedules for Bracketed Operation of Continuous Production Analyzers.

    Science.gov (United States)

    Westgard, James O; Bayat, Hassan; Westgard, Sten A

    2018-02-01

    To minimize patient risk, "bracketed" statistical quality control (SQC) is recommended in the new CLSI guidelines for SQC (C24-Ed4). Bracketed SQC requires that a QC event both precedes and follows (brackets) a group of patient samples. In optimizing a QC schedule, the frequency of QC or run size becomes an important planning consideration to maintain quality and also facilitate responsive reporting of results from continuous operation of high production analytic systems. Different plans for optimizing a bracketed SQC schedule were investigated on the basis of Parvin's model for patient risk and CLSI C24-Ed4's recommendations for establishing QC schedules. A Sigma-metric run size nomogram was used to evaluate different QC schedules for processes of different sigma performance. For high Sigma performance, an effective SQC approach is to employ a multistage QC procedure utilizing a "startup" design at the beginning of production and a "monitor" design periodically throughout production. Example QC schedules are illustrated for applications with measurement procedures having 6-σ, 5-σ, and 4-σ performance. Continuous production analyzers that demonstrate high σ performance can be effectively controlled with multistage SQC designs that employ a startup QC event followed by periodic monitoring or bracketing QC events. Such designs can be optimized to minimize the risk of harm to patients. © 2017 American Association for Clinical Chemistry.

  9. A Multi-layer Dynamic Model for Coordination Based Group Decision Making in Water Resource Allocation and Scheduling

    Science.gov (United States)

    Huang, Wei; Zhang, Xingnan; Li, Chenming; Wang, Jianying

    Management of group decision-making is an important issue in water source management development. In order to overcome the defects in lacking of effective communication and cooperation in the existing decision-making models, this paper proposes a multi-layer dynamic model for coordination in water resource allocation and scheduling based group decision making. By introducing the scheme-recognized cooperative satisfaction index and scheme-adjusted rationality index, the proposed model can solve the problem of poor convergence of multi-round decision-making process in water resource allocation and scheduling. Furthermore, the problem about coordination of limited resources-based group decision-making process can be solved based on the effectiveness of distance-based group of conflict resolution. The simulation results show that the proposed model has better convergence than the existing models.

  10. Efficient Hybrid Genetic Based Multi Dimensional Host Load Aware Algorithm for Scheduling and Optimization of Virtual Machines

    OpenAIRE

    Thiruvenkadam, T; Karthikeyani, V

    2014-01-01

    Mapping the virtual machines to the physical machines cluster is called the VM placement. Placing the VM in the appropriate host is necessary for ensuring the effective resource utilization and minimizing the datacenter cost as well as power. Here we present an efficient hybrid genetic based host load aware algorithm for scheduling and optimization of virtual machines in a cluster of Physical hosts. We developed the algorithm based on two different methods, first initial VM packing is done by...

  11. Performance improvement of per-user threshold based multiuser switched scheduling system

    KAUST Repository

    Nam, Haewoon

    2013-01-01

    SUMMARY This letter proposes a multiuser switched scheduling scheme with per-user threshold and post user selection and provides a generic analytical framework for determining the optimal feedback thresholds. The proposed scheme applies an individual feedback threshold for each user rather than a single common threshold for all users to achieve some capacity gain due to the flexibility of threshold selection as well as a lower scheduling outage probability. In addition, since scheduling outage may occur with a non-negligible probability, the proposed scheme employs post user selection in order to further improve the ergodic capacity, where the user with the highest potential for a higher channel quality than other users is selected. Numerical and simulation results show that the capacity gain by post user selection is significant when random sequence is used. Copyright © 2013 The Institute of Electronics, Information and Communication Engineers.

  12. DEVELOPMENT OF GENETIC ALGORITHM-BASED METHODOLOGY FOR SCHEDULING OF MOBILE ROBOTS

    DEFF Research Database (Denmark)

    Dang, Vinh Quang

    problem is to minimize the total traveling time of the single mobile robot and thereby increase its availability. For the second scheduling problem, a fleet of mobile robots is considered together with a set of machines to carry out different types of tasks, e.g. pre-assembly or quality inspection. Some...... problem and finding optimal solutions for each one. However, the formulated mathematical models could only be applicable to small-scale problems in practice due to the significant increase of computation time as the problem size grows. Note that making schedules of mobile robots is part of real-time....... For the first scheduling problem, a single mobile robot is considered to collect and transport container of parts and empty them into machine feeders where needed. A limit on carrying capacity of the single mobile robot and hard time windows of part-feeding tasks are considered. The objective of the first...

  13. A Case Study of Line-of-Balance based Schedule Planning and Control System

    OpenAIRE

    Seppänen, Olli; Aalto, Erno

    2005-01-01

    Line-of-Balance is a graphical technique which can be used to plan and manage work flow. It is suit-able for construction projects because of their large degree of repetition. Despite its strengths Line-of-Balance has not gained widespread use in construction industry internationally. However, it has been used as the principal scheduling tool in Finland since 1980s. As a result of two decades of research and use in industry, a comprehensive schedule planning and control system has been develo...

  14. Mortgage lending and house prices in Albania - a co-integrated analysis based on VECM

    Directory of Open Access Journals (Sweden)

    Erjona REBI

    2014-06-01

    Full Text Available The general view that the banks’ lending plays a crucial role in the real estate market was again confirmed during the recent financial crisis. During the precrisis period, house prices in Albania increased rapidly, supported also by a fast expansion of mortgage lending. This study aims to empirically analyse the relation between housing prices and banks’ financing in the long run, referring to a VECM model. The estimated results confirm the important role of mortgage to house prices. Meanwhile, the relation between house prices and interest rates resulted statistically insignificant. Unlike the previous literature, exchange rate has been included as an endogenous variable. Results show positive correlation and statistical significance between house prices and exchange rate. Finally, this paper is expected to contribute to the literature as there are very few studies that elaborate on the macroeconomic factors’ influence on the housing prices in Albania.

  15. Pricing of premiums for equity-linked life insurance based on joint mortality models

    Science.gov (United States)

    Riaman; Parmikanti, K.; Irianingsih, I.; Supian, S.

    2018-03-01

    Life insurance equity - linked is a financial product that not only offers protection, but also investment. The calculation of equity-linked life insurance premiums generally uses mortality tables. Because of advances in medical technology and reduced birth rates, it appears that the use of mortality tables is less relevant in the calculation of premiums. To overcome this problem, we use a combination mortality model which in this study is determined based on Indonesian Mortality table 2011 to determine the chances of death and survival. In this research, we use the Combined Mortality Model of the Weibull, Inverse-Weibull, and Gompertz Mortality Model. After determining the Combined Mortality Model, simulators calculate the value of the claim to be given and the premium price numerically. By calculating equity-linked life insurance premiums well, it is expected that no party will be disadvantaged due to the inaccuracy of the calculation result

  16. A New Availability-Payment Model for Pricing Performance-Based Logistics Contracts

    Science.gov (United States)

    2014-05-01

    Grant number: N00244‐13‐1‐0009 A New “Availability‐ Payment ”  Model  for Pricing Performance‐ Based Logistics Contracts A. KashaniPour, X. Zhu, P...DATE MAY 2014 2. REPORT TYPE 3. DATES COVERED 00-00-2014 to 00-00-2014 4. TITLE AND SUBTITLE A New ’Availability‐ Payment ’ Model for...is how the  payment   model  in the contract  quantifies the contractor’s  performance for awarding incentives  or penalties Discrete‐Event Simulator ut

  17. Early evaluation and value-based pricing of regenerative medicine technologies.

    Science.gov (United States)

    Koerber, Florian; Rolauffs, Bernd; Rogowski, Wolf

    2013-11-01

    Since the first pioneering scientists explored the potential of using human cells for therapeutic purposes the branch of regenerative medicine has evolved to become a mature industry. The focus has switched from 'what can be done' to 'what can be commercialized'. Timely health economic evaluation supports successful marketing by establishing the value of a product from a healthcare system perspective. This article reports results from a research project on early health economic evaluation in collaboration with developers, clinicians and manufacturers. We present an approach to determine an early value-based price for a new treatment of cartilage defects of the knee from the area of regenerative medicine. Examples of using evaluation results for the purpose of business planning, market entry, preparing the coverage decision and managed entry are discussed.

  18. Optimization of multi-objective integrated process planning and scheduling problem using a priority based optimization algorithm

    Science.gov (United States)

    Ausaf, Muhammad Farhan; Gao, Liang; Li, Xinyu

    2015-12-01

    For increasing the overall performance of modern manufacturing systems, effective integration of process planning and scheduling functions has been an important area of consideration among researchers. Owing to the complexity of handling process planning and scheduling simultaneously, most of the research work has been limited to solving the integrated process planning and scheduling (IPPS) problem for a single objective function. As there are many conflicting objectives when dealing with process planning and scheduling, real world problems cannot be fully captured considering only a single objective for optimization. Therefore considering multi-objective IPPS (MOIPPS) problem is inevitable. Unfortunately, only a handful of research papers are available on solving MOIPPS problem. In this paper, an optimization algorithm for solving MOIPPS problem is presented. The proposed algorithm uses a set of dispatching rules coupled with priority assignment to optimize the IPPS problem for various objectives like makespan, total machine load, total tardiness, etc. A fixed sized external archive coupled with a crowding distance mechanism is used to store and maintain the non-dominated solutions. To compare the results with other algorithms, a C-matric based method has been used. Instances from four recent papers have been solved to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed method is an efficient approach for solving the MOIPPS problem.

  19. A PMBGA to Optimize the Selection of Rules for Job Shop Scheduling Based on the Giffler-Thompson Algorithm

    Directory of Open Access Journals (Sweden)

    Rui Zhang

    2012-01-01

    Full Text Available Most existing research on the job shop scheduling problem has been focused on the minimization of makespan (i.e., the completion time of the last job. However, in the fiercely competitive market nowadays, delivery punctuality is more important for maintaining a high service reputation. So in this paper, we aim at solving job shop scheduling problems with the total weighted tardiness objective. Several dispatching rules are adopted in the Giffler-Thompson algorithm for constructing active schedules. It is noticeable that the rule selections for scheduling consecutive operations are not mutually independent but actually interrelated. Under such circumstances, a probabilistic model-building genetic algorithm (PMBGA is proposed to optimize the sequence of selected rules. First, we use Bayesian networks to model the distribution characteristics of high-quality solutions in the population. Then, the new generation of individuals is produced by sampling the established Bayesian network. Finally, some elitist individuals are further improved by a special local search module based on parameter perturbation. The superiority of the proposed approach is verified by extensive computational experiments and comparisons.

  20. 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

  1. 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.

  2. Quantitative Model of Price Diffusion and Market Friction Based on Trading as a Mechanistic Random Process

    Science.gov (United States)

    Daniels, Marcus G.; Farmer, J. Doyne; Gillemot, László; Iori, Giulia; Smith, Eric

    2003-03-01

    We model trading and price formation in a market under the assumption that order arrival and cancellations are Poisson random processes. This model makes testable predictions for the most basic properties of markets, such as the diffusion rate of prices (which is the standard measure of financial risk) and the spread and price impact functions (which are the main determinants of transaction cost). Guided by dimensional analysis, simulation, and mean-field theory, we find scaling relations in terms of order flow rates. We show that even under completely random order flow the need to store supply and demand to facilitate trading induces anomalous diffusion and temporal structure in prices.

  3. Estimating deficit probabilities with price-responsive demand in contract-based electricity markets

    International Nuclear Information System (INIS)

    Galetovic, Alexander; Munoz, Cristian M.

    2009-01-01

    Studies that estimate deficit probabilities in hydrothermal systems have generally ignored the response of demand to changing prices, in the belief that such response is largely irrelevant. We show that ignoring the response of demand to prices can lead to substantial over or under estimation of the probability of an energy deficit. To make our point we present an estimation of deficit probabilities in Chile's Central Interconnected System between 2006 and 2010. This period is characterized by tight supply, fast consumption growth and rising electricity prices. When the response of demand to rising prices is acknowledged, forecasted deficit probabilities and marginal costs are shown to be substantially lower

  4. [Price elasticity of demand for cigarettes and alcohol in Ecuador, based on household data].

    Science.gov (United States)

    Chávez, Ricardo

    2016-10-01

    Estimate price elasticity of demand for cigarettes and alcohol in Ecuador using cross-sectional data from the National Survey of Urban and Rural Household Income and Expenditures (ENIGHUR is the acronym in Spanish) 2011-2012. ENIGHUR 2011-2012 data were used with Deaton's (1, 2) methodology to estimate price elasticity of demand for cigarettes and alcohol with expenditure and quantity information. Household socioeconomic variables were also included. Price elasticity of demand for cigarettes is -0.87, meaning that a 10% price increase could lead to an 8.7% decrease in consumption. Results for cross-price elasticities of alcohol on cigarette demand are negative, as expected, indicating that they are complementary goods; however, the results are not statistically significant. Furthermore, it was found that price elasticity of demand for alcohol is -0.44, meaning that a 10% increase in the price of alcohol would produce a 4.4% decrease in consumption. A policy of price increases, for example, with a tax increase, applied to both cigarettes and alcohol, could have a positive effect on public health through reductions in consumption of both goods. However, this measure would not be sufficient to bridge gaps in prevalence measures and health outcomes between sex and other population groups, given the observed difference in the sensitivity of consumption to price variations.

  5. A comparison of cost-based pricing rules for natural gas distribution utilities

    International Nuclear Information System (INIS)

    Klein, C.C.

    1993-01-01

    Partial-equilibrium social welfare deadweight losses under uniform Ramsey pricing, a cost allocation pricing method, and the actual average revenues by customer class for two natural gas distribution utilities are calculated and compared. Marginal cost estimates are derived from a multiple-output translog variable cost function and used, along with three sets of demand elasticities, to generate the Ramsey prices and welfare losses. The actual and cost-allocation prices are taken directly from rate case files. The largest social welfare losses are associated with the cost-allocation rule, as high as 10-25% of revenue, despite suggestions in the literature to the contrary. (Author)

  6. Effectiveness of Time-Based Attention Schedules on Students in Inclusive Classrooms in Turkey

    Science.gov (United States)

    Sazak Pinar, Elif

    2015-01-01

    This study examines the effectiveness of fixed-time (FT) and variable-time (VT) schedules and attention on the problem behaviors and on-task behaviors of students with and without intellectual disabilities in inclusive classrooms in Turkey. Three second-grade students with intellectual disabilities, three students without intellectual…

  7. Load Scheduling in a Cloud Based Massive Video-Storage Environment

    DEFF Research Database (Denmark)

    Bayyapu, Karunakar Reddy; Fischer, Paul

    2015-01-01

    We propose an architecture for a storage system of surveillance videos. Such systems have to handle massive amounts of incoming video streams and relatively few requests for replay. In such a system load (i.e., Write requests) scheduling is essential to guarantee performance. Large-scale data-sto...

  8. Scheduler-Specific Confidentiality for Multi-Threaded Programs and Its Logic-Based Verification

    NARCIS (Netherlands)

    Huisman, Marieke; Ngo, Minh Tri; Beckert, B.; Damiani, F.; Gurov, D.

    2012-01-01

    Observational determinism has been proposed in the literature as a way to ensure condentiality for multi-threaded programs. Intuitively, a program is observationally deterministic if the behavior of the public variables is deterministic, i.e., independent of the private variables and the scheduling

  9. A duty-period-based formulation of the airline crew scheduling problem

    Energy Technology Data Exchange (ETDEWEB)

    Hoffman, K.

    1994-12-31

    We present a new formulation of the airline crew scheduling problem that explicitly considers the duty periods. We suggest an algorithm for solving the formulation by a column generation approach with branch-and-bound. Computational results are reported for a number of test problems.

  10. 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%.

  11. 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...

  12. Schedule Analytics

    Science.gov (United States)

    2016-04-30

    Warfare, Naval Sea Systems Command Acquisition Cycle Time : Defining the Problem David Tate, Institute for Defense Analyses Schedule Analytics Jennifer...research was comprised of the following high- level steps :  Identify and review primary data sources 1...research. However, detailed reviews of the OMB IT Dashboard data revealed that schedule data is highly aggregated. Program start date and program end date

  13. 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.

  14. Evaluating price-based demand response in practice – with application to the EcoGrid EU Experiment

    DEFF Research Database (Denmark)

    Le Ray, Guillaume; Larsen, Emil Mahler; Pinson, Pierre

    2016-01-01

    users is exploited in the power system, e.g. for system balancing. However, very few real-world experiments have been carried out and price-based demand response has consistently been found difficult to assess and quantify. It is our aim here to describe an approach to do so, as motivated by the large......Increased emphasis is placed today on various types of demand response, motivated by the integration of renewable energy generation and efficiency improvements in electricity markets. Some advocated for the development of price-based approaches, where the conditional dynamic elasticity of final...

  15. 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...

  16. A demand response modeling for residential consumers in smart grid environment using game theory based energy scheduling algorithm

    Directory of Open Access Journals (Sweden)

    S. Sofana Reka

    2016-06-01

    Full Text Available In this paper, demand response modeling scheme is proposed for residential consumers using game theory algorithm as Generalized Tit for Tat (GTFT Dominant Game based Energy Scheduler. The methodology is established as a work flow domain model between the utility and the user considering the smart grid framework. It exhibits an algorithm which schedules load usage by creating several possible tariffs for consumers such that demand is never raised. This can be done both individually and among multiple users of a community. The uniqueness behind the demand response proposed is that, the tariff is calculated for all hours and the load during the peak hours which can be rescheduled is shifted based on the Peak Average Ratio. To enable the vitality of the work simulation results of a general case of three domestic consumers are modeled extended to a comparative performance and evaluation with other algorithms and inference is analyzed.

  17. Enhanced first-in-first-out-based round-robin multicast scheduling algorithm for input-queued switches

    DEFF Research Database (Denmark)

    Yu, Hao; Ruepp, Sarah Renée; Berger, Michael Stübert

    2011-01-01

    This study focuses on the multicast scheduling for M × N input-queued switches. An enhanced first-in-first-out -based round-robin multicast scheduling algorithm is proposed with a function of searching deeper into queues to reduce the head-of-line (HOL) blocking problem and thereby the multicast...... out on the decision matrix to reduce the number of transmission for each cell. To reduce the HOL blocking problem, a complement matrix is constructed based on the traffic matrix and the decision matrix, and a process of searching deeper into the queues is carried out to find cells that can be sent...... to the idle outputs. Simulation results show that the proposed function of searching deeper into the queues can alleviate the HOL blocking and as a result reduce the multicast latency significantly. Under both balanced and unbalanced multicast traffic, the proposed algorithm is able to maintain a stable...

  18. Algorithm for complete enumeration based on a stroke graph to solve the supply network configuration and operations scheduling problem

    Directory of Open Access Journals (Sweden)

    Julien Maheut

    2013-07-01

    Full Text Available Purpose: The purpose of this paper is to present an algorithm that solves the supply network configuration and operations scheduling problem in a mass customization company that faces alternative operations for one specific tool machine order in a multiplant context. Design/methodology/approach: To achieve this objective, the supply chain network configuration and operations scheduling problem is presented. A model based on stroke graphs allows the design of an algorithm that enumerates all the feasible solutions. The algorithm considers the arrival of a new customized order proposal which has to be inserted into a scheduled program. A selection function is then used to choose the solutions to be simulated in a specific simulation tool implemented in a Decision Support System. Findings and Originality/value: The algorithm itself proves efficient to find all feasible solutions when alternative operations must be considered. The stroke structure is successfully used to schedule operations when considering more than one manufacturing and supply option in each step. Research limitations/implications: This paper includes only the algorithm structure for a one-by-one, sequenced introduction of new products into the list of units to be manufactured. Therefore, the lotsizing process is done on a lot-per-lot basis. Moreover, the validation analysis is done through a case study and no generalization can be done without risk. Practical implications: The result of this research would help stakeholders to determine all the feasible and practical solutions for their problem. It would also allow to assessing the total costs and delivery times of each solution. Moreover, the Decision Support System proves useful to assess alternative solutions. Originality/value: This research offers a simple algorithm that helps solve the supply network configuration problem and, simultaneously, the scheduling problem by considering alternative operations. The proposed system

  19. Real-Time Pricing Strategy Based on the Stability of Smart Grid for Green Internet of Things

    Directory of Open Access Journals (Sweden)

    Huwei Chen

    2017-01-01

    Full Text Available The ever increasing demand of energy efficiency and the strong awareness of environment have led to the enhanced interests in green Internet of things (IoTs. How to efficiently deliver power, especially, with the smart grid based on the stability of network becomes a challenge for green IoTs. Therefore, in this paper we present a novel real-time pricing strategy based on the network stability in the green IoTs enabled smart grid. Firstly, the outage is analyzed by considering the imbalance of power supply and demand as well as the load uncertainty. Secondly, the problem of power supply with multiple-retailers is formulated as a Stackelberg game, where the optimal price can be obtained with the maximal profit for retailers and users. Thirdly, the stability of price is analyzed under the constraints. In addition, simulation results show the efficiency of the proposed strategy.

  20. 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)