Model-based Optimization of Oil Recovery: Robust Operational Strategies
Van Essen, G.M.
2015-01-01
The process of depleting an oil reservoir can be poured into an optimal control problem with the objective to maximize economic performance over the life of the ﬁeld. Despite its large potential, life-cycle optimization has not yet found its way into operational environments. The objective of this t
DEFF Research Database (Denmark)
Lund, Henrik; Salgi, Georges; Elmegaard, Brian;
2009-01-01
on electricity spot markets by storing energy when electricity prices are low and producing electricity when prices are high. In order to make a profit on such markets, CAES plant operators have to identify proper strategies to decide when to sell and when to buy electricity. This paper describes three...... plants will not be able to achieve such optimal operation, since the fluctuations of spot market prices in the coming hours and days are not known. Consequently, two simple practical strategies have been identified and compared to the results of the optimal strategy. This comparison shows that...... independent computer-based methodologies which may be used for identifying the optimal operation strategy for a given CAES plant, on a given spot market and in a given year. The optimal strategy is identified as the one which provides the best business-economic net earnings for the plant. In practice, CAES...
Integrated emission management strategy for cost-optimal engine-aftertreatment operation
Cloudt, R.P.M.; Willems, F.P.T.
2011-01-01
A new cost-based control strategy is presented that optimizes engine-aftertreatment performance under all operating conditions. This Integrated Emission Management strategy minimizes fuel consumption within the set emission limits by on-line adjustment of air management based on the actual state of
An Optimal Operating Strategy for Battery Life Cycle Costs in Electric Vehicles
Directory of Open Access Journals (Sweden)
Yinghua Han
2014-01-01
Full Text Available Impact on petroleum based vehicles on the environment, cost, and availability of fuel has led to an increased interest in electric vehicle as a means of transportation. Battery is a major component in an electric vehicle. Economic viability of these vehicles depends on the availability of cost-effective batteries. This paper presents a generalized formulation for determining the optimal operating strategy and cost optimization for battery. Assume that the deterioration of the battery is stochastic. Under the assumptions, the proposed operating strategy for battery is formulated as a nonlinear optimization problem considering reliability and failure number. And an explicit expression of the average cost rate is derived for battery lifetime. Results show that the proposed operating strategy enhances the availability and reliability at a low cost.
Optimal offering and operating strategies for wind-storage systems with linear decision rules
DEFF Research Database (Denmark)
Ding, Huajie; Pinson, Pierre; Hu, Zechun
2016-01-01
The participation of wind farm-energy storage systems (WF-ESS) in electricity markets calls for an integrated view of day-ahead offering strategies and real-time operation policies. Such an integrated strategy is proposed here by co-optimizing offering at the day-ahead stage and operation policy...... to be used at the balancing stage. Linear decision rules are seen as a natural approach to model and optimize the real-time operation policy. These allow enhancing profits from balancing markets based on updated information on prices and wind power generation. Our integrated strategies for WF...
Zhu, Senlai; Guo, Yuntao; Chen, Jingxu; Li, Dawei; Cheng, Lin
2017-08-02
Most existing network sensor location problem (NSLP) models are designed to identify the number of sensors with fixed costs and installation locations, and sensors are assumed to be installed permanently. However, sometimes sensors are carried by individuals to collect traffic data measurements manually at fixed locations. Hence, their duration of operation for which traffic data measurements are collected is limited, and their costs are not fixed as they are correlated with the duration of operation. This paper proposes a NSLP model that integrates optimal heterogeneous sensor deployment and operation strategies for the dynamic O-D demand estimates under budget constraints. The deployment strategy consists of the numbers of link and node sensors and their installation locations. The operation strategy includes sensors' start time and duration of operation, which has not been addressed in previous studies. An algorithm is developed to solve the proposed model. Numerical experiments performed on a network from a part of Chennai, India show that the proposed model can identify the optimal heterogeneous sensor deployment and operation strategies with the maximum dynamic O-D demand estimation accuracy.
Kiran, B. S.; Singh, Satyendra; Negi, Kuldeep
The GSAT-12 spacecraft is providing Communication services from the INSAT/GSAT system in the Indian region. The spacecraft carries 12 extended C-band transponders. GSAT-12 was launched by ISRO’s PSLV from Sriharikota, into a sub-geosynchronous Transfer Orbit (sub-GTO) of 284 x 21000 km with inclination 18 deg. This Mission successfully accomplished combined optimization of launch vehicle and satellite capabilities to maximize operational life of the s/c. This paper describes mission analysis carried out for GSAT-12 comprising launch window, orbital events study and orbit raising maneuver strategies considering various Mission operational constraints. GSAT-12 is equipped with two earth sensors (ES), three gyroscopes and digital sun sensor. The launch window was generated considering mission requirement of minimum 45 minutes of ES data for calibration of gyros with Roll-sun-pointing orientation in T.O. Since the T.O. period was a rather short 6.1 hr, required pitch biases were worked out to meet the gyro-calibration requirement. A 440 N Liquid Apogee Motor (LAM) is used for orbit raising. The objective of the maneuver strategy is to achieve desired drift orbit satisfying mission constraints and minimizing propellant expenditure. In case of sub-GTO, the optimal strategy is to first perform an in-plane maneuver at perigee to raise the apogee to synchronous level and then perform combined maneuvers at the synchronous apogee to achieve desired drift orbit. The perigee burn opportunities were examined considering ground station visibility requirement for monitoring the burn. Two maneuver strategies were proposed: an optimal five-burn strategy with two perigee burns centered around perigee#5 and perigee#8 with partial ground station visibility and three apogee burns with dual station visibility, a near-optimal five-burn strategy with two off-perigee burns at perigee#5 and perigee#8 with single ground station visibility and three apogee burns with dual station visibility
A Dynamic Optimization Strategy for the Operation of Large Scale Seawater Reverses Osmosis System
Directory of Open Access Journals (Sweden)
Aipeng Jiang
2014-01-01
Full Text Available In this work, an efficient strategy was proposed for efficient solution of the dynamic model of SWRO system. Since the dynamic model is formulated by a set of differential-algebraic equations, simultaneous strategies based on collocations on finite element were used to transform the DAOP into large scale nonlinear programming problem named Opt2. Then, simulation of RO process and storage tanks was carried element by element and step by step with fixed control variables. All the obtained values of these variables then were used as the initial value for the optimal solution of SWRO system. Finally, in order to accelerate the computing efficiency and at the same time to keep enough accuracy for the solution of Opt2, a simple but efficient finite element refinement rule was used to reduce the scale of Opt2. The proposed strategy was applied to a large scale SWRO system with 8 RO plants and 4 storage tanks as case study. Computing result shows that the proposed strategy is quite effective for optimal operation of the large scale SWRO system; the optimal problem can be successfully solved within decades of iterations and several minutes when load and other operating parameters fluctuate.
DEFF Research Database (Denmark)
Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte
2010-01-01
Since the hourly spot market price is available one day ahead, the price could be transferred to the consumers and they may have some motivations to install an energy storage system in order to save their energy costs. This paper presents an optimal operation strategy for a battery energy storage...... system (BESS) in relation to the real-time electricity price in order to achieve the maximum profits of the BESS. The western Danish power system, which is currently the grid area in the world that has the largest share of wind power in its generation profiles and may represent the future of electricity...
Parameter Optimization and Operating Strategy of a TEG System for Railway Vehicles
Heghmanns, A.; Wilbrecht, S.; Beitelschmidt, M.; Geradts, K.
2016-03-01
A thermoelectric generator (TEG) system demonstrator for diesel electric locomotives with the objective of reducing the mechanical load on the thermoelectric modules (TEM) is developed and constructed to validate a one-dimensional thermo-fluid flow simulation model. The model is in good agreement with the measurements and basis for the optimization of the TEG's geometry by a genetic multi objective algorithm. The best solution has a maximum power output of approx. 2.7 kW and does not exceed the maximum back pressure of the diesel engine nor the maximum TEM hot side temperature. To maximize the reduction of the fuel consumption, an operating strategy regarding the system power output for the TEG system is developed. Finally, the potential consumption reduction in passenger and freight traffic operating modes is estimated under realistic driving conditions by means of a power train and lateral dynamics model. The fuel savings are between 0.5% and 0.7%, depending on the driving style.
Wang, Yan; Huang, Song; Ji, Zhicheng
2017-07-01
This paper presents a hybrid particle swarm optimization and gravitational search algorithm based on hybrid mutation strategy (HGSAPSO-M) to optimize economic dispatch (ED) including distributed generations (DGs) considering market-based energy pricing. A daily ED model was formulated and a hybrid mutation strategy was adopted in HGSAPSO-M. The hybrid mutation strategy includes two mutation operators, chaotic mutation, Gaussian mutation. The proposed algorithm was tested on IEEE-33 bus and results show that the approach is effective for this problem.
Directory of Open Access Journals (Sweden)
Moein parastegari
2015-03-01
Full Text Available Optimal operation and bidding strategy of renewable units are two important problems of the restructured power market. In this paper, a new method for the joint operation of wind, photovoltaic and pump-storage units in day ahead power market is studied to increase the profit of joint units. In this study, artificial neural network is used to predict the wind power generation of wind farms. Since, there are uncertainties in energy and reserve prices, wind and photovoltaic power generation, the optimal operation of joint units can be modeled as a stochastic optimization problem. For this purpose, uncertainties of parameters are modeled by scenario tree method. The performance of the proposed method is evaluated on the renewable energy resources (wind farms, photovoltaic and pump-storage units of the modified IEEE 118 bus test system. Results of the proposed joint operation of renewable resources confirm that the value of expected profit increases in comparison with uncoordinated operation (UO of units.
Optimal Offering and Operating Strategy for a Large Wind-Storage System as a Price Maker
DEFF Research Database (Denmark)
Ding, Huajie; Pinson, Pierre; Hu, Zechun
2017-01-01
Wind farms and energy storage systems are playing increasingly more important roles in power systems, which makes their offering non-negligible in some markets. From the perspective of wind farm-energy storage systems (WF-ESS), this paper proposes an integrated strategy of day-ahead offering...... and real-time operation policies to maximize their overall profit. As participants with large capacity in electricity markets can influence cleared prices by strategic offering, a large scaled WFESS is assumed to be a price maker in day-ahead markets. Correspondingly, the strategy considers influence...
Sun, Congcong; Wang, Zhijie; Liu, Sanming; Jiang, Xiuchen; Sheng, Gehao; Liu, Tianyu
2017-05-01
Wind power has the advantages of being clean and non-polluting and the development of bundled wind-thermal generation power systems (BWTGSs) is one of the important means to improve wind power accommodation rate and implement “clean alternative” on generation side. A two-stage optimization strategy for BWTGSs considering wind speed forecasting results and load characteristics is proposed. By taking short-term wind speed forecasting results of generation side and load characteristics of demand side into account, a two-stage optimization model for BWTGSs is formulated. By using the environmental benefit index of BWTGSs as the objective function, supply-demand balance and generator operation as the constraints, the first-stage optimization model is developed with the chance-constrained programming theory. By using the operation cost for BWTGSs as the objective function, the second-stage optimization model is developed with the greedy algorithm. The improved PSO algorithm is employed to solve the model and numerical test verifies the effectiveness of the proposed strategy.
Optimal GENCO bidding strategy
Gao, Feng
Electricity industries worldwide are undergoing a period of profound upheaval. The conventional vertically integrated mechanism is being replaced by a competitive market environment. Generation companies have incentives to apply novel technologies to lower production costs, for example: Combined Cycle units. Economic dispatch with Combined Cycle units becomes a non-convex optimization problem, which is difficult if not impossible to solve by conventional methods. Several techniques are proposed here: Mixed Integer Linear Programming, a hybrid method, as well as Evolutionary Algorithms. Evolutionary Algorithms share a common mechanism, stochastic searching per generation. The stochastic property makes evolutionary algorithms robust and adaptive enough to solve a non-convex optimization problem. This research implements GA, EP, and PS algorithms for economic dispatch with Combined Cycle units, and makes a comparison with classical Mixed Integer Linear Programming. The electricity market equilibrium model not only helps Independent System Operator/Regulator analyze market performance and market power, but also provides Market Participants the ability to build optimal bidding strategies based on Microeconomics analysis. Supply Function Equilibrium (SFE) is attractive compared to traditional models. This research identifies a proper SFE model, which can be applied to a multiple period situation. The equilibrium condition using discrete time optimal control is then developed for fuel resource constraints. Finally, the research discusses the issues of multiple equilibria and mixed strategies, which are caused by the transmission network. Additionally, an advantage of the proposed model for merchant transmission planning is discussed. A market simulator is a valuable training and evaluation tool to assist sellers, buyers, and regulators to understand market performance and make better decisions. A traditional optimization model may not be enough to consider the distributed
Liu, Xing; Hou, Kun Mean; de Vaulx, Christophe; Xu, Jun; Yang, Jianfeng; Zhou, Haiying; Shi, Hongling; Zhou, Peng
2015-01-01
Memory and energy optimization strategies are essential for the resource-constrained wireless sensor network (WSN) nodes. In this article, a new memory-optimized and energy-optimized multithreaded WSN operating system (OS) LiveOS is designed and implemented. Memory cost of LiveOS is optimized by using the stack-shifting hybrid scheduling approach. Different from the traditional multithreaded OS in which thread stacks are allocated statically by the pre-reservation, thread stacks in LiveOS are allocated dynamically by using the stack-shifting technique. As a result, memory waste problems caused by the static pre-reservation can be avoided. In addition to the stack-shifting dynamic allocation approach, the hybrid scheduling mechanism which can decrease both the thread scheduling overhead and the thread stack number is also implemented in LiveOS. With these mechanisms, the stack memory cost of LiveOS can be reduced more than 50% if compared to that of a traditional multithreaded OS. Not is memory cost optimized, but also the energy cost is optimized in LiveOS, and this is achieved by using the multi-core “context aware” and multi-core “power-off/wakeup” energy conservation approaches. By using these approaches, energy cost of LiveOS can be reduced more than 30% when compared to the single-core WSN system. Memory and energy optimization strategies in LiveOS not only prolong the lifetime of WSN nodes, but also make the multithreaded OS feasible to run on the memory-constrained WSN nodes. PMID:25545264
Directory of Open Access Journals (Sweden)
Xing Liu
2014-12-01
Full Text Available Memory and energy optimization strategies are essential for the resource-constrained wireless sensor network (WSN nodes. In this article, a new memory-optimized and energy-optimized multithreaded WSN operating system (OS LiveOS is designed and implemented. Memory cost of LiveOS is optimized by using the stack-shifting hybrid scheduling approach. Different from the traditional multithreaded OS in which thread stacks are allocated statically by the pre-reservation, thread stacks in LiveOS are allocated dynamically by using the stack-shifting technique. As a result, memory waste problems caused by the static pre-reservation can be avoided. In addition to the stack-shifting dynamic allocation approach, the hybrid scheduling mechanism which can decrease both the thread scheduling overhead and the thread stack number is also implemented in LiveOS. With these mechanisms, the stack memory cost of LiveOS can be reduced more than 50% if compared to that of a traditional multithreaded OS. Not is memory cost optimized, but also the energy cost is optimized in LiveOS, and this is achieved by using the multi-core “context aware” and multi-core “power-off/wakeup” energy conservation approaches. By using these approaches, energy cost of LiveOS can be reduced more than 30% when compared to the single-core WSN system. Memory and energy optimization strategies in LiveOS not only prolong the lifetime of WSN nodes, but also make the multithreaded OS feasible to run on the memory-constrained WSN nodes.
Liu, Xing; Hou, Kun Mean; de Vaulx, Christophe; Xu, Jun; Yang, Jianfeng; Zhou, Haiying; Shi, Hongling; Zhou, Peng
2014-12-23
Memory and energy optimization strategies are essential for the resource-constrained wireless sensor network (WSN) nodes. In this article, a new memory-optimized and energy-optimized multithreaded WSN operating system (OS) LiveOS is designed and implemented. Memory cost of LiveOS is optimized by using the stack-shifting hybrid scheduling approach. Different from the traditional multithreaded OS in which thread stacks are allocated statically by the pre-reservation, thread stacks in LiveOS are allocated dynamically by using the stack-shifting technique. As a result, memory waste problems caused by the static pre-reservation can be avoided. In addition to the stack-shifting dynamic allocation approach, the hybrid scheduling mechanism which can decrease both the thread scheduling overhead and the thread stack number is also implemented in LiveOS. With these mechanisms, the stack memory cost of LiveOS can be reduced more than 50% if compared to that of a traditional multithreaded OS. Not is memory cost optimized, but also the energy cost is optimized in LiveOS, and this is achieved by using the multi-core "context aware" and multi-core "power-off/wakeup" energy conservation approaches. By using these approaches, energy cost of LiveOS can be reduced more than 30% when compared to the single-core WSN system. Memory and energy optimization strategies in LiveOS not only prolong the lifetime of WSN nodes, but also make the multithreaded OS feasible to run on the memory-constrained WSN nodes.
Chen, Robert T. N.; Zhao, Yi-Yuan; Aiken, Edwin W. (Technical Monitor)
1995-01-01
Engine failure represents a major safety concern to helicopter operations, especially in the critical flight phases of takeoff and landing from/to small, confined areas. As a result, the JAA and FAA both certificate a transport helicopter as either Category-A or Category-B according to the ability to continue its operations following engine failures. A Category-B helicopter must be able to land safely in the event of one or all engine failures. There is no requirement, however, for continued flight capability. In contrast, Category-A certification, which applies to multi-engine transport helicopters with independent engine systems, requires that they continue the flight with one engine inoperative (OEI). These stringent requirements, while permitting its operations from rooftops and oil rigs and flight to areas where no emergency landing sites are available, restrict the payload of a Category-A transport helicopter to a value safe for continued flight as well as for landing with one engine inoperative. The current certification process involves extensive flight tests, which are potentially dangerous, costly, and time consuming. These tests require the pilot to simulate engine failures at increasingly critical conditions, Flight manuals based on these tests tend to provide very conservative recommendations with regard to maximum takeoff weight or required runway length. There are very few theoretical studies on this subject to identify the fundamental parameters and tradeoff factors involved. Furthermore, a capability for real-time generation of OEI optimal trajectories is very desirable for providing timely cockpit display guidance to assist the pilot in reducing his workload and to increase safety in a consistent and reliable manner. A joint research program involving NASA Ames Research Center, the FAA, and the University of Minnesota is being conducted to determine OEI optimal control strategies and the associated optimal,trajectories for continued takeoff (CTO
Directory of Open Access Journals (Sweden)
Tinggui Chen
2014-01-01
Full Text Available Artificial bee colony (ABC algorithm, inspired by the intelligent foraging behavior of honey bees, was proposed by Karaboga. It has been shown to be superior to some conventional intelligent algorithms such as genetic algorithm (GA, artificial colony optimization (ACO, and particle swarm optimization (PSO. However, the ABC still has some limitations. For example, ABC can easily get trapped in the local optimum when handing in functions that have a narrow curving valley, a high eccentric ellipse, or complex multimodal functions. As a result, we proposed an enhanced ABC algorithm called EABC by introducing self-adaptive searching strategy and artificial immune network operators to improve the exploitation and exploration. The simulation results tested on a suite of unimodal or multimodal benchmark functions illustrate that the EABC algorithm outperforms ACO, PSO, and the basic ABC in most of the experiments.
Directory of Open Access Journals (Sweden)
Xumei Chen
2017-09-01
Full Text Available The idea of corporate social responsibility has promoted bus operation agencies to rethink how to provide not only efficient but also environmentally friendly services for residents. A study on the potential of using an optimized design of skip-stop services, one of the essential operational strategies in practice, to reduce emissions is conducted in this paper. The underlying scheduling problem is formulated as a nonlinear programming problem with the primary objective of optimizing the total costs for both passengers and operating agencies, as well as with the secondary objective of minimizing bus emissions. A solution method is developed to solve the problem. A real-world case of Route 16 in Beijing is studied, in which the optimal scheduling strategy that maximizes the cost savings and environmental benefits is determined. The costs and emissions of the proposed scheduling strategy are compared with the optimal scheduling with skip-stop services without considering bus emissions. The results show that the proposed scheduling strategy outperforms the other operating strategy with respect to operational costs and bus emissions. A sensitivity study is then conducted to investigate the impact of the fleet size in operations and passenger demand on the effectiveness of the proposed stop-skipping strategy considering bus emissions.
Optimal Strategy in Basketball
Skinner, Brian
2015-01-01
This book chapter reviews some of the major principles associated with optimal strategy in basketball. In particular, we consider the principles of allocative efficiency (optimal allocation of shots between offensive options), dynamic efficiency (optimal shot selection in the face of pressure from the shot clock), and the risk/reward tradeoff (strategic manipulation of outcome variance). For each principle, we provide a simple example of a strategic problem and show how it can be described analytically. We then review general analytical results and provide an overview of existing statistical studies. A number of open challenges in basketball analysis are highlighted.
Directory of Open Access Journals (Sweden)
Zengqiang Mi
2016-01-01
Full Text Available A novel control strategy based on the optimization of transfer trajectory at operation points for DFIG is proposed. Aim of this control strategy is to reduce the mechanical fatigue of DFIG caused by the frequent adjustment of rotating speed and pitch angle when operating in the islanded power system. Firstly, the stability of DFIG at different operation points is analyzed. Then an optimization model of transfer trajectory at operation points is established, with the minimum synthetic adjustment amount of rotating speed and pitch angle as the objective function and with the balance of active power and the stability of operation points as the constraint conditions. Secondly, the wind speed estimator is designed, and the control strategy of pitch system is improved to cooperate with the indirect stator flux orientation control technology for rotor-side inverter control. Then by the coordination control of its rotating speed and pitch angle, an operation trajectory controller is established to ensure the islanded operation of DFIG along the optimal transfer trajectory. Finally, the simulation results show that the proposed control strategy is technical feasibility with good performance.
Operations Strategy in practice
DEFF Research Database (Denmark)
Rytter, Niels Gorm; Koch, Christian; Boer, Harry
2005-01-01
In this paper, we describe and illustrate a new, action-based longitudinal case study approach, which aims at helping scholars narrow the gap between the theory and practice of Operations Strategy (OS). First, we elaborate on the need for new research methods for studying OS in practice. Then, we...... present the two research strategies underpinning the approach proposed here: action research and longitudinal case study. Next, we illustrate the use of the method and exemplify it using a recent study of OS in practice. Then, based on this experience we present and discuss the advantages...... and disadvantages of the method. Finally, we draw conclusions on its potential for operations strategy and operations management studies....
Network Structure Expert System and Operation Optimization
Institute of Scientific and Technical Information of China (English)
刘洪谦; 袁希钢; 麻德贤
2003-01-01
It is proposed that double level programming technique may be adopted in synthesis strategy. Optimization of heat exchanger network structural configuration (the master problem) may be solved at the upper level, leaving the rest operating conditions( the slave problem) being optimized at the lower level. With the uniqueness in mind, an HEN synthesis expert system may be employed to address both the logical constraints and the global operation parameters′ optimization using enhanced sequential number optimization theory.Case studies demonstrate that the synthesis strategy proposed can effectively simplify both the problem-solving and the synthesis process. The validity of the strategy recommended is evidenced by case studies′ results compared.
Resilient Grid Operational Strategies
Energy Technology Data Exchange (ETDEWEB)
Pasqualini, Donatella [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-03-01
Extreme weather-related disturbances, such as hurricanes, are a leading cause of grid outages historically. Although physical asset hardening is perhaps the most common way to mitigate the impacts of severe weather, operational strategies may be deployed to limit the extent of societal and economic losses associated with weather-related physical damage.1 The purpose of this study is to examine bulk power-system operational strategies that can be deployed to mitigate the impact of severe weather disruptions caused by hurricanes, thereby increasing grid resilience to maintain continuity of critical infrastructure during extreme weather. To estimate the impacts of resilient grid operational strategies, Los Alamos National Laboratory (LANL) developed a framework for hurricane probabilistic risk analysis (PRA). The probabilistic nature of this framework allows us to estimate the probability distribution of likely impacts, as opposed to the worst-case impacts. The project scope does not include strategies that are not operations related, such as transmission system hardening (e.g., undergrounding, transmission tower reinforcement and substation flood protection) and solutions in the distribution network.
Operations Strategy in practice
DEFF Research Database (Denmark)
Rytter, Niels Gorm; Koch, Christian; Boer, Harry
2005-01-01
In this paper, we describe and illustrate a new, action-based longitudinal case study approach, which aims at helping scholars narrow the gap between the theory and practice of Operations Strategy (OS). First, we elaborate on the need for new research methods for studying OS in practice. Then, we...... and disadvantages of the method. Finally, we draw conclusions on its potential for operations strategy and operations management studies.......In this paper, we describe and illustrate a new, action-based longitudinal case study approach, which aims at helping scholars narrow the gap between the theory and practice of Operations Strategy (OS). First, we elaborate on the need for new research methods for studying OS in practice. Then, we...... present the two research strategies underpinning the approach proposed here: action research and longitudinal case study. Next, we illustrate the use of the method and exemplify it using a recent study of OS in practice. Then, based on this experience we present and discuss the advantages...
Developing & Optimizing a Logical Sourcing Strategy
National Research Council Canada - National Science Library
Lee S Scheible; Chris Bodurow; Karin Daun
2015-01-01
In order to optimize the benefit of the sourcing strategy and ensure delivery of the portfolio, a logical operational process flow must be developed and implemented consistently across all study...
Hu, Zhe; Yu, Yi; Wang, Guangjin; Chen, Xuesong; Chen, Pei; Chen, Jun; Zhou, Su
2016-07-01
Dead-ended anode (DEA) mode is commonly applied in fuel cell vehicles for the hydrogen purge at the anode side, to reduce fuel waste and enhance fuel cell efficiency. Anode purge is necessary and is definitely important with respect to removing liquid water and accumulated nitrogen in the gas diffusion layer and the flow field of the DEA-mode fuel cell. In this paper, the effect of different purge strategies on the stack performance and system efficiency is investigated experimentally using fast data acquisition and advanced tools, such as the fast cell voltage measurement (CVM) system and the mass spectrum. From the fast data acquisition, the voltage stability, liquid water and nitrogen concentration measurement in the anode exhaust are compared and analyzed under different purge strategy designs and using different purge valves. The results show that under the optimal purge strategy, the DEA fuel cell stack can achieve the desired stability and system efficiency based on the analysis of the cell voltage and purge volume. Moreover, the diameter of the purge valve has a great impact on the voltage stability because a diameter change will result in a different pressure drop and purge volume when the purge valve is open.
Evolution Strategies in Optimization Problems
Cruz, Pedro A F
2007-01-01
Evolution Strategies are inspired in biology and part of a larger research field known as Evolutionary Algorithms. Those strategies perform a random search in the space of admissible functions, aiming to optimize some given objective function. We show that simple evolution strategies are a useful tool in optimal control, permitting to obtain, in an efficient way, good approximations to the solutions of some recent and challenging optimal control problems.
Conceptualizing operations strategy processes
DEFF Research Database (Denmark)
Rytter, Niels Gorm; Boer, Harry; Koch, Christian
2007-01-01
Purpose - The purpose of this paper is to present insights into operations strategy (OS) in practice. It outlines a conceptualization and model of OS processes and, based on findings from an in-depth and longitudinal case study, contributes to further development of extant OS models and methods...... which presently mainly focus on OS content, as distinct from process issues. DesignImethodology/approach - The methodology combines action research and a longitudinal single site case study of OS processes in practice. Findings - The paper conceptualises an OS process as: events of dialogue and action...... provides a useful tool for describing and analyzing real-time OS processes unfolding in practice. Research limitations/implications - The research is based on a single case, which limits the generalizability of the findings. Practical implications - The findings suggest that, in order to obtain successful...
Determining an optimal supply chain strategy
Directory of Open Access Journals (Sweden)
Intaher M. Ambe
2012-11-01
Full Text Available In today’s business environment, many companies want to become efficient and flexible, but have struggled, in part, because they have not been able to formulate optimal supply chain strategies. Often this is as a result of insufficient knowledge about the costs involved in maintaining supply chains and the impact of the supply chain on their operations. Hence, these companies find it difficult to manufacture at a competitive cost and respond quickly and reliably to market demand. Mismatched strategies are the root cause of the problems that plague supply chains, and supply-chain strategies based on a one-size-fits-all strategy often fail. The purpose of this article is to suggest instruments to determine an optimal supply chain strategy. This article, which is conceptual in nature, provides a review of current supply chain strategies and suggests a framework for determining an optimal strategy.
Operations Strategy with Paper Boats
Sumukadas, Narendar
2010-01-01
When participants in introductory business courses encounter the term "operations strategy," it is not easy for them to appreciate what operations strategy is about, or how it fits with overall business strategy. This game breaks down highfalutin jargon into experiences that participants can readily relate to. While working in teams to make paper…
Burhan, Muhammad
2017-09-16
Despite highest energy potential, solar energy is only available during diurnal period with varying intensity. Therefore, owing to solar intermittency, solar energy systems need to operate in standalone configuration for steady power supply which requires reliable and sustainable energy storage. Hydrogen production has proved to be the most reliable and sustainable energy storage option for medium and long term operation. However, at the first priority, solar energy must be captured with high efficiency, in order to reduce the overall size of the system and energy storage. Multi-junction solar cells (MJCs) provide highest energy efficiency among all of the photovoltaic technologies and the concentrated photovoltaic (CPV) system concept makes their use cost effective. However, literature is lacking the performance model and optimization strategy for standalone operation of the CPV-hydrogen system. In addition, there is no commercial tool available that can analyze CPV performance, utilizing multi-junction solar cell. This paper proposes the performance model for the CPV-hydrogen systems and the multi-objective optimization strategy for its standalone operation and techno-economic analysis, using micro genetic algorithm (micro-GA). The electrolytic hydrogen production with compression storage and fuel cell, is used as energy storage system. The CPV model is verified for the experimental data of InGaP/InGaAs/Ge triple junction solar cell. An optimal CPV system design is provided for uninterrupted power supply, even under seasonal weather variations. Such approach can be easily integrated with commercial tools and the presented performance data can be used for the design of individual components of the system.
Multiobjective Optimization Based Vessel Collision Avoidance Strategy Optimization
Directory of Open Access Journals (Sweden)
Qingyang Xu
2014-01-01
Full Text Available The vessel collision accidents cause a great loss of lives and property. In order to reduce the human fault and greatly improve the safety of marine traffic, collision avoidance strategy optimization is proposed to achieve this. In the paper, a multiobjective optimization algorithm NSGA-II is adopted to search for the optimal collision avoidance strategy considering the safety as well as economy elements of collision avoidance. Ship domain and Arena are used to evaluate the collision risk in the simulation. Based on the optimization, an optimal rudder angle is recommended to navigator for collision avoidance. In the simulation example, a crossing encounter situation is simulated, and the NSGA-II searches for the optimal collision avoidance operation under the Convention on the International Regulations for Preventing Collisions at Sea (COLREGS. The simulation studies exhibit the validity of the method.
Optimization of power system operation
Zhu, Jizhong
2015-01-01
This book applies the latest applications of new technologies topower system operation and analysis, including new and importantareas that are not covered in the previous edition. Optimization of Power System Operation covers both traditional andmodern technologies, including power flow analysis, steady-statesecurity region analysis, security constrained economic dispatch,multi-area system economic dispatch, unit commitment, optimal powerflow, smart grid operation, optimal load shed, optimalreconfiguration of distribution network, power system uncertaintyanalysis, power system sensitivity analysis, analytic hierarchicalprocess, neural network, fuzzy theory, genetic algorithm,evolutionary programming, and particle swarm optimization, amongothers. New topics such as the wheeling model, multi-areawheeling, the total transfer capability computation in multipleareas, are also addressed. The new edition of this book continues to provide engineers andac demics with a complete picture of the optimization of techn...
Optimizing the operating theatre environment.
Wong, Shing W; Smith, Richard; Crowe, Phil
2010-12-01
The operating theatre is a complex place. There are many potential factors which can interfere with surgery and predispose to errors. Optimizing the operating theatre environment can enhance surgeon performance, which can ultimately improve patient outcomes. These factors include the physical environment (such as noise and light), human factors (such as ergonomics), and surgeon-related factors (such as fatigue and stress). As individual factors, they may not affect surgical outcome but in combination, they may exert a significant influence. The evidence for some of these working environment factors are examined individually. Optimizing the operating environment may have a potentially more significant impact on overall surgical outcome than improving individual surgical skill.
Trends in operations strategy research
Directory of Open Access Journals (Sweden)
Ana Beatriz Lopes de Sousa Jabbour
2009-12-01
Full Text Available This article aims to identify research approaches in operations strategy research, with regards its content. From a systematic literature review we highlight the main definitions of operations strategy and discussions on competitive priorities and then, present the main focuses of the articles published in reputable journals nationally and internationally. It was identified that studies on the operations strategy followed in general the direction of relating the influence and the alignment of competitive priorities for structural and infrastructure decisions. And there are initiatives of studies, which derive from that, to relate the operations strategy in the context of supply chain, which in future may be an important trend. The results of this article bring insights on research trends in a subject with constant interest from researchers in the field of operations management.
Optimal Strategy and Business Models
DEFF Research Database (Denmark)
Johnson, Peter; Foss, Nicolai Juul
2016-01-01
, it is possible to formalize useful notions of a business model, resources, and competitive advantage. The business model that underpins strategy may be seen as a set of constraints on resources that can be interpreted as controls in optimal control theory. Strategy then might be considered to be the control......This study picks up on earlier suggestions that control theory may further the study of strategy. Strategy can be formally interpreted as an idealized path optimizing heterogeneous resource deployment to produce maximum financial gain. Using standard matrix methods to describe the firm Hamiltonian...... variable of firm path, suggesting in turn that the firm's business model is the codification of the application of investment resources used to control the strategic path of value realization....
Energy Technology Data Exchange (ETDEWEB)
Franco, Alessandro; Salza, Pasquale [Dipartimento di Energetica ' ' L. Poggi' ' , Universita di Pisa, Largo Lucio Lazzarino, 2, 56126 PISA (Italy)
2011-02-15
Renewable energy sources (RES) are mainly used in the electrical sector. Electricity is not a storable commodity. Hence it is necessary to produce the requested quantity and distribute it through the system in such a way as to ensure that electricity supply and demand are always evenly balanced. This constraint is actually the main problem related to the penetration of new renewables (wind and photovoltaic power) in the context of complex energy systems. Moreover the design of optimal energy resource mixes in climate change mitigation actions is a challenge faced in many places. The paper analyzes the problem of new renewable energy sources penetration. The case of Italian scenario is considered as a meaningful reference due to the characteristic size and the complexity of the same. The various energy scenarios are evaluated with the aid of a multipurpose software taking into account the interconnections between the different energetic uses. In particular it is shown how the penetration of new renewable energy sources is limited at an upper level by technological considerations and it will be more sustainable if an integration of the various energy uses (thermal, mobility and electrical) will be considered. A series of optimized scenarios are developed. In each case the maximum RES penetration feasible with the constraints was defined. Then analysis is applied to an energy system model of Italy showing how an integrated development of CHP and electric mobility can aid a further integration of wind and photovoltaic energy power. Finally the primary energy consumption saving possible in case of consistent penetration of intermittent renewables and CHP was identified. (author)
Energy Technology Data Exchange (ETDEWEB)
Harold, Michael; Crocker, Mark; Balakotaiah, Vemuri; Luss, Dan; Choi, Jae-Soon; Dearth, Mark; McCabe, Bob; Theis, Joe
2013-09-30
Oxides of nitrogen in the form of nitric oxide (NO) and nitrogen dioxide (NO{sub 2}) commonly referred to as NO{sub x}, is one of the two chemical precursors that lead to ground-level ozone, a ubiquitous air pollutant in urban areas. A major source of NO{sub x} is generated by equipment and vehicles powered by diesel engines, which have a combustion exhaust that contains NO{sub x} in the presence of excess O{sub 2}. Catalytic abatement measures that are effective for gasoline-fueled engines such as the precious metal containing three-way catalytic converter (TWC) cannot be used to treat O2-laden exhaust containing NO{sub x}. Two catalytic technologies that have emerged as effective for NO{sub x} abatement are NO{sub x} storage and reduction (NSR) and selective catalytic reduction (SCR). NSR is similar to TWC but requires much larger quantities of expensive precious metals and sophisticated periodic switching operation, while SCR requires an on-board source of ammonia which serves as the chemical reductant of the NO{sub x}. The fact that NSR produces ammonia as a byproduct while SCR requires ammonia to work has led to interest in combining the two together to avoid the need for the cumbersome ammonia generation system. In this project a comprehensive study was carried out of the fundamental aspects and application feasibility of combined NSR/SCR. The project team, which included university, industry, and national lab researchers, investigated the kinetics and mechanistic features of the underlying chemistry in the lean NOx trap (LNT) wherein NSR was carried out, with particular focus on identifying the operating conditions such as temperature and catalytic properties which lead to the production of ammonia in the LNT. The performance features of SCR on both model and commercial catalysts focused on the synergy between the LNT and SCR converters in terms of utilizing the upstream-generated ammonia and alternative reductants such as propylene, representing the
Optimal strategies for throwing accurately.
Venkadesan, M; Mahadevan, L
2017-04-01
The accuracy of throwing in games and sports is governed by how errors in planning and initial conditions are propagated by the dynamics of the projectile. In the simplest setting, the projectile path is typically described by a deterministic parabolic trajectory which has the potential to amplify noisy launch conditions. By analysing how parabolic trajectories propagate errors, we show how to devise optimal strategies for a throwing task demanding accuracy. Our calculations explain observed speed-accuracy trade-offs, preferred throwing style of overarm versus underarm, and strategies for games such as dart throwing, despite having left out most biological complexities. As our criteria for optimal performance depend on the target location, shape and the level of uncertainty in planning, they also naturally suggest an iterative scheme to learn throwing strategies by trial and error.
Minimax Strategy of Optimal Unambiguous State Discrimination
Institute of Scientific and Technical Information of China (English)
张文海; 余龙宝; 曹卓良; 叶柳
2012-01-01
In this paper, we consider the minimax strategy to unambiguously discriminate two pure nonorthogonal quantum states without knowing a priori probability. By exploiting the positive-operator valued measure, we derive the upper bound of the minimax measurement of the optimal unambiguous state discrimination. Based on the linear optical devices, we propose an experimentally feasible scheme to implement a minimax measure of a general pair of two nonorthogonal quantum states.
Optimal Strategy of Purchase and Sale of Micro Grid Connected Operation%微电网联网的购售电优化策略
Institute of Scientific and Technical Information of China (English)
徐小明; 吴振鹏
2016-01-01
介绍了微电网并网的运营策略，提出了微电网并网运行模式下的经济运行优化模型。模型中考虑了微电网的运行成本、环境成本、停电补偿成本以及与大电网之间的功率交换。通过粒子群算法，以典型日负荷曲线为例，得到了微电网并网运行时的各机组出力、微电网的售电收益、微电网的运行成本、峰值时的停电补偿费用以及和大电网之间的交换功率。仿真结果表明，微电网代理商可以根据自身的情况，灵活调节各机组出力以及通过与大电网之间的功率交换来获取最大的利益。%Introduction was made to the operation strategy of micro grid connected. This paper proposed the optimization model of economic operation in micro grid connected operation mode. The design of the model considered the micro grid operation cost, environmental cost, outage cost compensation and the power exchange with the large power grid. Using the particle swarm algorithm and taking the typical daily load curve for example, this paper obtained the output of each unit, the earnings of micro grid electricity sale, the operation cost of micro grid, the cost of the peak power outage compensation and the power exchange with the large power grid.The simulation results show that the micro grid agents, according to their own situation, can lfexibly adjust each unit output and obtain the maximum beneift through the power exchange with the large power grid.
Particle swarm optimization based optimal bidding strategy in an ...
African Journals Online (AJOL)
user
Particle swarm optimization based optimal bidding strategy in an open ... relaxation-based approach for strategic bidding in England-Wales pool type electricity market has ... presents the mathematical formulation of optimal bidding problem.
Mixed integer evolution strategies for parameter optimization.
Li, Rui; Emmerich, Michael T M; Eggermont, Jeroen; Bäck, Thomas; Schütz, M; Dijkstra, J; Reiber, J H C
2013-01-01
Evolution strategies (ESs) are powerful probabilistic search and optimization algorithms gleaned from biological evolution theory. They have been successfully applied to a wide range of real world applications. The modern ESs are mainly designed for solving continuous parameter optimization problems. Their ability to adapt the parameters of the multivariate normal distribution used for mutation during the optimization run makes them well suited for this domain. In this article we describe and study mixed integer evolution strategies (MIES), which are natural extensions of ES for mixed integer optimization problems. MIES can deal with parameter vectors consisting not only of continuous variables but also with nominal discrete and integer variables. Following the design principles of the canonical evolution strategies, they use specialized mutation operators tailored for the aforementioned mixed parameter classes. For each type of variable, the choice of mutation operators is governed by a natural metric for this variable type, maximal entropy, and symmetry considerations. All distributions used for mutation can be controlled in their shape by means of scaling parameters, allowing self-adaptation to be implemented. After introducing and motivating the conceptual design of the MIES, we study the optimality of the self-adaptation of step sizes and mutation rates on a generalized (weighted) sphere model. Moreover, we prove global convergence of the MIES on a very general class of problems. The remainder of the article is devoted to performance studies on artificial landscapes (barrier functions and mixed integer NK landscapes), and a case study in the optimization of medical image analysis systems. In addition, we show that with proper constraint handling techniques, MIES can also be applied to classical mixed integer nonlinear programming problems.
Optimal intervention strategies for tuberculosis
Bowong, Samuel; Aziz Alaoui, A. M.
2013-06-01
This paper deals with the problem of optimal control of a deterministic model of tuberculosis (abbreviated as TB for tubercle bacillus). We first present and analyze an uncontrolled tuberculosis model which incorporates the essential biological and epidemiological features of the disease. The model is shown to exhibit the phenomenon of backward bifurcation, where a stable disease-free equilibrium co-exists with one or more stable endemic equilibria when the associated basic reproduction number is less than the unity. Based on this continuous model, the tuberculosis control is formulated and solved as an optimal control problem, indicating how control terms on the chemoprophylaxis and detection should be introduced in the population to reduce the number of individuals with active TB. Results provide a framework for designing the cost-effective strategies for TB with two intervention methods.
Hedging Strategies for Bayesian Optimization
Brochu, Eric; de Freitas, Nando
2010-01-01
Bayesian optimization with Gaussian processes has become an increasingly popular tool in the machine learning community. It is efficient and can be used when very little is known about the objective function, making it popular in expensive black-box optimization scenarios. It is able to do this by sampling the objective using an acquisition function which incorporates the model's estimate of the objective and the uncertainty at any given point. However, there are several different parameterized acquisition functions in the literature, and it is often unclear which one to use. Instead of using a single acquisition function, we adopt a portfolio of acquisition functions governed by an online multi-armed bandit strategy. We describe the method, which we call GP-Hedge, and show that this method almost always outperforms the best individual acquisition function.
Following an Optimal Batch Bioreactor Operations Model
DEFF Research Database (Denmark)
Ibarra-Junquera, V.; Jørgensen, Sten Bay; Virgen-Ortíz, J.J.;
2012-01-01
The problem of following an optimal batch operation model for a bioreactor in the presence of uncertainties is studied. The optimal batch bioreactor operation model (OBBOM) refers to the bioreactor trajectory for nominal cultivation to be optimal. A multiple-variable dynamic optimization of fed-b...
Service Operations Optimization: Recent Development in Supply Chain Management
Bin Shen
2015-01-01
Services are the key of success in operation management. Designing the effective strategies by optimization techniques is the fundamental and important condition for performance increase in service operations (SOs) management. In this paper, we mainly focus on investigating SOs optimization in the areas of supply chain management, which create the greatest business values. Specifically, we study the recent development of SOs optimization associated with supply chain by categorizing them into ...
Optimization of BEV Charging Strategy
Ji, Wei
This paper presents different approaches to optimize fast charging and workplace charging strategy of battery electric vehicle (BEV) drivers. For the fast charging analysis, a rule-based model was built to simulate BEV charging behavior. Monte Carlo analysis was performed to explore to the potential range of congestion at fast charging stations which could be more than four hours at the most crowded stations. Genetic algorithm was performed to explore the theoretical minimum waiting time at fast charging stations, and it can decrease the waiting time at the most crowded stations to be shorter than one hour. A deterministic approach was proposed as a feasible suggestion that people should consider to take fast charging when the state of charge is approaching 40 miles. This suggestion is hoped to help to minimize potential congestion at fast charging stations. For the workplace charging analysis, scenario analysis was performed to simulate temporal distribution of charging demand under different workplace charging strategies. It was found that if BEV drivers charge as much as possible and as late as possible at workplace, it could increase the utility of solar-generated electricity while relieve grid stress of extra intensive electricity demand at night caused by charging electric vehicles at home.
Topological Optimization of Artificial Microstructure Strategies
2015-04-02
Topographic Optimization Through Artificial Microstructure Strategies During this project as part of DARPA MCMA we aimed to develop and demonstrate...Topographic Optimization Through Artificial Microstructure Strategies Report Title During this project as part of DARPA MCMA we aimed to develop and...Artificial Microstructure Strategies (Yale and Johns Hopkins) During DARPA MCMA we aimed to develop and demonstrate a 3D microstructural
2002-01-01
A decomposition methodology based on the concept of â thermoeconomic isolationâ applied to the synthesis/design and operational optimization of a stationary cogeneration proton exchange membrane fuel cell (PEMFC) based total energy system (TES) for residential/commercial applications is the focus of this work. A number of different configurations for the fuel cell based TES were considered. The most promising set based on an energy integration analysis of candidate configurations was devel...
Optimal Investment Strategy for Risky Assets
Sergei Maslov; Yi-Cheng Zhang
1998-01-01
We design an optimal strategy for investment in a portfolio of assets subject to a multiplicative Brownian motion. The strategy provides the maximal typical long-term growth rate of investor's capital. We determine the optimal fraction of capital that an investor should keep in risky assets as well as weights of different assets in an optimal portfolio. In this approach both average return and volatility of an asset are relevant indicators determining its optimal weight. Our results are parti...
Resources and Capabilities for Sustainable Operations Strategy
Gavronski, Iuri; Unisinos
2013-01-01
Researchers in OM have made a large effort to incorporate sustainable operations into the mainstream of operations strategy. However, OM scholars and practitioners have no comprehensive framework for sustainable operations strategy to date. This paper attempts to fill this gap by providing a literature review on five dimensions of sustainable operations strategy: external context, competitive dimensions, strategic decisions, operations value chain activities, and organizational learning and k...
Enhanced Ocean Predictability Through Optimal Observing Strategies
2016-06-14
Enhanced Ocean Predictability Through Optimal Observing Strategies A. D. Kirwan, Jr. College of Marine Studies University of Delaware Robinson Hall...observation strategies that will maximize the capacity to predict mesoscale and submesoscale conditions so as to provide the best possible nowcasts and...systems approaches on developing optimal observing strategies . The common thread linking both approaches is Lagrangian data, so this phase of the work
Optimality criteria solution strategies in multiple constraint design optimization
Levy, R.; Parzynski, W.
1981-01-01
Procedures and solution strategies are described to solve the conventional structural optimization problem using the Lagrange multiplier technique. The multipliers, obtained through solution of an auxiliary nonlinear optimization problem, lead to optimality criteria to determine the design variables. It is shown that this procedure is essentially equivalent to an alternative formulation using a dual method Lagrangian function objective. Although mathematical formulations are straight-forward, successful applications and computational efficiency depend upon execution procedure strategies. Strategies examined, with application examples, include selection of active constraints, move limits, line search procedures, and side constraint boundaries.
Linear Tabling Strategies and Optimizations
Zhou, Neng-Fa; Shen, Yi-Dong
2007-01-01
Recently, the iterative approach named linear tabling has received considerable attention because of its simplicity, ease of implementation, and good space efficiency. Linear tabling is a framework from which different methods can be derived based on the strategies used in handling looping subgoals. One decision concerns when answers are consumed and returned. This paper describes two strategies, namely, {\\it lazy} and {\\it eager} strategies, and compares them both qualitatively and quantitatively. The results indicate that, while the lazy strategy has good locality and is well suited for finding all solutions, the eager strategy is comparable in speed with the lazy strategy and is well suited for programs with cuts. Linear tabling relies on depth-first iterative deepening rather than suspension to compute fixpoints. Each cluster of inter-dependent subgoals as represented by a top-most looping subgoal is iteratively evaluated until no subgoal in it can produce any new answers. Naive re-evaluation of all loopi...
Institute of Scientific and Technical Information of China (English)
王如强; 李初福; 何小荣; 陈丙珍
2008-01-01
Production planning models generated by common modeling systems do not involve constraints for process operations, and a solution optimized by these models is called a quasi-optimal plan. The quasi-optimal plan cannot be executed in practice some time for no corresponding operating conditions. In order to determine a practically feasible optimal plan and corresponding operating conditions of fluidized catalytic cracking unit (FCCU), a novel close-loop integrated strategy, including determination of a quasi-optimal plan, search of operating conditions of FCCU and revision of the production planning model, was proposed in this article. In the strategy, a generalized genetic algorithm (GA) coupled with a sequential process simulator of FCCU was applied to search operating conditions implementing the quasi-optimal plan of FCCU and output the optimal individual in the GA search as a final genetic individual. When no corresponding operating conditions were found, the final genetic individual based correction (FGIC) method was presented to revise the production planning model, and then a new quasi-optimal production plan was determined. The above steps were repeated until a practically feasible optimal plan and corresponding operating conditions of FCCU were obtained. The close-loop integrated strategy was validated by two cases, and it was indicated that the strategy was efficient in determining a practically executed optimal plan and corresponding operating conditions of FCCU.
Optimization of Sensor Monitoring Strategies for Emissions
Klise, K. A.; Laird, C. D.; Downey, N.; Baker Hebert, L.; Blewitt, D.; Smith, G. R.
2016-12-01
Continuous or regularly scheduled monitoring has the potential to quickly identify changes in air quality. However, even with low-cost sensors, only a limited number of sensors can be placed to monitor airborne pollutants. The physical placement of these sensors and the sensor technology used can have a large impact on the performance of a monitoring strategy. Furthermore, sensors can be placed for different objectives, including maximum coverage, minimum time to detection or exposure, or to quantify emissions. Different objectives may require different monitoring strategies, which need to be evaluated by stakeholders before sensors are placed in the field. In this presentation, we outline methods to enhance ambient detection programs through optimal design of the monitoring strategy. These methods integrate atmospheric transport models with sensor characteristics, including fixed and mobile sensors, sensor cost and failure rate. The methods use site specific pre-computed scenarios which capture differences in meteorology, terrain, concentration averaging times, gas concentration, and emission characteristics. The pre-computed scenarios become input to a mixed-integer, stochastic programming problem that solves for sensor locations and types that maximize the effectiveness of the detection program. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.
Optimal operation of batch membrane processes
Paulen, Radoslav
2016-01-01
This study concentrates on a general optimization of a particular class of membrane separation processes: those involving batch diafiltration. Existing practices are explained and operational improvements based on optimal control theory are suggested. The first part of the book introduces the theory of membrane processes, optimal control and dynamic optimization. Separation problems are defined and mathematical models of batch membrane processes derived. The control theory focuses on problems of dynamic optimization from a chemical-engineering point of view. Analytical and numerical methods that can be exploited to treat problems of optimal control for membrane processes are described. The second part of the text builds on this theoretical basis to establish solutions for membrane models of increasing complexity. Each chapter starts with a derivation of optimal operation and continues with case studies exemplifying various aspects of the control problems under consideration. The authors work their way from th...
Immune clonal selection optimization method with combining mutation strategies
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
In artificial immune optimization algorithm, the mutation of immune cells has been considered as the key operator that determines the algorithm performance. Traditional immune optimization algorithms have used a single mutation operator, typically a Gaussian. Using a variety of mutation operators that can be combined during evolution to generate different probability density function could hold the potential for producing better solutions with less computational effort. In view of this, a linear combination mutation operator of Gaussian and Cauchy mutation is presented in this paper, and a novel clonal selection optimization method based on clonal selection principle is proposed also. The simulation results show the combining mutation strategy can obtain the same performance as the best of pure strategies or even better in some cases.
Optimal strategies for flood prevention
Eijgenraam, Carel; Brekelmans, Ruud; den Hertog, Dick; Roos, C.
2016-01-01
Flood prevention policy is of major importance to the Netherlands since a large part of the country is below sea level and high water levels in rivers may also cause floods. In this paper we propose a dike height optimization model to determine economically efficient flood protection standards. We i
Optimization and assistance operations; Optimisation et operations de secours
Energy Technology Data Exchange (ETDEWEB)
Giordan, D. [Centre de Secours Principal de Rambouillet, 78 (France)
1998-07-01
The purpose of this article is to answer this question: what does optimization mean in the frame of an assistance operation. Two points have been developed: the first one is devoted to a broad training and sensitizing for the persons susceptible to participate to these interventions, the second one is the preparation of operations: it is possible to develop optimization from information feedback. (N.C.)
Operator assisted optimization of sludge dewatering
DEFF Research Database (Denmark)
Grüttner, Henrik
1991-01-01
On a municipal wastewater treatment plant using a decanter-centrifuge for dewatering of anaerobic digested sludge an operator assisting system for sludge dewatering was developed. The system is based on a database used to collect data on sludge properties and operational conditions which is added...... by the operator. By graphical presentation and an advisory service these data are used to support the operator in his dewatering operations and to secure a running optimization of the sludge dewatering. Evaluations show that this system is a useful tool for data collection and presentation and that the data...... collected seem to reflect the actual situation at the plant. In the future such systems are expected to be used as tools for education of operators, transfer of knowledge from one operator to another and for a continuous optimization of dewatering operations. (A)...
Cultural Change and the Operational Energy Strategy
2012-02-01
CULTURAL CHANGE AND THE OPERATIONAL ENERGY STRATEGY by Colonel Steven L. Allen United States Army Dr. Richard Meinhart ...Cultural Change and the Operational Energy Strategy by Colonel Steven L. Allen United States Army United States... Army War College Class of 2012 DISTRIBUTION STATEMENT: A Approved for Public Release Distribution is Unlimited This manuscript is submitted
微网联合优化配置及运行控制策略研究%Microgrid Jointly Optimal Configuration and Operation Control Strategy
Institute of Scientific and Technical Information of China (English)
胡蕊; 王婧; 吴晓军
2015-01-01
针对陈家镇微电网现有结构能量利用率低下的问题，分析了陈家镇微网电气接线图现状并收集运行数据，确定了影响微网能源转化效率的关键指标。结合微网气象条件、节假日负荷特性及对大电网削峰平谷的作用，研究得到了微网有功控制策略。该方案可以最大程度地提高新能源发电系统的利用率，提高对负荷的供电可靠性，实现运行效益最高的目标。%In view of the low energy utilization of the existing microgrid structure in Chenjia Town ,this paper analy‐zes the current electrical wiring diagram of the microgrid and collects the operation data ,determines the the key indi‐cators influencing microgrid energy conversion efficiency .Combined with microgrid meteorological conditions ,holiday load characteristics and large grid peak clipping function ,the active control strategy for the microgrid is formulated . This scheme can improve the utilization of new energy power generation system to the greatest extent ,increase the power supply reliability to the load ,and achieve the highest goal of operation efficiency .
Turbine Control Strategies for Wind Farm Power Optimization
DEFF Research Database (Denmark)
Mirzaei, Mahmood; Göçmen Bozkurt, Tuhfe; Giebel, Gregor
2015-01-01
In recent decades there has been increasing interest in green energies, of which wind energy is the most important one. In order to improve the competitiveness of the wind power plants, there are ongoing researches to decrease cost per energy unit and increase the efficiency of wind turbines...... and wind farms. One way of achieving these goals is to optimize the power generated by a wind farm. One optimization method is to choose appropriate operating points for the individual wind turbines in the farm. We have made three models of a wind farm based on three difference control strategies....... Basically, the control strategies determine the steady state operating points of the wind turbines. Except the control strategies of the individual wind turbines, the wind farm models are similar. Each model consists of a row of 5MW reference wind turbines. In the models we are able to optimize...
Institute of Scientific and Technical Information of China (English)
袁尧; 刘超
2013-01-01
针对泵站优化运行计算时最优解评价指标单一的问题,建立了包含机组开停机约束的泵站优化运行数学模型和运行方案选优的投影寻踪决策模型.提出了求解泵站多机组优化运行模型的蚁群算法,并通过分析模型的特性改进了算法中启发式信息和信息素更新方式.对江都四站多机组日优化运行计算的结果显示,变量同等离散的情况下,利用蚁群算法优化的结果比用动态规划逐次逼近法优化的结果节省了2.8％的电费,前者相比设计工况运行时节省了29.2％的电费,且蚁群算法优化结果对应的运行方案中叶片调节次数少,机组运行时间短；方案选优时投影寻踪决策模型能够兼顾多个评价指标的优选,得到的运行方案不仅运行成本低,且更合理,更贴切于日常运行,可见改进后的蚁群算法结合投影寻踪决策模型在泵站优化运行及相近的领域有较大的实用价值.%Usually the evaluation index of optimal pump operation solution is single. An optimal pump operation model which contained the constraint of start-stop pump unit was developed, and projection pursuit evaluation method for scheme optimization was proposed. The ant colony optimization algorithm was used to calculate the model. The heuristic information and the pheromone trail update method were improved by analyzing characters of the model for better performances. A calculation example for the No. 4 Jiangdu pumping station was conducted. The results from ant colony optimization algorithm showed that 29. 2% of energy fee could be saved under the designed operation condition, which was compared with the result from dynamic programming with successive approximation algorithm under the same discrete condition, and was better with 2. 8% of the result from dynamic programming. The results from ant colony optimization algorithm had less times of the blade adjusting, and shorter operating time of the pumps
Efficient Computation of Optimal Trading Strategies
Boyarshinov, Victor
2010-01-01
Given the return series for a set of instruments, a \\emph{trading strategy} is a switching function that transfers wealth from one instrument to another at specified times. We present efficient algorithms for constructing (ex-post) trading strategies that are optimal with respect to the total return, the Sterling ratio and the Sharpe ratio. Such ex-post optimal strategies are useful analysis tools. They can be used to analyze the "profitability of a market" in terms of optimal trading; to develop benchmarks against which real trading can be compared; and, within an inductive framework, the optimal trades can be used to to teach learning systems (predictors) which are then used to identify future trading opportunities.
Service Operations Optimization: Recent Development in Supply Chain Management
Directory of Open Access Journals (Sweden)
Bin Shen
2015-01-01
Full Text Available Services are the key of success in operation management. Designing the effective strategies by optimization techniques is the fundamental and important condition for performance increase in service operations (SOs management. In this paper, we mainly focus on investigating SOs optimization in the areas of supply chain management, which create the greatest business values. Specifically, we study the recent development of SOs optimization associated with supply chain by categorizing them into four different industries (i.e., e-commerce industry, consumer service industry, public sector, and fashion industry and four various SOs features (i.e., advertising, channel coordination, pricing, and inventory. Moreover, we conduct the technical review on the stylish industries/topics and typical optimization models. The classical optimization approaches for SOs management in supply chain are presented. The managerial implications of SOs in supply chain are discussed.
Optimal control of anthracnose using mixed strategies.
Fotsa Mbogne, David Jaures; Thron, Christopher
2015-11-01
In this paper we propose and study a spatial diffusion model for the control of anthracnose disease in a bounded domain. The model is a generalization of the one previously developed in [15]. We use the model to simulate two different types of control strategies against anthracnose disease. Strategies that employ chemical fungicides are modeled using a continuous control function; while strategies that rely on cultivational practices (such as pruning and removal of mummified fruits) are modeled with a control function which is discrete in time (though not in space). For comparative purposes, we perform our analyses for a spatially-averaged model as well as the space-dependent diffusion model. Under weak smoothness conditions on parameters we demonstrate the well-posedness of both models by verifying existence and uniqueness of the solution for the growth inhibition rate for given initial conditions. We also show that the set [0, 1] is positively invariant. We first study control by impulsive strategies, then analyze the simultaneous use of mixed continuous and pulse strategies. In each case we specify a cost functional to be minimized, and we demonstrate the existence of optimal control strategies. In the case of pulse-only strategies, we provide explicit algorithms for finding the optimal control strategies for both the spatially-averaged model and the space-dependent model. We verify the algorithms for both models via simulation, and discuss properties of the optimal solutions. Copyright © 2015 Elsevier Inc. All rights reserved.
Optimal operation of hybrid-SITs under a SBO accident
Energy Technology Data Exchange (ETDEWEB)
Jeon, In Seop, E-mail: inseopjeon@kaist.ac.kr [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701 (Korea, Republic of); Heo, Sun, E-mail: sunnysunny@khnp.co.kr [Central Research Institute, Korea Hydro & Nuclear Power Co., 70 Yuseong-daero 1312 beon-gil, Yuseong-gu, Daejeon 305-343 (Korea, Republic of); Kang, Hyun Gook, E-mail: hyungook@kaist.ac.kr [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701 (Korea, Republic of)
2016-02-15
Highlights: • Operation strategy of hybrid-SIT (H-SIT) in station blackout (SBO) is developed. • There are five main factors which have to be carefully treated in the development of the operation strategy. • Optimal value of each main factor is investigated analytically and then through thermal-hydraulic analysis using computer code. • The optimum operation strategy is suggested based on the optimal value of the main factors. - Abstract: A hybrid safety injection tank (H-SIT) is designed to enhance the capability of pressurized water reactors against high-pressure accidents which might be caused by the combined accidents accompanied by station blackout (SBO), and is suggested as a useful alternative to electricity-driven motor injection pumps. The main purpose of the H-SIT is to provide coolant to the core so that core safety can be maintained for a longer period. As H-SITs have a limited inventory, their efficient use in cooling down the core is paramount to maximize the available time for long-term cooling component restoration. Therefore, an optimum operation strategy must be developed to support the operators for the most efficient H-SIT use. In this study, the main factors which have to be carefully treated in the development of an operation strategy are first identified. Then the optimal value of each main factor is investigated analytically, a process useful to get the basis of the global optimum points. Based on these analytical optimum points, a thermal-hydraulic analysis using MARS code is performed to get more accurate values and to verify the results of the analytical study. The available time for long-term cooling component restoration is also estimated. Finally, an integrated optimum operation strategy for H-SITs in SBO is suggested.
Operation Strategy of EV Battery Charging and Swapping Station
Institute of Scientific and Technical Information of China (English)
Zhuo Peng; Li Zhang; Ku-An Lu; Jun-Peng Hu; Si Liu
2014-01-01
An operation strategy of the electric vehicle (EV) battery charging and swapping station is proposed in the paper. The strategy is established based on comprehensively consideration of the EV charging behaviors and the possible mutual actions between battery charging and swapping. Three energy management strategies can be used in the station:charging period shifting, energy exchange between EVs, and energy supporting from surplus swapping batteries. Then an optimization model which minimizes the total energy management costs of the station is built. The Monte Carlo simulation is applied to analyze the characteristics of the EV battery charging load, and a heuristic algorithm is used to solve the strategy providing the relevant information of EVs and the battery charging and swapping station. The operation strategy can efficiently reduce battery charging during the high electricity price periods and make more reasonable use of the resources. Simulations prove the feasibility and rationality of the strategy.
Integrated Bidding and Operating Strategies for Wind-Storage Systems
DEFF Research Database (Denmark)
Ding, Huajie; Pinson, Pierre; Hu, Zechun
2016-01-01
to perform arbitrage and to alleviate wind power deviations from day-ahead contracts. The strategy is developed with two-price balancing markets in mind. A mixed integer nonlinear optimization formulation is built to determine optimal offers by taking into account expected wind power forecasting errors......Due to their flexible charging and discharging capabilities, energy storage systems (ESS) are considered a promising complement to wind farms (WFs) participating in electricity markets. This paper presents integrated day-ahead bidding and real-time operation strategies for a wind-storage system...... and the power balancing capability of the ESS. A modified gradient descent algorithm is designed to solve this nonlinear problem. A number of case studies validate the computational efficiency and optimality of the algorithm. Compared to the existing strategies, the proposed strategies yield increased economic...
Optimal strategies for throwing accurately
Venkadesan, Madhusudhan
2010-01-01
Accuracy of throwing in games and sports is governed by how errors at projectile release are propagated by flight dynamics. To address the question of what governs the choice of throwing strategy, we use a simple model of throwing with an arm modelled as a hinged bar of fixed length that can release a projectile at any angle and angular velocity. We show that the amplification of deviations in launch parameters from a one parameter family of solution curves is quantified by the largest singular value of an appropriate Jacobian. This allows us to predict a preferred throwing style in terms of this singular value, which itself depends on target location and the target shape. Our analysis also allows us to characterize the trade-off between speed and accuracy despite not including any effects of signal-dependent noise. Using nonlinear calculations for propagating finite input-noise, we find that an underarm throw to a target leads to an undershoot, but an overarm throw does not. Finally, we consider the limit of...
Operative strategy of acetabular fractures
Institute of Scientific and Technical Information of China (English)
WANG Yan; TANG Pei-fu; HUANG Peng
2006-01-01
Anatomic structure of acetabular fractures are complex and operative exposure and fixation are extremely difficult.For those obviously displaced acetabular fractures, close reduction is doomed to cause deformative healing. Open reduction with internal fixation (ORIF) not only results in anatomic reduction, but also brings complications. No matter which method will be adopted, traumatic arthritis or avascular necrosis of femoral head might occur. In order to treat acetabular fractures more effectively, orthopedic surgeons should be required to fully master the acetabular anatomy, biomechanics, classification and the necessary knowledge for complication prevention.
Optimal Inspection and Maintenance Strategies for Structural Systems
DEFF Research Database (Denmark)
Sommer, A. M.
The aim of this thesis is to give an overview of conventional and optimal reliability-based inspection and maintenance strategies and to examine for specific structures how the cost can be reduced and/or the safety can be improved by using optimal reliability-based inspection strategies. For stru......The aim of this thesis is to give an overview of conventional and optimal reliability-based inspection and maintenance strategies and to examine for specific structures how the cost can be reduced and/or the safety can be improved by using optimal reliability-based inspection strategies....... Furthermore, in relation to the calculations performed the intention is to modify an existing program for determination of optimal inspection strategies. The main purpose of inspection and maintenance of structural systems is to prevent or delay damage or deterioration to protect people, environment......, and investments made in the structure. The inspection and maintenance should be performed so that the structural system is operating as much of the time as possible and the cost is kept at a minimum and so that the safety of the structure is satisfactory. Up till now inspection strategies have been based...
Optimal experimental design strategies for detecting hormesis.
Dette, Holger; Pepelyshev, Andrey; Wong, Weng Kee
2011-12-01
Hormesis is a widely observed phenomenon in many branches of life sciences, ranging from toxicology studies to agronomy, with obvious public health and risk assessment implications. We address optimal experimental design strategies for determining the presence of hormesis in a controlled environment using the recently proposed Hunt-Bowman model. We propose alternative models that have an implicit hormetic threshold, discuss their advantages over current models, and construct and study properties of optimal designs for (i) estimating model parameters, (ii) estimating the threshold dose, and (iii) testing for the presence of hormesis. We also determine maximin optimal designs that maximize the minimum of the design efficiencies when we have multiple design criteria or there is model uncertainty where we have a few plausible models of interest. We apply these optimal design strategies to a teratology study and show that the proposed designs outperform the implemented design by a wide margin for many situations.
Optimal Deterministic Investment Strategies for Insurers
Directory of Open Access Journals (Sweden)
Ulrich Rieder
2013-11-01
Full Text Available We consider an insurance company whose risk reserve is given by a Brownian motion with drift and which is able to invest the money into a Black–Scholes financial market. As optimization criteria, we treat mean-variance problems, problems with other risk measures, exponential utility and the probability of ruin. Following recent research, we assume that investment strategies have to be deterministic. This leads to deterministic control problems, which are quite easy to solve. Moreover, it turns out that there are some interesting links between the optimal investment strategies of these problems. Finally, we also show that this approach works in the Lévy process framework.
Rearrangement invariant optimal range for Hardy type operators
Soria, Javier; Tradacete, Pedro
2013-01-01
We characterize, in the context of rearrangement invariant spaces, the optimal range space for a class of monotone operators related to the Hardy operator. The connection between optimal range and optimal domain for these operators is carefully analyzed.
Improved Large-Scale Process Cooling Operation through Energy Optimization
Directory of Open Access Journals (Sweden)
Kriti Kapoor
2013-11-01
Full Text Available This paper presents a study based on real plant data collected from chiller plants at the University of Texas at Austin. It highlights the advantages of operating the cooling processes based on an optimal strategy. A multi-component model is developed for the entire cooling process network. The model is used to formulate and solve a multi-period optimal chiller loading problem, posed as a mixed-integer nonlinear programming (MINLP problem. The results showed that an average energy savings of 8.57% could be achieved using optimal chiller loading as compared to the historical energy consumption data from the plant. The scope of the optimization problem was expanded by including a chilled water thermal storage in the cooling system. The effect of optimal thermal energy storage operation on the net electric power consumption by the cooling system was studied. The results include a hypothetical scenario where the campus purchases electricity at wholesale market prices and an optimal hour-by-hour operating strategy is computed to use the thermal energy storage tank.
Alien: How Operational Art Devoured Strategy
2009-09-01
time holding his own.”10 He thus describes strategy as the “art of making war on the map [which] comprehends the whole theatre of operations,”11...and comprehensive change, usually for the worse, rested on a Weltanschauung heavily influenced by romanticism , with a consequent lack of desire to...are planned, conducted and sustained within a theatre or area of operations.” 91. A. F. Lykke, “Toward an Understanding of Military Strategy
Optimization strategies for complex engineering applications
Energy Technology Data Exchange (ETDEWEB)
Eldred, M.S.
1998-02-01
LDRD research activities have focused on increasing the robustness and efficiency of optimization studies for computationally complex engineering problems. Engineering applications can be characterized by extreme computational expense, lack of gradient information, discrete parameters, non-converging simulations, and nonsmooth, multimodal, and discontinuous response variations. Guided by these challenges, the LDRD research activities have developed application-specific techniques, fundamental optimization algorithms, multilevel hybrid and sequential approximate optimization strategies, parallel processing approaches, and automatic differentiation and adjoint augmentation methods. This report surveys these activities and summarizes the key findings and recommendations.
A Strategy of Minimising Wind Power Curtailment by Considering Operation Capacity Credit
DEFF Research Database (Denmark)
Liu, Zhou; Su, Chi; Fang, Jiakun
2015-01-01
An optimal wind power curtailment strategy considering operation capacity credit is proposed in this paper to minimize the uncertain wind power curtailment and minimize the system operation cost. The relevant definitions in capacity credit assessment are applied in the power system operation...... situation. Based on operation capacity credit prediction, the optimal operation control strategy is defined and implemented for hourly system operation and control. Multi-agent system based control structure is adopted to coordinate the diverse system components to work together and realize the system wide...... targets of the proposed strategy. The simulation results demonstrate the effectiveness of the proposed strategy....
OPTIMAL OPERATIONAL CONTROL OF INTERCEPTOR SEWER SYSTEM
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
In this paper, a mathematical model was built up to solve the problem of optimal operational control by analysing the factors on an interceptor sewer system and a Fortran program was produced for this model. This paper shows that the optimal control states can be determined by working out the optimal flow rates by means of Linear Programming (LP). The result is very sensitive to interception points and the concentration weight coefficients over time. The result further highlights some practical applications for the existing sewer systems or the sewer systems under design.
Optimal operation of Petlyuk distillation: Steady-state behavior
Directory of Open Access Journals (Sweden)
Ivar J. Halvorsen
2001-07-01
Full Text Available The "Petlyuk" or "dividing-wall" or "fully thermally coupled" distillation column is an interesting alternative to the conventional cascaded binary columns for separation of multi-component mixtures. However, the industrial use has been limited, and difficulties in operation have been reported as one reason. With three product compositions controlled, the system has two degrees of freedom left for on-line optimization. We show that the steady-state optimal solution surface is quite narrow, and depends strongly on disturbances and design parameters. Thus it seems difficult to achieve the potential energy savings compared to conventional approaches without a good control strategy. We discuss candidate variables which may be used as feedback variables in order to keep the column operation close to optimal in a "self-optimizing" control scheme.
Optimization of Operations Resources via Discrete Event Simulation Modeling
Joshi, B.; Morris, D.; White, N.; Unal, R.
1996-01-01
The resource levels required for operation and support of reusable launch vehicles are typically defined through discrete event simulation modeling. Minimizing these resources constitutes an optimization problem involving discrete variables and simulation. Conventional approaches to solve such optimization problems involving integer valued decision variables are the pattern search and statistical methods. However, in a simulation environment that is characterized by search spaces of unknown topology and stochastic measures, these optimization approaches often prove inadequate. In this paper, we have explored the applicability of genetic algorithms to the simulation domain. Genetic algorithms provide a robust search strategy that does not require continuity and differentiability of the problem domain. The genetic algorithm successfully minimized the operation and support activities for a space vehicle, through a discrete event simulation model. The practical issues associated with simulation optimization, such as stochastic variables and constraints, were also taken into consideration.
Institute of Scientific and Technical Information of China (English)
张峰; 张熙; 张利; 苗骁健; 杨立滨; 梁军
2016-01-01
Due to the spatial scale effect, battery energy storage station (BESS) in adjacent wind farms has advantages in capacity and investment compared with the distributed energy storage systems. Besides, BESS has centralized supervisory control, which bears higher controllability when participating in dispatching and control. Therefore, this paper analyzes the operation pattern and working mode of BESS. It is shown that the current BESS scale can participate in the fluctuation smoothing and peak shaving in power grid. After that, the cost optimization mathematical model is set up based on charging and discharging strategy, to minimize the sum of operating cost. So the optimal BESS capacity can be determined. According to the seasonal differences of wind power outputs, the BESS operating strategy for fluctuation smoothing and peak shaving has been discussed. Taken the maximal benefit of real time operation as the target, the optimal operating model has been built. Thus BESS can adjust the operating mode in accordance with the wind power output differences. The actual wind power data show that this method can optimize the capacity and operating strategy of BESS, and has high feasibility.%风电场群的空间规模效应使其自身具备波动平滑调节能力，由此使得区域风电场群中配置电池储能电站（BESS）具备理论可行性。基于此，分析了区域风电场群配置BESS的运行形态和工作模式，指出当前规模的 BESS 可参与功率波动平抑和适度的电网调峰。基于构建 BESS充放电策略，提出了以运营成本最小为目标的成本优化模型，由此确定风电场群最佳 BESS 容量配比。同时，利用风功率出力波动的季节性规律差异，探讨 BESS 在低风电出力季节参与电网调峰的可行性，提出了以实时运行效益最大为目标的 BESS 运行策略，使其在该目标下根据风电出力季节性差异调整运行模式。利用风电场实际运行数据验证
Optimizing Infant Development: Strategies for Day Care.
Chambliss, Catherine
This guide for infant day care providers examines the importance of early experience for brain development and strategies for providing optimal infant care. The introduction discusses the current devaluation of day care and idealization of maternal care and identifies benefits of quality day care experience for intellectual development, sleep…
Optimal Heating Strategies for a Convection Oven
Stigter, J.D.; Scheerlinck, N.; Nicolai, B.M.; Impe, van J.F.
2001-01-01
In this study classical control theory is applied to a heat conduction model with convective boundary conditions. Optimal heating strategies are obtained through solution of an associated algebraic Riccati equation for a finite horizon linear quadratic regulator (LQR). The large dimensional system
Instance Optimality of the Adaptive Maximum Strategy
L. Diening; C. Kreuzer; R. Stevenson
2016-01-01
In this paper, we prove that the standard adaptive finite element method with a (modified) maximum marking strategy is instance optimal for the total error, being the square root of the squared energy error plus the squared oscillation. This result will be derived in the model setting of Poisson’s e
Space Operations Center orbit altitude selection strategy
Indrikis, J.; Myers, H. L.
1982-01-01
The strategy for the operational altitude selection has to respond to the Space Operation Center's (SOC) maintenance requirements and the logistics demands of the missions to be supported by the SOC. Three orbit strategies are developed: two are constant altitude, and one variable altitude. In order to minimize the effect of atmospheric uncertainty the dynamic altitude method is recommended. In this approach the SOC will operate at the optimum altitude for the prevailing atmospheric conditions and logistics model, provided that mission safety constraints are not violated. Over a typical solar activity cycle this method produces significant savings in the overall logistics cost.
Optimal inspection Strategies for Offshore Structural Systems
DEFF Research Database (Denmark)
Faber, M. H.; Sørensen, John Dalsgaard; Kroon, I. B.
1992-01-01
Optimal planning of inspection and maintenance strategies for structures has become a subject of increasing interest especially for offshore structures for which large costs are associated with structural failure, inspections and repairs. During the last five years a methodology has been formulated...... a mathematical framework for the estimation of the failure and repair costs a.ssociated with systems failure. Further a strategy for selecting the components to inspect based on decision tree analysis is suggested. Methods and analysis schemes are illustrated by a simple example....... to perform optimal inspection and repair strategies for structural components subject to uncertain loading conditions and material behavior. In this paper this methodology is extended to inelude also system failure i.e. failure of a given sub set of all the structural components. This extension ineludes...
Optimization of the bank's operating portfolio
Borodachev, S. M.; Medvedev, M. A.
2016-06-01
The theory of efficient portfolios developed by Markowitz is used to optimize the structure of the types of financial operations of a bank (bank portfolio) in order to increase the profit and reduce the risk. The focus of this paper is to check the stability of the model to errors in the original data.
Yingst, R. A.; Russell, P.; ten Kate, I. L.; Noble, S.; Graff, T.; Graham, L. D.; Eppler, D.
2015-08-01
The Moon Mars Analog Mission Activities Mauna Kea 2012 (MMAMA 2012) field campaign aimed to assess how effectively an integrated science and engineering rover team operating on a 24-h planning cycle facilitates high-fidelity science products. The science driver of this field campaign was to determine the origin of a glacially-derived deposit: was the deposit the result of (1) glacial outwash from meltwater; or (2) the result of an ice dam breach at the head of the valley? Lessons learned from MMAMA 2012 science operations include: (1) current rover science operations scenarios tested in this environment provide adequate data to yield accurate derivative products such as geologic maps; (2) instrumentation should be selected based on both engineering and science goals; and chosen during, rather than after, mission definition; and (3) paralleling the tactical and strategic science processes provides significant efficiencies that impact science return. The MER-model concept of operations utilized, in which rover operators were sufficiently facile with science intent to alter traverse and sampling plans during plan execution, increased science efficiency, gave the Science Backroom time to develop mature hypotheses and science rationales, and partially alleviated the problem of data flow being greater than the processing speed of the scientists.
Yingst, R. A.; Russell, P.; Ten Kate, I. L.|info:eu-repo/dai/nl/292012217; Noble, S.; Graff, T.; Graham, L. D.; Eppler, D.
2015-01-01
The Moon Mars Analog Mission Activities Mauna Kea 2012 (MMAMA 2012) field campaign aimed to assess how effectively an integrated science and engineering rover team operating on a 24-h planning cycle facilitates high-fidelity science products. The science driver of this field campaign was to determin
Yingst, R. A.; Russell, P.; Ten Kate, I. L.; Noble, S.; Graff, T.; Graham, L. D.; Eppler, D.
2015-01-01
The Moon Mars Analog Mission Activities Mauna Kea 2012 (MMAMA 2012) field campaign aimed to assess how effectively an integrated science and engineering rover team operating on a 24-h planning cycle facilitates high-fidelity science products. The science driver of this field campaign was to determin
Institute of Scientific and Technical Information of China (English)
章美丹; 宋晓喆; 辛焕海; 甘德强; 谢俊; 陈琳
2013-01-01
Generally the peak load shifting is regarded as the optimization objective for the operation of battery energy storage system (BESS) connected to distribution network, on this basis the network loss reduction is also taken into account in this paper. Based on the radial structure of distribution network a simplified network loss computing method is designed so as to establish an optimal operation model of BESS. Utilizing the operational features of BESS, the established model is solved by bi-level optimization. In the outer layer the genetic algorithm (GA) is utilized to optimize the charging/discharging states of BESS, while in the inner layer the quadratic programming (QP) is employed to measure individual fitness of GA used in outer layer, thus the optimal charging and discharging states under specified conditions can be obtained. During the case study, the influences of network-connected position of BESS and its operational scheme under load curve with different characteristics on network loss are analyzed, and the optimization results under different charging/discharging times within the research period are compared. The simulation results show that the proposed method is also applicable to make medium/long term optimal operation strategy of BESS.% 通常接入配电网的电池储能站的运行以削峰填谷为优化目标，在此基础上，增加了减少网损这个因素。为此，基于配电网辐射型结构的特点，设计了简化的网损计算方法，建立相应的电池储能站优化运行模型。利用电池储能站的运行特点，采用双层优化方法进行求解：外层利用遗传算法对电池储能站的充放电状态进行优化，内层利用二次规划法计算外层遗传算法中个体的适应度，从而分别得到给定条件下最优的充放电状态及充放电功率。通过算例分析了电池储能站的接入位置和运行方案在不同特性负荷曲线下对网损的影响，并比较了研究
Institute of Scientific and Technical Information of China (English)
石慧; 王玉华; 曾建潮
2012-01-01
在MRO系统中,随着对精益维修要求的日益提高,提出一种计算设备维护维修的最小平均费用率的模型.此模型是利用接收到的监控信息确定设备退化模型,设定退化模型动态预防性维修阈值,根据维修成本最小的原则动态选择最佳的预防性维护阈值和最佳的预防性维护时间.并计算各种不同参数下符合伽玛分布的退化模型的最小平均费用率,结论证明该模型的正确性和有效性.%In the MRO system, as the requirements of the lean maintenance is improved increasingly, a model of calculating the optimal preventive maintenance average cost rate is put forward. This model is used to determine the deterioration model using received monitoring equipment information, set the deterioration model preventive maintenance threshold value as time function, dynamically choose the best preventive maintenance threshold value and time according to the principle of minimal maintenance cost cycle. The least average cost rate of various parameters with gamma distribution under the deterioration model of optimal maintenance cycle is calculated. The conclusion shows that this model is correct and effective.
The Optimal Nash Equilibrium Strategies Under Competition
Institute of Scientific and Technical Information of China (English)
孟力; 王崇喜; 汪定伟; 张爱玲
2004-01-01
This paper presented a game theoretic model to study the competition for a single investment oppertunity under uncertainty. It models the hazard rate of investment as a function of competitors' trigger level. Under uncertainty and different information structure, the option and game theory was applied to researching the optimal Nash equilibrium strategies of one or more firm. By means of Matlab software, the paper simulates a real estate developing project example and illustrates how parameter affects investment strategies. The paper's work will contribute to the present investment practice in China.
Buffer management optimization strategy for satellite ATM
Institute of Scientific and Technical Information of China (English)
Lu Rong; Cao Zhigang
2006-01-01
ECTD (erroneous cell tail drop), a buffer management optimization strategy is suggested which can improve the utilization of buffer resources in satellite ATM (asynchronous transfer mode) networks. The strategy, in which erroneous cells caused by satellite channel and the following cells that belong to the same PDU (protocol data Unit) are discarded, concerns non-real-time data services that use higher layer protocol for retransmission. Based on EPD (early packet drop) policy, mathematical models are established with and without ECTD. The numerical results show that ECTD would optimize buffer management and improve effective throughput (goodput), and the increment of goodput is relative to the CER (cell error ratio) and the PDU length. The higher their values are, the greater the increment. For example,when the average PDU length values are 30 and 90, the improvement of goodput are respectively about 4% and 10%.
Optimal Investment Strategy to Minimize Occupation Time
Bayraktar, Erhan
2008-01-01
We find the optimal investment strategy to minimize the expected time that an individual's wealth stays below zero, the so-called {\\it occupation time}. The individual consumes at a constant rate and invests in a Black-Scholes financial market consisting of one riskless and one risky asset, with the risky asset's price process following a geometric Brownian motion. We also consider an extension of this problem by penalizing the occupation time for the degree to which wealth is negative.
Optimal experimental design strategies for detecting hormesis
2010-01-01
Hormesis is a widely observed phenomenon in many branches of life sciences ranging from toxicology studies to agronomy with obvious public health and risk assessment implications. We address optimal experimental design strategies for determining the presence of hormesis in a controlled environment using the recently proposed Hunt-Bowman model. We propose alternative models that have an implicit hormetic threshold, discuss their advantages over current models, construct and study properties of...
Optimal strategies for pricing general insurance
Emms, P.; Haberman, S.; Savoulli, I.
2006-01-01
Optimal premium pricing policies in a competitive insurance environment are investigated using approximation methods and simulation of sample paths. The market average premium is modelled as a diffusion process, with the premium as the control function and the maximization of the expected total utility of wealth, over a finite time horizon, as the objective. In order to simplify the optimisation problem, a linear utility function is considered and two particular premium strategies are adopted...
Directory of Open Access Journals (Sweden)
Fei Wang
2017-07-01
Full Text Available The optimized dispatch of different distributed generations (DGs in stand-alone microgrid (MG is of great significance to the operation’s reliability and economy, especially for energy crisis and environmental pollution. Based on controllable load (CL and combined cooling-heating-power (CCHP model of micro-gas turbine (MT, a multi-objective optimization model with relevant constraints to optimize the generation cost, load cut compensation and environmental benefit is proposed in this paper. The MG studied in this paper consists of photovoltaic (PV, wind turbine (WT, fuel cell (FC, diesel engine (DE, MT and energy storage (ES. Four typical scenarios were designed according to different day types (work day or weekend and weather conditions (sunny or rainy in view of the uncertainty of renewable energy in variable situations and load fluctuation. A modified dispatch strategy for CCHP is presented to further improve the operation economy without reducing the consumers’ comfort feeling. Chaotic optimization and elite retention strategy are introduced into basic particle swarm optimization (PSO to propose modified chaos particle swarm optimization (MCPSO whose search capability and convergence speed are improved greatly. Simulation results validate the correctness of the proposed model and the effectiveness of MCPSO algorithm in the optimized operation application of stand-alone MG.
Optimal generator bidding strategies for power and ancillary services
Morinec, Allen G.
generator operating point in the P-Q plane. Four computer programs were developed to automatically perform the market auction simulations using the equal incremental cost rule. The software calculates the payoffs for the two competing competitors, dispatches six generators, and allocates ancillary services for 64 combinations of bidding strategies, three levels of system demand, and three different types of competitors. Matrix Game theory was utilized to calculate Nash Equilibrium solutions and mixed-strategy Nash solutions as the optimal generator bidding strategies. A method to incorporate ancillary services into the generation bidding strategy, to assure an adequate supply of ancillary services, and to allocate these necessary resources to the on-line units was devised. The optimal generator bid strategy in a power auction was shown to be the Nash Equilibrium solution found in two-player variable-sum matrix games.
Systematic Methodology for Reproducible Optimizing Batch Operation
DEFF Research Database (Denmark)
Bonné, Dennis; Jørgensen, Sten Bay
2006-01-01
This contribution presents a systematic methodology for rapid acquirement of discrete-time state space model representations of batch processes based on their historical operation data. These state space models are parsimoniously parameterized as a set of local, interdependent models. The present....... This controller may also be used for Optimizing control. The modeling and control performance is demonstrated on a fed-batch protein cultivation example. The presented methodologies lend themselves directly for application as Process Analytical Technologies (PAT)....
Optimal network protection against diverse interdictor strategies
Energy Technology Data Exchange (ETDEWEB)
Ramirez-Marquez, Jose E., E-mail: jmarquez@stevens.ed [Systems Development and Maturity Lab, School of Systems and Enterprises, Stevens Institute of Technology, Castle Point on Hudson, Hoboken, NJ 07030 (United States); Rocco, Claudio M. [Facultad de Ingenieria, Universidad Central de Venezuela, Caracas (Venezuela, Bolivarian Republic of); Levitin, Gregory [Collaborative Autonomic Computing Laboratory, School of Computer Science, University of Electronic Science and Technology of China (China); Israel Electric Corporation, Reliability and Equipment Department, Haifa 31000 (Israel)
2011-03-15
The objective of this paper is to provide optimal protection configurations for a network with components vulnerable to an interdictor with potentially different attacking strategies. Under this new setting, a solution/configuration describes the defender's optimal amount of defense resources allocated to each link against a potential interdictor strategy. Previous to this research decisions were of a binary nature, restricted to defend or not. Obtaining these configurations is important because along with describing the protection scheme, they are also useful for identifying sets of components critical to the successful performance of the network. The application of the approach can be beneficial for networks in telecommunications, energy, and supply chains to name a few. To obtain an optimal solution, the manuscript describes an evolutionary algorithm that considers continuous decision variables. The results obtained for different examples illustrate that equal resource allocation is optimal for the case of homogeneous component vulnerability. These findings are the basis for discussion and for describing future research directives in this area.
Optimizing emergency department front-end operations.
Wiler, Jennifer L; Gentle, Christopher; Halfpenny, James M; Heins, Alan; Mehrotra, Abhi; Mikhail, Michael G; Fite, Diana
2010-02-01
As administrators evaluate potential approaches to improve cost, quality, and throughput efficiencies in the emergency department (ED), "front-end" operations become an important area of focus. Interventions such as immediate bedding, bedside registration, advanced triage (triage-based care) protocols, physician/practitioner at triage, dedicated "fast track" service line, tracking systems and whiteboards, wireless communication devices, kiosk self check-in, and personal health record technology ("smart cards") have been offered as potential solutions to streamline the front-end processing of ED patients, which becomes crucial during periods of full capacity, crowding, and surges. Although each of these operational improvement strategies has been described in the lay literature, various reports exist in the academic literature about their effect on front-end operations. In this report, we present a review of the current body of academic literature, with the goal of identifying select high-impact front-end operational improvement solutions.
Learning operational strategies in surgery training.
Paydar, Shahram; Ghahramani, Zahra; Bolandparvaz, Shahram; Khalili, Hosseinali; Abbasi, Hamid Reza
2014-04-01
Education and training in surgery is in the middle of apprenticeship style of learning especially in operating room with little importance of understanding on how trainees learn. This training is one of the most difficult types of training. Medical training and expertise are the specialty of this education system. We can name these complex fields as "Operational Strategies". The strategies are includes of "what to do", "what to think" and "what to create". These strategies are good to test and train higher functions in persons who have professional's positions. Most of educational fields are complex. It means that the training is not limited in an area and includes of theory fields, areas of decision making and areas of handy and practical skills. These fields are the most relevant skills or expertise which individual must be informed of the performance of maintenance and repair or upgrade and make a new system. The operational strategy is a new training strategy for surgery students. It is useful to train surgery students to modify and improve their practices and doing surgeries and treating patients in best conditions.
On optimal strategies for upgrading networks
Energy Technology Data Exchange (ETDEWEB)
Krumke, S.O.; Noltemeier, H. [Wuerzburg Univ. (Germany). Dept. of Computer Science; Marathe, M.V. [Los Alamos National Lab., NM (United States); Ravi, S.S. [State Univ. of New York, Albany, NY (United States). Dept. of Computer Science; Ravi, R. [Carnegie-Mellon Univ., Pittsburgh, PA (United States). Graduate School of Industrial Administration; Sundaram, R. [Massachusetts Inst. of Tech., Cambridge, MA (United States)
1996-07-02
We study {ital budget constrained optimal network upgrading problems}. Such problems aim at finding optimal strategies for improving a network under some cost measure subject to certain budget constraints. Given an edge weighted graph {ital G(V,E)}, in the {ital edge based upgrading model}, it is assumed that each edge {ital e} of the given network has an associated function {ital c(e)} that specifies for each edge {ital e} the amount by which the length {ital l(e)} is to be reduced. In the {ital node based upgrading model} a node {ital v} can be upgraded at an expense of cost {ital (v)}. Such an upgrade reduces the cost of each edge incident on {ital v} by a fixed factor {rho}, where 0 < {rho} < 1. For a given budget, {ital B}, the goal is to find an improvement strategy such that the total cost of reduction is a most the given budget {ital B} and the cost of a subgraph (e.g. minimum spanning tree) under the modified edge lengths is the best over all possible strategies which obey the budget constraint. Define an ({alpha},{beta})-approximation algorithm as a polynomial-time algorithm that produces a solution within {alpha} times the optimal function value, violating the budget constraint by a factor of at most {Beta}. The results obtained in this paper include the following 1. We show that in general the problem of computing optimal reduction strategy for modifying the network as above is {bold NP}-hard. 2. In the node based model, we show how to devise a near optimal strategy for improving the bottleneck spanning tree. The algorithms have a performance guarantee of (2 ln {ital n}, 1). 3. for the edge based improvement problems we present improved (in terms of performance and time) approximation algorithms. 4. We also present pseudo-polynomial time algorithms (extendible to polynomial time approximation schemes) for a number of edge/node based improvement problems when restricted to the class of treewidth-bounded graphs.
Optimizing Integrated Terminal Airspace Operations Under Uncertainty
Bosson, Christabelle; Xue, Min; Zelinski, Shannon
2014-01-01
In the terminal airspace, integrated departures and arrivals have the potential to increase operations efficiency. Recent research has developed geneticalgorithm- based schedulers for integrated arrival and departure operations under uncertainty. This paper presents an alternate method using a machine jobshop scheduling formulation to model the integrated airspace operations. A multistage stochastic programming approach is chosen to formulate the problem and candidate solutions are obtained by solving sample average approximation problems with finite sample size. Because approximate solutions are computed, the proposed algorithm incorporates the computation of statistical bounds to estimate the optimality of the candidate solutions. A proof-ofconcept study is conducted on a baseline implementation of a simple problem considering a fleet mix of 14 aircraft evolving in a model of the Los Angeles terminal airspace. A more thorough statistical analysis is also performed to evaluate the impact of the number of scenarios considered in the sampled problem. To handle extensive sampling computations, a multithreading technique is introduced.
Trading Strategy Adipted Optimization of European Call Option
Fukumi, Toshio
2005-01-01
Optimal pricing of European call option is described by linear stochastic differential equation. Trading strategy given by a twin of stochastic variables was integrated w.r.t. Black-Scholes formula to adopt optimal pricing to tarading strategy.
Optimal growth strategies under divergent predation pressure.
Aikio, S; Herczeg, G; Kuparinen, A; Merilä, J
2013-01-01
The conditions leading to gigantism in nine-spined sticklebacks Pungitius pungitius were analysed by modelling fish growth with the von Bertalanffy model searching for the optimal strategy when the model's growth constant and asymptotic fish size parameters are negatively related to each other. Predator-related mortality was modelled through the increased risk of death during active foraging. The model was parameterized with empirical growth data of fish from four different populations and analysed for optimal growth strategy at different mortality levels. The growth constant and asymptotic fish size were negatively related in most populations. Optimal fish size, fitness and life span decreased with predator-induced mortality. At low mortality, the fitness of pond populations was higher than that of sea populations. The differences disappeared at intermediate mortalities, and sea populations had slightly higher fitness at extremely high mortalities. In the scenario where all populations mature at the same age, the pond populations perform better at low mortalities and the sea populations at high mortalities. It is concluded that a trade-off between growth constant and asymptotic fish size, together with different mortality rates, can explain a significant proportion of body size differentiation between populations. In the present case, it is a sufficient explanation of gigantism in pond P. pungitius. © 2012 The Authors. Journal of Fish Biology © 2012 The Fisheries Society of the British Isles.
Optimization of Operating Systems towards Green Computing
Directory of Open Access Journals (Sweden)
Appasami Govindasamy
2011-01-01
Full Text Available Green Computing is one of the emerging computing technology in the field of computer science engineering and technology to provide Green Information Technology (Green IT. It is mainly used to protect environment, optimize energy consumption and keeps green environment. Green computing also refers to environmentally sustainable computing. In recent years, companies in the computer industry have come to realize that going green is in their best interest, both in terms of public relations and reduced costs. Information and communication technology (ICT has now become an important department for the success of any organization. Making IT “Green” can not only save money but help save our world by making it a better place through reducing and/or eliminating wasteful practices. In this paper we focus on green computing by optimizing operating systems and scheduling of hardware resources. The objectives of the green computing are human power, electrical energy, time and cost reduction with out polluting the environment while developing the software. Operating System (OS Optimization is very important for Green computing, because it is bridge for both hardware components and Application Soft wares. The important Steps for green computing user and energy efficient usage are also discussed in this paper.
Affordance Learning Based on Subtask's Optimal Strategy
Directory of Open Access Journals (Sweden)
Huaqing Min
2015-08-01
Full Text Available Affordances define the relationships between the robot and environment, in terms of actions that the robot is able to perform. Prior work is mainly about predicting the possibility of a reactive action, and the object's affordance is invariable. However, in the domain of dynamic programming, a robot’s task could often be decomposed into several subtasks, and each subtask could limit the search space. As a result, the robot only needs to replan its sub strategy when an unexpected situation happens, and an object’s affordance might change over time depending on the robot’s state and current subtask. In this paper, we propose a novel affordance model linking the subtask, object, robot state and optimal action. An affordance represents the first action of the optimal strategy under the current subtask when detecting an object, and its influence is promoted from a primitive action to the subtask strategy. Furthermore, hierarchical reinforcement learning and state abstraction mechanism are introduced to learn the task graph and reduce state space. In the navigation experiment, the robot equipped with a camera could learn the objects’ crucial characteristics, and gain their affordances in different subtasks.
A new Methodology for Operations Strategy
DEFF Research Database (Denmark)
Koch, Christian; Rytter, Niels Gorm; Boer, Harry
2005-01-01
This paper proposes a new methodology for developing and implementing Operations Strategy (OS). It encompasses both content and process aspects of OS and differs thereby from many of the present OS methodologies. The paper outlines its paradigmatic foundation and presents aim, process, dimensions......, guidelines and required competencies for using it on OS in practice. A case-based action research strategy has been conducted to make a first test and evaluation of the OS methodology and the paper thus provides a case example illustrating its practical unfolding. Finally a discussion is made...
A new Methodology for Operations Strategy
DEFF Research Database (Denmark)
Koch, Christian; Rytter, Niels Gorm; Boer, Harry
2005-01-01
This paper proposes a new methodology for developing and implementing Operations Strategy (OS). It encompasses both content and process aspects of OS and differs thereby from many of the present OS methodologies. The paper outlines its paradigmatic foundation and presents aim, process, dimensions......, guidelines and required competencies for using it on OS in practice. A case-based action research strategy has been conducted to make a first test and evaluation of the OS methodology and the paper thus provides a case example illustrating its practical unfolding. Finally a discussion is made...
An Optimization Study of Hot Stamping Operation
Ghoo, Bonyoung; Umezu, Yasuyoshi; Watanabe, Yuko; Ma, Ninshu; Averill, Ron
2010-06-01
In the present study, 3-dimensional finite element analyses for hot-stamping processes of Audi B-pillar product are conducted using JSTAMP/NV and HEEDS. Special attention is paid to the optimization of simulation technology coupling with thermal-mechanical formulations. Numerical simulation based on FEM technology and optimization design using the hybrid adaptive SHERPA algorithm are applied to hot stamping operation to improve productivity. The robustness of the SHERPA algorithm is found through the results of the benchmark example. The SHERPA algorithm is shown to be far superior to the GA (Genetic Algorithm) in terms of efficiency, whose calculation time is about 7 times faster than that of the GA. The SHERPA algorithm could show high performance in a large scale problem having complicated design space and long calculation time.
Optimization Under Uncertainty for Wake Steering Strategies
Energy Technology Data Exchange (ETDEWEB)
Quick, Julian [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Annoni, Jennifer [National Renewable Energy Laboratory (NREL), Golden, CO (United States); King, Ryan N [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dykes, Katherine L [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Fleming, Paul A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ning, Andrew [Brigham Young University
2017-08-03
Offsetting turbines' yaw orientations from incoming wind is a powerful tool that may be leveraged to reduce undesirable wake effects on downstream turbines. First, we examine a simple two-turbine case to gain intuition as to how inflow direction uncertainty affects the optimal solution. The turbines are modeled with unidirectional inflow such that one turbine directly wakes the other, using ten rotor diameter spacing. We perform optimization under uncertainty (OUU) via a parameter sweep of the front turbine. The OUU solution generally prefers less steering. We then do this optimization for a 60-turbine wind farm with unidirectional inflow, varying the degree of inflow uncertainty and approaching this OUU problem by nesting a polynomial chaos expansion uncertainty quantification routine within an outer optimization. We examined how different levels of uncertainty in the inflow direction effect the ratio of the expected values of deterministic and OUU solutions for steering strategies in the large wind farm, assuming the directional uncertainty used to reach said OUU solution (this ratio is defined as the value of the stochastic solution or VSS).
Optimal defense strategy: storage vs. new production.
Shudo, Emi; Iwasa, Yoh
2002-12-07
If hosts produce defense proteins after they are infected by pathogens, it may take hours to days before defense becomes fully active. By producing defense proteins beforehand, and storing them until infection, the host can cope with pathogens with a short time delay. However, producing and storing defense proteins require energy, and the activated defense proteins often cause harm to the host's body as well as to pathogens. Here, we study the optimal strategy for a host who chooses the amount of stored defense proteins, the activation of the stored proteins upon infection, and the new production of the proteins. The optimal strategy is the one that minimizes the sum of the harm by pathogens and the cost of defense. The host chooses the storage size of defense proteins based on the probability distribution of the magnitude of pathogen infection. When the infection size is predictable, all the stored proteins are to be activated upon infection. The optimal strategy is to have no storage and to rely entirely on new production if the expected infection size n(0) is small, but to have a big storage without new production if n(0) is large. The transition from the "new production" phase to "storage" phase occurs at a smaller n(0) when storage cost is small, activation cost is large, pathogen toxicity is large, pathogen growth is fast, the defense is effective, the delay is long, and the infection is more likely. On the other hand, the storage size to produce for a large n(0) decreases with three cost parameters and the defense effectiveness, increases with the likelihood of infection, the toxicity and the growth rate of pathogens, and it is independent of the time delay. When infection size is much smaller than the expected size, some of the stored proteins may stay unused.
Directory of Open Access Journals (Sweden)
Mohsen Khalilpour
2013-02-01
Full Text Available Power companies world-wide have been restructuring their electric power systems from a vertically integrated entity to a deregulated, open-market environment. Previously, electric utilities usually sought to maximize the social welfare of the system with distributional equity as its main operational criterion. The operating paradigm was based on achieving the least-cost system solution while meeting reliability and security margins. This often resulted in investments in generating capacity operating at very low capacity factors. Decommissioning of this type of generating capacity was a natural outcome when the vertically integrated utilities moved over to deregulated market operations. This study proposes an optimizing base and load demand relative binding strategy for generating power apprises of different units in the investigated system. Afterwards, congestion effect in this biding strategy is investigated. The described systems analysis is implemented on 5 and 9 bus systems and optimizing technique in this issue is the Invasive Weed Optimization algorithm; the results are then compared by GA. Finally, examined systems is simulated by using the Power World software; experimental results show that the proposed technique (Invasive Weed Optimization is a high performance by compared GA for the congestion management purposes.
Operational Optimization in Port Container Terminals
DEFF Research Database (Denmark)
As a result of the significant increase in worldwide containerized transportation the development of efficient handling systems in marine terminals has become very important for port competitiveness. In order to optimize the productivity the total handling time for containers in the terminal must...... be minimized. An overview of the different operational problems in port container terminals is presented and an aggregated model and solution approach is shown. Next, there will be focused on the yard storage problem and a mathematical formulation and solution proposals will be presented....
Optimization of Train Trip Package Operation Scheme
Directory of Open Access Journals (Sweden)
Lu Tong
2015-01-01
Full Text Available Train trip package transportation is an advanced form of railway freight transportation, realized by a specialized train which has fixed stations, fixed time, and fixed path. Train trip package transportation has lots of advantages, such as large volume, long distance, high speed, simple forms of organization, and high margin, so it has become the main way of railway freight transportation. This paper firstly analyzes the related factors of train trip package transportation from its organizational forms and characteristics. Then an optimization model for train trip package transportation is established to provide optimum operation schemes. The proposed model is solved by the genetic algorithm. At last, the paper tests the model on the basis of the data of 8 regions. The results show that the proposed method is feasible for solving operation scheme issues of train trip package.
Combined optimization model for sustainable energization strategy
Abtew, Mohammed Seid
Access to energy is a foundation to establish a positive impact on multiple aspects of human development. Both developed and developing countries have a common concern of achieving a sustainable energy supply to fuel economic growth and improve the quality of life with minimal environmental impacts. The Least Developing Countries (LDCs), however, have different economic, social, and energy systems. Prevalence of power outage, lack of access to electricity, structural dissimilarity between rural and urban regions, and traditional fuel dominance for cooking and the resultant health and environmental hazards are some of the distinguishing characteristics of these nations. Most energy planning models have been designed for developed countries' socio-economic demographics and have missed the opportunity to address special features of the poor countries. An improved mixed-integer programming energy-source optimization model is developed to address limitations associated with using current energy optimization models for LDCs, tackle development of the sustainable energization strategies, and ensure diversification and risk management provisions in the selected energy mix. The Model predicted a shift from traditional fuels reliant and weather vulnerable energy source mix to a least cost and reliable modern clean energy sources portfolio, a climb on the energy ladder, and scored multifaceted economic, social, and environmental benefits. At the same time, it represented a transition strategy that evolves to increasingly cleaner energy technologies with growth as opposed to an expensive solution that leapfrogs immediately to the cleanest possible, overreaching technologies.
Local Optimization Strategies in Urban Vehicular Mobility.
Directory of Open Access Journals (Sweden)
Pierpaolo Mastroianni
Full Text Available The comprehension of vehicular traffic in urban environments is crucial to achieve a good management of the complex processes arising from people collective motion. Even allowing for the great complexity of human beings, human behavior turns out to be subject to strong constraints--physical, environmental, social, economic--that induce the emergence of common patterns. The observation and understanding of those patterns is key to setup effective strategies to optimize the quality of life in cities while not frustrating the natural need for mobility. In this paper we focus on vehicular mobility with the aim to reveal the underlying patterns and uncover the human strategies determining them. To this end we analyze a large dataset of GPS vehicles tracks collected in the Rome (Italy district during a month. We demonstrate the existence of a local optimization of travel times that vehicle drivers perform while choosing their journey. This finding is mirrored by two additional important facts, i.e., the observation that the average vehicle velocity increases by increasing the travel length and the emergence of a universal scaling law for the distribution of travel times at fixed traveled length. A simple modeling scheme confirms this scenario opening the way to further predictions.
Production of sugar and alcohol: financial and operational strategies
Directory of Open Access Journals (Sweden)
Celma de Oliveira Ribeiro
2014-12-01
Full Text Available This article proposes the construction of an optimization model to define the product portfolio of a sugarcane mill, taking into account operational and financial aspects. It is considered that the revenue earned by a producer comes from the sale of sugar and alcohol in the physical market and the results obtained through hedging in the derivatives market of sugar. Employing CVaR (Conditional Value-at-Risk, as the risk measure, the model allows the construction of an efficient frontier and, according to the producer's risk tolerance, defines the optimal strategy of production (production mix and activity in the derivatives market (hedge ratio. Through the model the article also seeks to analyze the advantage of using the options market in the construction of financial hedging strategies in agricultural commodities markets.
Impact of Fluctuating Energy Prices on the Operation Strategy of a Trigeneration System
Directory of Open Access Journals (Sweden)
Dražen Balić
2015-09-01
The optimization method is based on two criteria – energy and economic criterion, which were applied hierarchically. Therefore, two optimal operation strategies are introduced. A mixed integer non-linear programming model provides energy and cost savings up to 32% and 28% respectively in comparison with conventional system. In addition, optimal capacity of trigeneration system is explored.
Optimal allocation of trend following strategies
Grebenkov, Denis S.; Serror, Jeremy
2015-09-01
We consider a portfolio allocation problem for trend following (TF) strategies on multiple correlated assets. Under simplifying assumptions of a Gaussian market and linear TF strategies, we derive analytical formulas for the mean and variance of the portfolio return. We construct then the optimal portfolio that maximizes risk-adjusted return by accounting for inter-asset correlations. The dynamic allocation problem for n assets is shown to be equivalent to the classical static allocation problem for n2 virtual assets that include lead-lag corrections in positions of TF strategies. The respective roles of asset auto-correlations and inter-asset correlations are investigated in depth for the two-asset case and a sector model. In contrast to the principle of diversification suggesting to treat uncorrelated assets, we show that inter-asset correlations allow one to estimate apparent trends more reliably and to adjust the TF positions more efficiently. If properly accounted for, inter-asset correlations are not deteriorative but beneficial for portfolio management that can open new profit opportunities for trend followers. These concepts are illustrated using daily returns of three highly correlated futures markets: the E-mini S&P 500, Euro Stoxx 50 index, and the US 10-year T-note futures.
Production optimization of remotely operated gas wells
Energy Technology Data Exchange (ETDEWEB)
Juell, Aleksander
2012-07-01
From the introduction: The Remote Operations in Oklahoma Intended for Education (ROOKIE) project is a remote field laboratory constructed as a part of this research project. ROOKIE was initiated to provide data in research on production optimization of low productivity gas wells. In addition to this, ROOKIE is used as a teaching tool. Much of the remote operations technology used in the ROOKIE project has been used by the industry for several decades. The first use of remote data acquisition in Oklahoma was in 1989, as described by Luppens [7]. Even though this, for the most part, is old technology, the ROOKIE project is the first remote operations project set up with research and teaching as the main focus. This chapter will discuss the process of establishing the remote field laboratory and the data storage facilities. Results from the project will also be discussed. All testing, instrumentation installation, and modifications to the wells discussed in this chapter was performed by the author. The communication system between the well and NTNU, and the storage database was installed and configured by the author.(Author)
Risky Arbitrage Strategies: Optimal Portfolio Choice and Economic Implications
Liu, Jun; Timmermann, Allan G
2009-01-01
We define risky arbitrages as self-financing trading strategies that have a strictly positive market price but a zero expected cumulative payoff. A continuous time cointegrated system is used to model risky arbitrages as arising from a mean-reverting mispricing component. We derive the optimal trading strategy in closed-form and show that the standard textbook arbitrage strategy is not optimal. In a calibration exercise, we show that the optimal strategy makes a sizeable difference in economi...
Sleep As A Strategy For Optimizing Performance.
Yarnell, Angela M; Deuster, Patricia
2016-01-01
Recovery is an essential component of maintaining, sustaining, and optimizing cognitive and physical performance during and after demanding training and strenuous missions. Getting sufficient amounts of rest and sleep is key to recovery. This article focuses on sleep and discusses (1) why getting sufficient sleep is important, (2) how to optimize sleep, and (3) tools available to help maximize sleep-related performance. Insufficient sleep negatively impacts safety and readiness through reduced cognitive function, more accidents, and increased military friendly-fire incidents. Sufficient sleep is linked to better cognitive performance outcomes, increased vigor, and better physical and athletic performance as well as improved emotional and social functioning. Because Special Operations missions do not always allow for optimal rest or sleep, the impact of reduced rest and sleep on readiness and mission success should be minimized through appropriate preparation and planning. Preparation includes periods of "banking" or extending sleep opportunities before periods of loss, monitoring sleep by using tools like actigraphy to measure sleep and activity, assessing mental effectiveness, exploiting strategic sleep opportunities, and consuming caffeine at recommended doses to reduce fatigue during periods of loss. Together, these efforts may decrease the impact of sleep loss on mission and performance. 2016.
Optimal portfolio strategies under a shortfall constraint
Directory of Open Access Journals (Sweden)
D Akuma
2009-06-01
Full Text Available We impose dynamically, a shortfall constraint in terms of Tail Conditional Expectation on the portfolio selection problem in continuous time, in order to obtain optimal strategies. The financial market is assumed to comprise n risky assets driven by geometric Brownian motion and one risk-free asset. The method of Lagrange multipliers is combined with the Hamilton-Jacobi-Bellman equation to insert the constraint into the resolution framework. The constraint is re-calculated at short intervals of time throughout the investment horizon. A numerical method is applied to obtain an approximate solution to the problem. It is found that the imposition of the constraint curbs investment in the risky assets.
Operational strategies for nitrogen removal in granular sequencing batch reactor.
Chen, Fang-yuan; Liu, Yong-Qiang; Tay, Joo-Hwa; Ning, Ping
2011-05-15
This study investigated the effects of different operational strategies for nitrogen removal by aerobic granules with mean granule sizes of 1.5mm and 0.7 mm in a sequencing batch reactor (SBR). With an alternating anoxic/oxic (AO) operation mode without control of dissolve oxygen (DO), the granular sludge with different size achieved the total inorganic nitrogen (TIN) removal efficiencies of 67.8-71.5%. While under the AO condition with DO controlled at 2mg/l at the oxic phase, the TIN removal efficiency was improved up to 75.0-80.4%. A novel operational strategy of alternating anoxic/oxic combined with the step-feeding mode was developed for nitrogen removal by aerobic granules. It was found that nitrogen removal efficiencies could be further improved to 93.0-95.9% with the novel strategy. Obviously, the alternating anoxic/oxic strategy combined with step-feeding is the optimal way for TIN removal by granular sludge, which is independent of granule size. Copyright © 2011 Elsevier B.V. All rights reserved.
Optimal Bidding Strategy for Renewable Microgrid with Active Network Management
Directory of Open Access Journals (Sweden)
Seung Wan Kim
2016-01-01
Full Text Available Active Network Management (ANM enables a microgrid to optimally dispatch the active/reactive power of its Renewable Distributed Generation (RDG and Battery Energy Storage System (BESS units in real time. Thus, a microgrid with high penetration of RDGs can handle their uncertainties and variabilities to achieve the stable operation using ANM. However, the actual power flow in the line connecting the main grid and microgrid may deviate significantly from the day-ahead bids if the bids are determined without consideration of the real-time adjustment through ANM, which will lead to a substantial imbalance cost. Therefore, this study proposes a formulation for obtaining an optimal bidding which reflects the change of power flow in the connecting line by real-time adjustment using ANM. The proposed formulation maximizes the expected profit of the microgrid considering various network and physical constraints. The effectiveness of the proposed bidding strategy is verified through the simulations with a 33-bus test microgrid. The simulation results show that the proposed bidding strategy improves the expected operating profit by reducing the imbalance cost to a greater degree compared to the basic bidding strategy without consideration of ANM.
Operational strategy of adsorption desalination systems
Thu, Kyaw
2009-03-01
This paper presents the performances of an adsorption desalination (AD) system in two-bed and four-bed operational modes. The tested results are calculated in terms of key performance parameters namely, (i) specific daily water production (SDWP), (ii) cycle time, and (iii) performance ratio (PR) for various heat source temperatures, mass flow rates, cycle times along with a fixed heat sink temperature. The optimum input parameters such as driving heat source and cycle time of the AD cycle are also evaluated. It is found from the present experimental data that the maximum potable water production per tonne of adsorbent (silica gel) per day is about 10 m3 whilst the corresponding performance ratio is 0.61, and a longer cycle time is required to achieve maximum water production at lower heat source temperatures. This paper also provides a useful guideline for the operational strategy of the AD cycle. © 2008 Elsevier Ltd. All rights reserved.
Optimization of Equipment Maintenance Strategy Based on Availability
Institute of Scientific and Technical Information of China (English)
张友诚
2001-01-01
It is very important to optimize maintenance strategy in maintenance plan. Proper parameters play a decisive role for the optimization. In the opinion of writer, availability is a basic parameter, failure consequence cost and failure characteristic are also important parameters. Maintenance strategy can be optimized on the base by means of quantitative analysis and diagram.
Reconfiguration strategies for electrical devices for operation within feasibility margins
Energy Technology Data Exchange (ETDEWEB)
Gandor, Malin; Blank, Marita [Oldenburg Univ. (Germany); Lehnhoff, Sebastian [OFFIS - Institut fuer Informatik, Oldenburg (Germany)
2012-07-01
Due to a transition of the energy system towards a sustainable energy supply by the integration of renewable, decentralized energy resources, new challenges regarding a safe and secure energy supply appear. With renewable energy resources the power fee-in will be highly volatile. Furthermore, due to a correlated feed-in depending on e.g. weather phenomena or control strategies on the demand side, the system might be operated beyond feasible boundaries. However, the satisfaction of viable operational boundaries must be guaranteed. In this paper a method is presented that allows the utilization of degrees of freedom in form of decentralized flexible electric consumers and products in order to optimize an operational state with regard to its feasibility. First results are presented in a case study. (orig.)
Optimal Economic Operation of Islanded Microgrid by Using a Modified PSO Algorithm
Directory of Open Access Journals (Sweden)
Yiwei Ma
2015-01-01
Full Text Available An optimal economic operation method is presented to attain a joint-optimization of cost reduction and operation strategy for islanded microgrid, which includes renewable energy source, the diesel generator, and battery storage system. The optimization objective is to minimize the overall generating cost involving depreciation cost, operation cost, emission cost, and economic subsidy available for renewable energy source, while satisfying various equality and inequality constraints. A novel dynamic optimization process is proposed based on two different operation control modes where diesel generator or battery storage acts as the master unit to maintain the system frequency and voltage stability, and a modified particle swarm optimization algorithm is applied to get faster solution to the practical economic operation problem of islanded microgrid. With the example system of an actual islanded microgrid in Dongao Island, China, the proposed models, dynamic optimization strategy, and solution algorithm are verified and the influences of different operation strategies and optimization algorithms on the economic operation are discussed. The results achieved demonstrate the effectiveness and feasibility of the proposed method.
Strategy Developed for Selecting Optimal Sensors for Monitoring Engine Health
2004-01-01
Sensor indications during rocket engine operation are the primary means of assessing engine performance and health. Effective selection and location of sensors in the operating engine environment enables accurate real-time condition monitoring and rapid engine controller response to mitigate critical fault conditions. These capabilities are crucial to ensure crew safety and mission success. Effective sensor selection also facilitates postflight condition assessment, which contributes to efficient engine maintenance and reduced operating costs. Under the Next Generation Launch Technology program, the NASA Glenn Research Center, in partnership with Rocketdyne Propulsion and Power, has developed a model-based procedure for systematically selecting an optimal sensor suite for assessing rocket engine system health. This optimization process is termed the systematic sensor selection strategy. Engine health management (EHM) systems generally employ multiple diagnostic procedures including data validation, anomaly detection, fault-isolation, and information fusion. The effectiveness of each diagnostic component is affected by the quality, availability, and compatibility of sensor data. Therefore systematic sensor selection is an enabling technology for EHM. Information in three categories is required by the systematic sensor selection strategy. The first category consists of targeted engine fault information; including the description and estimated risk-reduction factor for each identified fault. Risk-reduction factors are used to define and rank the potential merit of timely fault diagnoses. The second category is composed of candidate sensor information; including type, location, and estimated variance in normal operation. The final category includes the definition of fault scenarios characteristic of each targeted engine fault. These scenarios are defined in terms of engine model hardware parameters. Values of these parameters define engine simulations that generate
Optimized Control Strategy For Over Loaded Offshore Wind Turbines
DEFF Research Database (Denmark)
Odgaard, Peter Fogh; Knudsen, Torben; Wisniewski, Rafal
2015-01-01
Abstract Optimized control strategy for overloaded offshore wind turbines Introduction Operation and maintenance cost are an important part of cost of energy especially for offshore wind farms. Typically unplanned service is called for due to detection off excessive loads on components, e...... controller tuning for a given wind turbine. It also enables a very safe and robust comparison between a new control strategy and the present one. Main body of abstract Is it true that power de-rating indeed the best way to reduce loads? The power de-rating approach has the drawback of only indirectly...... and service at offshore location, where accessibility can be problematic. The controller objectives are focused directly on the actual objective like lowering of fore aft fatigue loads, instead of using an indirect objective of de-rating the power production of the wind turbine. This means what the wind...
Particle Swarm Optimization With Interswarm Interactive Learning Strategy.
Qin, Quande; Cheng, Shi; Zhang, Qingyu; Li, Li; Shi, Yuhui
2016-10-01
The learning strategy in the canonical particle swarm optimization (PSO) algorithm is often blamed for being the primary reason for loss of diversity. Population diversity maintenance is crucial for preventing particles from being stuck into local optima. In this paper, we present an improved PSO algorithm with an interswarm interactive learning strategy (IILPSO) by overcoming the drawbacks of the canonical PSO algorithm's learning strategy. IILPSO is inspired by the phenomenon in human society that the interactive learning behavior takes place among different groups. Particles in IILPSO are divided into two swarms. The interswarm interactive learning (IIL) behavior is triggered when the best particle's fitness value of both the swarms does not improve for a certain number of iterations. According to the best particle's fitness value of each swarm, the softmax method and roulette method are used to determine the roles of the two swarms as the learning swarm and the learned swarm. In addition, the velocity mutation operator and global best vibration strategy are used to improve the algorithm's global search capability. The IIL strategy is applied to PSO with global star and local ring structures, which are termed as IILPSO-G and IILPSO-L algorithm, respectively. Numerical experiments are conducted to compare the proposed algorithms with eight popular PSO variants. From the experimental results, IILPSO demonstrates the good performance in terms of solution accuracy, convergence speed, and reliability. Finally, the variations of the population diversity in the entire search process provide an explanation why IILPSO performs effectively.
Decisively Avoiding Defeat: Strategy, the Operational Artist, and Limited War
2016-05-26
Decisively Avoiding Defeat: Strategy , the Operational Artist, and Limited War A Monograph by MAJ Matthew W. Bandi United States Army...NUMBER Decisively Avoiding Defeat: Strategy , the Operational Artist, and Limited War 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...ease this frustration. This monograph shows how strategy in limited war emerges from the negotiation between policy makers and operational artists over
Waste minimization strategies at Trail operations
Energy Technology Data Exchange (ETDEWEB)
Higginson, J. [Teck Cominco Metals Ltd., Trail, BC (Canada)
2003-07-01
The industrial facility at Teck Cominco in Trail, British Columbia represents one of the largest integrated zinc-lead production facilities in the world. It processes more than 600,000 tonnes per year of various metal concentrates, resulting in large amounts of waste. The company has implemented clear strategies designed to minimize or utilize the wastes. The input of unwanted species into the operation has been reduced through concentrated efforts. Recoveries were maximized through internal recycling and through the development of marketable products from materials that were once considered to be wastes. The company's results with sulphur product diversification were particularly successful, along with the use of smelter slag to make GS-CEM{sup TM}, which is used as an attractive supplementary cementitious material. figs.
Optimal strategies for electric energy contract decision making
Song, Haili
2000-10-01
The power industry restructuring in various countries in recent years has created an environment where trading of electric energy is conducted in a market environment. In such an environment, electric power companies compete for the market share through spot and bilateral markets. Being profit driven, electric power companies need to make decisions on spot market bidding, contract evaluation, and risk management. New methods and software tools are required to meet these upcoming needs. In this research, bidding strategy and contract pricing are studied from a market participant's viewpoint; new methods are developed to guide a market participant in spot and bilateral market operation. A supplier's spot market bidding decision is studied. Stochastic optimization is formulated to calculate a supplier's optimal bids in a single time period. This decision making problem is also formulated as a Markov Decision Process. All the competitors are represented by their bidding parameters with corresponding probabilities. A systematic method is developed to calculate transition probabilities and rewards. The optimal strategy is calculated to maximize the expected reward over a planning horizon. Besides the spot market, a power producer can also trade in the bilateral markets. Bidding strategies in a bilateral market are studied with game theory techniques. Necessary and sufficient conditions of Nash Equilibrium (NE) bidding strategy are derived based on the generators' cost and the loads' willingness to pay. The study shows that in any NE, market efficiency is achieved. Furthermore, all Nash equilibria are revenue equivalent for the generators. The pricing of "Flexible" contracts, which allow delivery flexibility over a period of time with a fixed total amount of electricity to be delivered, is analyzed based on the no-arbitrage pricing principle. The proposed algorithm calculates the price based on the optimality condition of the stochastic optimization formulation
Optimizing integrated airport surface and terminal airspace operations under uncertainty
Bosson, Christabelle S.
In airports and surrounding terminal airspaces, the integration of surface, arrival and departure scheduling and routing have the potential to improve the operations efficiency. Moreover, because both the airport surface and the terminal airspace are often altered by random perturbations, the consideration of uncertainty in flight schedules is crucial to improve the design of robust flight schedules. Previous research mainly focused on independently solving arrival scheduling problems, departure scheduling problems and surface management scheduling problems and most of the developed models are deterministic. This dissertation presents an alternate method to model the integrated operations by using a machine job-shop scheduling formulation. A multistage stochastic programming approach is chosen to formulate the problem in the presence of uncertainty and candidate solutions are obtained by solving sample average approximation problems with finite sample size. The developed mixed-integer-linear-programming algorithm-based scheduler is capable of computing optimal aircraft schedules and routings that reflect the integration of air and ground operations. The assembled methodology is applied to a Los Angeles case study. To show the benefits of integrated operations over First-Come-First-Served, a preliminary proof-of-concept is conducted for a set of fourteen aircraft evolving under deterministic conditions in a model of the Los Angeles International Airport surface and surrounding terminal areas. Using historical data, a representative 30-minute traffic schedule and aircraft mix scenario is constructed. The results of the Los Angeles application show that the integration of air and ground operations and the use of a time-based separation strategy enable both significant surface and air time savings. The solution computed by the optimization provides a more efficient routing and scheduling than the First-Come-First-Served solution. Additionally, a data driven analysis is
Optimal restructuring strategies under various dynamic factors
Institute of Scientific and Technical Information of China (English)
MENG Qing-xuan
2007-01-01
Corporate restructuring was identified as a new industrial force that has great impact on economic values and that therefore has become central in daily financial decision making. This article investigates the optimal restructuring strategies under different dynamic factors and their numerous impacts on firm value. The concept of quasi-leverage is introduced and valuation models are built for corporate debt and equity under imperfect market conditions. The model's input variables include the quasi-leverage and other firm-specific parameters, the output variables include multiple corporate security values. The restructuring cost is formulated in the form of exponential function, which allows us to observe the sensitivity of the variation in security values. The unified model and its analytical solution developed in this research allow us to examine the continuous changes of security values by dynamically changing the coupon rates, riskless interest rate, bankruptcy cost, quasi-leverage, personal tax rate, corporate taxes rate, transaction cost, firm risk, etc., so that the solutions provide useful guidance for financing and restructuring decisions.
Mesh refinement strategy for optimal control problems
Paiva, L. T.; Fontes, F. A. C. C.
2013-10-01
Direct methods are becoming the most used technique to solve nonlinear optimal control problems. Regular time meshes having equidistant spacing are frequently used. However, in some cases these meshes cannot cope accurately with nonlinear behavior. One way to improve the solution is to select a new mesh with a greater number of nodes. Another way, involves adaptive mesh refinement. In this case, the mesh nodes have non equidistant spacing which allow a non uniform nodes collocation. In the method presented in this paper, a time mesh refinement strategy based on the local error is developed. After computing a solution in a coarse mesh, the local error is evaluated, which gives information about the subintervals of time domain where refinement is needed. This procedure is repeated until the local error reaches a user-specified threshold. The technique is applied to solve the car-like vehicle problem aiming minimum consumption. The approach developed in this paper leads to results with greater accuracy and yet with lower overall computational time as compared to using a time meshes having equidistant spacing.
Prosumers strategy for DHC energy flow optimization
Directory of Open Access Journals (Sweden)
Vasek Lubomir
2016-01-01
Full Text Available This article introduces the proposal of discrete model of district heating and cooling system (DHC for energy flow optimization. The aim is to achieve the best solution of the objective function, usually determined by minimizing the production and distribution costs and providing meets the needs of energy consumers. The model also introduces the idea of general prosumers strategy, where all active elements within the modern DHC system are representing by prosumers object. The prosumers are perceived as objects able to actively participate in the planning of production and consumption of energy. It is assumed that the general behaviour of the object in DHC is the same, no matter how they differ in sizes and designs. Thus, all the objects are defined by two characteristics - the ability to produce and consume. The model based on this basic principle, of course, with the most accurate information about the particular values at a time, object properties and other, should provide tools for simulation and control of modern DHC, possibly superior units as Smart Energy Grids - understood as a system integrating Smart Grids (electricity and Smart Thermal Grids (heat a cool.
NASA Space Launch System Operations Strategy
Singer, Joan A.; Cook, Jerry R.
2012-01-01
The National Aeronautics and Space Administration's (NASA) Space Launch System (SLS) Program, managed at the Marshall Space Flight Center, is charged with delivering a new capability for human and scientific exploration beyond Earth orbit. The SLS also will provide backup crew and cargo services to the International Space Station, where astronauts have been training for long-duration voyages to destinations such as asteroids and Mars. For context, the SLS will be larger than the Saturn V, providing 10 percent more thrust at liftoff in its initial 70 metric ton (t) configuration and 20 percent more in its evolved 130 t configuration. The SLS Program knows that affordability is the key to sustainability. This paper will provide an overview of its operations strategy, which includes initiatives to reduce both development and fixed costs by using existing hardware and infrastructure assets to meet a first launch by 2017 within the projected budget. It also has a long-range plan to keep the budget flat using competitively selected advanced technologies that offer appropriate return on investment. To arrive at the launch vehicle concept, the SLS Program conducted internal engineering and business studies that have been externally validated by industry and reviewed by independent assessment panels. A series of design reference missions has informed the SLS operations concept, including launching the Orion Multi-Purpose Crew Vehicle on an autonomous demonstration mission in a lunar flyby scenario in 2017, and the first flight of a crew on Orion for a lunar flyby in 2021. Additional concepts address the processing of very large payloads, using a series of modular fairings and adapters to flexibly configure the rocket for the mission. This paper will describe how the SLS, Orion, and 21st Century Ground Systems programs are working together to create streamlined, affordable operations for sustainable exploration.
Optimization of wastewater treatment plant operation for greenhouse gas mitigation.
Kim, Dongwook; Bowen, James D; Ozelkan, Ertunga C
2015-11-01
This study deals with the determination of optimal operation of a wastewater treatment system for minimizing greenhouse gas emissions, operating costs, and pollution loads in the effluent. To do this, an integrated performance index that includes three objectives was established to assess system performance. The ASMN_G model was used to perform system optimization aimed at determining a set of operational parameters that can satisfy three different objectives. The complex nonlinear optimization problem was simulated using the Nelder-Mead Simplex optimization algorithm. A sensitivity analysis was performed to identify influential operational parameters on system performance. The results obtained from the optimization simulations for six scenarios demonstrated that there are apparent trade-offs among the three conflicting objectives. The best optimized system simultaneously reduced greenhouse gas emissions by 31%, reduced operating cost by 11%, and improved effluent quality by 2% compared to the base case operation.
Optimal Power Management Strategy for Energy Storage with Stochastic Loads
Directory of Open Access Journals (Sweden)
Stefano Pietrosanti
2016-03-01
Full Text Available In this paper, a power management strategy (PMS has been developed for the control of energy storage in a system subjected to loads of random duration. The PMS minimises the costs associated with the energy consumption of specific systems powered by a primary energy source and equipped with energy storage, under the assumption that the statistical distribution of load durations is known. By including the variability of the load in the cost function, it was possible to define the optimality criteria for the power flow of the storage. Numerical calculations have been performed obtaining the control strategies associated with the global minimum in energy costs, for a wide range of initial conditions of the system. The results of the calculations have been tested on a MATLAB/Simulink model of a rubber tyre gantry (RTG crane equipped with a flywheel energy storage system (FESS and subjected to a test cycle, which corresponds to the real operation of a crane in the Port of Felixstowe. The results of the model show increased energy savings and reduced peak power demand with respect to existing control strategies, indicating considerable potential savings for port operators in terms of energy and maintenance costs.
Optimality of feedback control strategies for qubit purification
Wiseman, Howard M.; Bouten, Luc
2007-01-01
Recently two papers [K. Jacobs, Phys. Rev. A {\\bf 67}, 030301(R) (2003); H. M. Wiseman and J. F. Ralph, New J. Physics {\\bf 8}, 90 (2006)] have derived control strategies for rapid purification of qubits, optimized with respect to various goals. In the former paper the proof of optimality was not mathematically rigorous, while the latter gave only heuristic arguments for optimality. In this paper we provide rigorous proofs of optimality in all cases, by applying simple concepts from optimal c...
Research on Optimization Operation of Urban Gas Pipeline Network
Institute of Scientific and Technical Information of China (English)
田一梅; 迟海燕; 李鸿; 周颖
2003-01-01
The optimization operation of gas pipeline network is investigated in this paper. Based on the theories of system optimization and the multi-object decision, a mathematical model about the multi-object optimization operation of gas pipeline network is established, in line with the demand of urban gas pipeline network operation. At the same time, an effective solution of the mathematical model is presented. A calculating software about optimization operation is compiled, coupling the actual operation of gas pipeline network. It can be applied to the operation of the gas pipeline network. The software was examined by real examples. The results indicated that 2.13%00 energy consumption and 3.12%oo gas supply cost can be reduced through optimization operation.
The Optimal Operation Criteria for a Gas Turbine Cogeneration System
Directory of Open Access Journals (Sweden)
Atsushi Akisawa
2009-04-01
Full Text Available The study demonstrated the optimal operation criteria of a gas turbine cogeneration system based on the analytical solution of a linear programming model. The optimal operation criteria gave the combination of equipment to supply electricity and steam with the minimum energy cost using the energy prices and the performance of equipment. By the comparison with a detailed optimization result of an existing cogeneration plant, it was shown that the optimal operation criteria successfully provided a direction for the system operation under the condition where the electric power output of the gas turbine was less than the capacity
Optimizing Reinjection Strategy at Palinpinon, Philippines Based on Chloride Data
Energy Technology Data Exchange (ETDEWEB)
Urbino, Ma. Elena G.; Horne, Roland N.
1992-03-24
One of the guidelines established for the safe and efficient management of the Palinpinon Geothermal Field is to adopt a production and well utilization strategy such that the rapid rate and magnitude of reinjection fluid returns leading to premature thermal breakthrough would be minimized. To help achieve this goal, sodium fluorescein and radioactive tracer tests have been conducted to determine the rate and extent of communication between the reinjection and producing sectors of the field. The first objective of this paper is to show how the results of these tests, together with information on field geometry and operating conditions were used in algorithms developed in Operations Research to allocate production and reinjection rates among the different Palinpinon wells. Due to operational and economic constraints, such tracer tests were very limited in number and scope. This prevents obtaining information on the explicit interaction between each reinjection well and the producing wells. Hence, the chloride value of the producing well, was tested to determine if use of this parameter would enable identifying fast reinjection paths among different production/reinjection well pairs. The second aim, therefore, of this paper is to show the different methods of using the chloride data of the producing wells and the injection flow rates of the reinjection wells to provide a ranking of the pair of wells and, thereby, optimize the reinjection strategy of the field.
Optimization strategies for discrete multi-material stiffness optimization
DEFF Research Database (Denmark)
Hvejsel, Christian Frier; Lund, Erik; Stolpe, Mathias
2011-01-01
Design of composite laminated lay-ups are formulated as discrete multi-material selection problems. The design problem can be modeled as a non-convex mixed-integer optimization problem. Such problems are in general only solvable to global optimality for small to moderate sized problems. To attack...... larger problem instances we formulate convex and non-convex continuous relaxations which can be solved using gradient based optimization algorithms. The convex relaxation yields a lower bound on the attainable performance. The optimal solution to the convex relaxation is used as a starting guess...
Developing an Integrated Design Strategy for Chip Layout Optimization
Wits, Wessel Willems; Jauregui Becker, Juan Manuel; van Vliet, Frank Edward; te Riele, G.J.
2011-01-01
This paper presents an integrated design strategy for chip layout optimization. The strategy couples both electric and thermal aspects during the conceptual design phase to improve chip performances; thermal management being one of the major topics. The layout of the chip circuitry is optimized acco
Optimizing metapopulation sustainability through a checkerboard strategy.
Zion, Yossi Ben; Yaari, Gur; Shnerb, Nadav M
2010-01-22
The persistence of a spatially structured population is determined by the rate of dispersal among habitat patches. If the local dynamic at the subpopulation level is extinction-prone, the system viability is maximal at intermediate connectivity where recolonization is allowed, but full synchronization that enables correlated extinction is forbidden. Here we developed and used an algorithm for agent-based simulations in order to study the persistence of a stochastic metapopulation. The effect of noise is shown to be dramatic, and the dynamics of the spatial population differs substantially from the predictions of deterministic models. This has been validated for the stochastic versions of the logistic map, the Ricker map and the Nicholson-Bailey host-parasitoid system. To analyze the possibility of extinction, previous studies were focused on the attractiveness (Lyapunov exponent) of stable solutions and the structure of their basin of attraction (dependence on initial population size). Our results suggest that these features are of secondary importance in the presence of stochasticity. Instead, optimal sustainability is achieved when decoherence is maximal. Individual-based simulations of metapopulations of different sizes, dimensions and noise types, show that the system's lifetime peaks when it displays checkerboard spatial patterns. This conclusion is supported by the results of a recently published Drosophila experiment. The checkerboard strategy provides a technique for the manipulation of migration rates (e.g., by constructing corridors) in order to affect the persistence of a metapopulation. It may be used in order to minimize the risk of extinction of an endangered species, or to maximize the efficiency of an eradication campaign.
Optimizing metapopulation sustainability through a checkerboard strategy.
Directory of Open Access Journals (Sweden)
Yossi Ben Zion
2010-01-01
Full Text Available The persistence of a spatially structured population is determined by the rate of dispersal among habitat patches. If the local dynamic at the subpopulation level is extinction-prone, the system viability is maximal at intermediate connectivity where recolonization is allowed, but full synchronization that enables correlated extinction is forbidden. Here we developed and used an algorithm for agent-based simulations in order to study the persistence of a stochastic metapopulation. The effect of noise is shown to be dramatic, and the dynamics of the spatial population differs substantially from the predictions of deterministic models. This has been validated for the stochastic versions of the logistic map, the Ricker map and the Nicholson-Bailey host-parasitoid system. To analyze the possibility of extinction, previous studies were focused on the attractiveness (Lyapunov exponent of stable solutions and the structure of their basin of attraction (dependence on initial population size. Our results suggest that these features are of secondary importance in the presence of stochasticity. Instead, optimal sustainability is achieved when decoherence is maximal. Individual-based simulations of metapopulations of different sizes, dimensions and noise types, show that the system's lifetime peaks when it displays checkerboard spatial patterns. This conclusion is supported by the results of a recently published Drosophila experiment. The checkerboard strategy provides a technique for the manipulation of migration rates (e.g., by constructing corridors in order to affect the persistence of a metapopulation. It may be used in order to minimize the risk of extinction of an endangered species, or to maximize the efficiency of an eradication campaign.
DEFF Research Database (Denmark)
Connolly, David; Lund, Henrik; Finn, P.
2011-01-01
that almost all (not, vert, similar97%) of the profits can be obtained by a PHES facility when it is optimised using the 24Optimal strategy developed, which optimises the energy storage based on the day-ahead electricity prices. However, to maximise profits with the 24Optimal strategy, the day......In this paper, three practical operation strategies (24Optimal, 24Prognostic, and 24Hsitrocial) are compared to the optimum profit feasible for a PHES facility with a 360 MW pump, 300 MW turbine, and a 2 GWh storage utilising price arbitrage on 13 electricity spot markets. The results indicate......-ahead electricity prices must be the actual prices which the PHES facility is charged or the PHES operator must have very accurate price predictions. Otherwise, the predicted profit could be significantly reduced and even become a loss. Finally, using the 24Optimal strategy, the PHES profit can surpass the annual...
Classification and uptake of reservoir operation optimization methods
Dobson, Barnaby; Pianosi, Francesca; Wagener, Thorsten
2016-04-01
Reservoir operation optimization algorithms aim to improve the quality of reservoir release and transfer decisions. They achieve this by creating and optimizing the reservoir operating policy; a function that returns decisions based on the current system state. A range of mathematical optimization algorithms and techniques has been applied to the reservoir operation problem of policy optimization. In this work, we propose a classification of reservoir optimization approaches by focusing on the formulation of the water management problem rather than the optimization algorithm type. We believe that decision makers and operators will find it easier to navigate a classification system based on the problem characteristics, something they can clearly define, rather than the optimization algorithm. Part of this study includes an investigation regarding the extent of algorithm uptake and the possible reasons that limit real world application.
Yuan, Xiangjuan; Gao, Dawen; Liang, Hong
2012-06-01
Aerobic granules after 6 months storage were employed in identical sequencing batch reactors (SBRs) using synthetic wastewater to investigate the impacts of different operational strategies on granules' reactivation process. The SBRs were operated under three operational strategies for reactivation of (a) different organic loading rate (OLR); (b) different ammonia concentration; and (c) different shear force (a superficial upflow air velocity). The results indicated that granules after long-term storage could be successfully recovered after 7 days of operation, and the excellent granule reactivation performance was closely related to the operational strategies, since inappropriate operational strategies could cause the outgrowth of filamentous bacteria and granule disintegration. Based on comprehensive comparison of reactivation performance under different operational strategies, the optimal operation strategy for granule reactivation was suggested at OLR of 0.8 kg COD/m(3)/day, ammonia concentration of 15-20 mg/L, and a superficial upflow air velocity of 2.6 cm/s. After 7 days operation under the optimal strategy, the dark brown granules (12 months storage) restored their bioactivities to previous state, in terms of COD removal efficiency (97.44%) and specific oxygen uptake rate (40.63 mg O(2)/g SS h(-1)). The results shed light on the future practical application of stored aerobic granules as bioseed for reactor fast start-up.
Directory of Open Access Journals (Sweden)
Azwar Aziz
2015-06-01
Full Text Available Jumlah pelanggan ketiga operator telekomunikasi seluler pada akhir tahun 2013, yaitu PT. Telkomsel Tbk, PT. XL Axiata Tbk, dan PT. Indosat Tbk, sebanyak 251,285 juta. Jumlah pelanggan telekomunikasi seluler ini telah melebihi jumlah penduduk Indonesia sebesar 242,013 juta pada akhir tahun 2013. Ketiga operator telekomunikasi seluler tersebut mendominasi pangsa pasar seluler di Indonesia dan sangat menentukan tingkat harga, kualitas layanan dan strategi persaingan lainnya. Persaingan di telekomunikasi seluler saat ini sudah masuk ke masa jenuh untuk suara dan SMS, tetapi sudah beralih ke layanan data atau menggunaan internet. Para operator telekomunikasi seluler berlomba-lomba untuk meningkatkan kualitas layanan internet kepada pelanggan yang menggunakan prabayar dan pascabayar untuk suara dan SMS.Kajian ini menggunakan metodologi penelitian kualitatif, dengan melakukan observasi atau pengamatan langsung ke lapangan kepada Telkomsel, XL Axiata dan Indosat.Teknik analisis data menggunakan teknik analisis deskritif. Berdasarkan hasil analisis diperoleh bahwa strategi persaingan ketiga operator tersebut dari aspekcore competence, time based competition, disiplin nilai sama-sama mengimplementasikannya. Dari aspek expeditionary marketing sangat tergantung pada luas jaringan yang dimiliki, aspek standar produk, memiliki sertifikat ISO yang lebih baik dan kompetensi manajemen fokus pada sumber daya manusia dengan belajar ke luar negeri. *****The number of subscribers of three mobile telecommunication operators by the end of 2013, namely PT. Telkomsel Tbk, PT. XL Axiata Tbk, and PT. Indosat Tbk is 251.285 million. The number of mobile telecommunication subscribers has exceeded the population of Indonesia amounted to 242.013 million at the end of 2013. Those operators dominate the market in Indonesia and determine the level of price, quality of service and other competitive strategies. Competition in the mobile telecommunications currently
Research on Design Optimization Strategy in Virtual Product Development
Institute of Scientific and Technical Information of China (English)
潘军; 韩帮军; 范秀敏; 马登哲
2004-01-01
Simulation and optimization are the key points of virtual product development (VPD). Traditional engineering simulation software and optimization methods are inadequate to analyze the optimization problems because of its computational inefficiency. A systematic design optimization strategy by using statistical methods and mathematical optimization technologies is proposed. This method extends the design of experiments (DOE) and the simulation metamodel technologies. Metamodels are built to in place of detailed simulation codes based on effectively DOE, and then be linked to optimization routines for fast analysis, or serve as a bridge for integrating simulation software across different domains. A design optimization of composite material structure is used to demonstrate the newly introduced methodology.
Optimal vaccination strategies and rational behaviour in seasonal epidemics.
Doutor, Paulo; Rodrigues, Paula; Soares, Maria do Céu; Chalub, Fabio A C C
2016-12-01
We consider a SIRS model with time dependent transmission rate. We assume time dependent vaccination which confers the same immunity as natural infection. We study two types of vaccination strategies: (i) optimal vaccination, in the sense that it minimizes the effort of vaccination in the set of vaccination strategies for which, for any sufficiently small perturbation of the disease free state, the number of infectious individuals is monotonically decreasing; (ii) Nash-equilibria strategies where all individuals simultaneously minimize the joint risk of vaccination versus the risk of the disease. The former case corresponds to an optimal solution for mandatory vaccinations, while the second corresponds to the equilibrium to be expected if vaccination is fully voluntary. We are able to show the existence of both optimal and Nash strategies in a general setting. In general, these strategies will not be functions but Radon measures. For specific forms of the transmission rate, we provide explicit formulas for the optimal and the Nash vaccination strategies.
Estimation of optimal feeding strategies for fed-batch bioprocesses.
Franco-Lara, Ezequiel; Weuster-Botz, Dirk
2005-07-01
A generic methodology for feeding strategy optimization is presented. This approach uses a genetic algorithm to search for optimal feeding profiles represented by means of artificial neural networks (ANN). Exemplified on a fed-batch hybridoma cell cultivation, the approach has proven to be able to cope with complex optimization tasks handling intricate constraints and objective functions. Furthermore, the performance of the method is compared with other previously reported standard techniques like: (1) optimal control theory, (2) first order conjugate gradient, (3) dynamical programming, (4) extended evolutionary strategies. The methodology presents no restrictions concerning the number or complexity of the state variables and therefore constitutes a remarkable alternative for process development and optimization.
Modelling and operation strategies of DLR's large scale thermocline test facility (TESIS)
Odenthal, Christian; Breidenbach, Nils; Bauer, Thomas
2017-06-01
In this work an overview of the TESIS:store thermocline test facility and its current construction status will be given. Based on this, the TESIS:store facility using sensible solid filler material is modelled with a fully transient model, implemented in MATLAB®. Results in terms of the impact of filler site and operation strategies will be presented. While low porosity and small particle diameters for the filler material are beneficial, operation strategy is one key element with potential for optimization. It is shown that plant operators have to ponder between utilization and exergetic efficiency. Different durations of the charging and discharging period enable further potential for optimizations.
An optimal replication strategy for data grid systems
Institute of Scientific and Technical Information of China (English)
JIANG Jianjin; YANG Guangwen
2007-01-01
Data access latency is an important metric of system performance in data grid.By means of efficient replication strategy,the amount of data transferred in a wide area network will decrease,and the average access latency of data will decrease ultimately.The motivation of our research is to solve the optimized replica distribution problem in a data grid;that is,the system should utilize many replicas for every data with storage constraints to minimize the average access latency of data.This paper proposes a model of replication strategy in federated data grid and gives the optimized solution.The analysis results and simulation results show that the optimized replication strategy proposed in this paper is superior to LRU caching strategy,uniform replication strategy,proportional replication strategy and square root replication strategy in terms of wide area network bandwidth requirement and in the average access latency of data.
An optimal tuning strategy for tidal turbines
Vennell, Ross
2016-11-01
Tuning wind and tidal turbines is critical to maximizing their power output. Adopting a wind turbine tuning strategy of maximizing the output at any given time is shown to be an extremely poor strategy for large arrays of tidal turbines in channels. This `impatient-tuning strategy' results in far lower power output, much higher structural loads and greater environmental impacts due to flow reduction than an existing `patient-tuning strategy' which maximizes the power output averaged over the tidal cycle. This paper presents a `smart patient tuning strategy', which can increase array output by up to 35% over the existing strategy. This smart strategy forgoes some power generation early in the half tidal cycle in order to allow stronger flows to develop later in the cycle. It extracts enough power from these stronger flows to produce more power from the cycle as a whole than the existing strategy. Surprisingly, the smart strategy can often extract more power without increasing maximum structural loads on the turbines, while also maintaining stronger flows along the channel. This paper also shows that, counterintuitively, for some tuning strategies imposing a cap on turbine power output to limit loads can increase a turbine's average power output.
An optimal tuning strategy for tidal turbines.
Vennell, Ross
2016-11-01
Tuning wind and tidal turbines is critical to maximizing their power output. Adopting a wind turbine tuning strategy of maximizing the output at any given time is shown to be an extremely poor strategy for large arrays of tidal turbines in channels. This 'impatient-tuning strategy' results in far lower power output, much higher structural loads and greater environmental impacts due to flow reduction than an existing 'patient-tuning strategy' which maximizes the power output averaged over the tidal cycle. This paper presents a 'smart patient tuning strategy', which can increase array output by up to 35% over the existing strategy. This smart strategy forgoes some power generation early in the half tidal cycle in order to allow stronger flows to develop later in the cycle. It extracts enough power from these stronger flows to produce more power from the cycle as a whole than the existing strategy. Surprisingly, the smart strategy can often extract more power without increasing maximum structural loads on the turbines, while also maintaining stronger flows along the channel. This paper also shows that, counterintuitively, for some tuning strategies imposing a cap on turbine power output to limit loads can increase a turbine's average power output.
Modeling and optimization of laser cutting operations
Directory of Open Access Journals (Sweden)
Gadallah Mohamed Hassan
2015-01-01
Full Text Available Laser beam cutting is one important nontraditional machining process. This paper optimizes the parameters of laser beam cutting parameters of stainless steel (316L considering the effect of input parameters such as power, oxygen pressure, frequency and cutting speed. Statistical design of experiments is carried in three different levels and process responses such as average kerf taper (Ta, surface roughness (Ra and heat affected zones are measured accordingly. A response surface model is developed as a function of the process parameters. Responses predicted by the models (as per Taguchi’s L27OA are employed to search for an optimal combination to achieve desired process yield. Response Surface Models (RSMs are developed for mean responses, S/N ratio, and standard deviation of responses. Optimization models are formulated as single objective optimization problem subject to process constraints. Models are formulated based on Analysis of Variance (ANOVA and optimized using Matlab developed environment. Optimum solutions are compared with Taguchi Methodology results. As such, practicing engineers have means to model, analyze and optimize nontraditional machining processes. Validation experiments are carried to verify the developed models with success.
Optimal relocation strategies for spatially mobile consumers
Iordanov, Iordan
2007-01-01
We develop a model of the behaviour of a dynamically optimizing economic agent who makes consumption-saving and spatial relocation decisions. We formulate an existence result for the model, derive the necessary conditions for optimality and study the behaviour of the economic agent, focusing on the case of a wage distribution with a single maximum.
Strategies for Optimal Design of Structural Systems
DEFF Research Database (Denmark)
Enevoldsen, I.; Sørensen, John Dalsgaard
1992-01-01
Reliability-based design of structural systems is considered. Especially systems where the reliability model is a series system of parallel systems are analysed. A sensitivity analysis for this class of problems is presented. Direct and sequential optimization procedures to solve the optimization...... problems are described. Numerical tests indicate that a sequential technique called the bounds iteration method (BIM) is particularly fast and stable....
Optimal strategy for selling on group-buying website
Directory of Open Access Journals (Sweden)
Xuan Jiang
2014-09-01
Full Text Available Purpose: The purpose of this paper is to help business marketers with offline channels to make decisions on whether to sell through Group-buying (GB websites and how to set online price with the coordination of maximum deal size on GB websites. Design/methodology/approach: Considering the deal structure of GB websites especially for the service fee and minimum deal size limit required by GB websites, advertising effect of selling on GB websites, and interaction between online and offline markets, an analytical model is built to derive optimal online price and maximum deal size for sellers selling through GB website. This paper aims to answer four research questions: (1 How to make a decision on maximum deal size with coordination of the deal price? (2 Will selling on GB websites always be better than staying with offline channel only? (3 What kind of products is more appropriate to sell on GB website? (4How could GB website operator induce sellers to offer deep discount in GB deals? Findings and Originality/value: This paper obtains optimal strategies for sellers selling on GB website and finds that: Even if a seller has sufficient capacity, he/she may still set a maximum deal size on the GB deal to take advantage of Advertisement with Limited Availability (ALA effect; Selling through GB website may not bring a higher profit than selling only through offline channel when a GB site only has a small consumer base and/or if there is a big overlap between the online and offline markets; Low margin products are more suitable for being sold online with ALA strategies (LP-ALA or HP-ALA than high margin ones; A GB site operator could set a small minimum deal size to induce deep discounts from the sellers selling through GB deals. Research limitations/implications: The present study assumed that the demand function is determinate and linear. It will be interesting to study how stochastic demand and a more general demand function affect the optimal
Optimization Criteria of Power Transformer Operation
Directory of Open Access Journals (Sweden)
A. A. Gonchar
2006-01-01
Full Text Available It has been shown that minimum losses in active power of a power transformer do not correspond to its maximum efficiency. For a transformer being operated there are no so called «zones of its economical operation». In this case strictly specified value of active power losses corresponds to a particular current of the winding.
Issues and Strategies in Solving Multidisciplinary Optimization Problems
Patnaik, Surya
2013-01-01
Optimization research at NASA Glenn Research Center has addressed the design of structures, aircraft and airbreathing propulsion engines. The accumulated multidisciplinary design activity is collected under a testbed entitled COMETBOARDS. Several issues were encountered during the solution of the problems. Four issues and the strategies adapted for their resolution are discussed. This is followed by a discussion on analytical methods that is limited to structural design application. An optimization process can lead to an inefficient local solution. This deficiency was encountered during design of an engine component. The limitation was overcome through an augmentation of animation into optimization. Optimum solutions obtained were infeasible for aircraft and airbreathing propulsion engine problems. Alleviation of this deficiency required a cascading of multiple algorithms. Profile optimization of a beam produced an irregular shape. Engineering intuition restored the regular shape for the beam. The solution obtained for a cylindrical shell by a subproblem strategy converged to a design that can be difficult to manufacture. Resolution of this issue remains a challenge. The issues and resolutions are illustrated through a set of problems: Design of an engine component, Synthesis of a subsonic aircraft, Operation optimization of a supersonic engine, Design of a wave-rotor-topping device, Profile optimization of a cantilever beam, and Design of a cylindrical shell. This chapter provides a cursory account of the issues. Cited references provide detailed discussion on the topics. Design of a structure can also be generated by traditional method and the stochastic design concept. Merits and limitations of the three methods (traditional method, optimization method and stochastic concept) are illustrated. In the traditional method, the constraints are manipulated to obtain the design and weight is back calculated. In design optimization, the weight of a structure becomes the
Optimizing urology group partnerships: collaboration strategies and compensation best practices.
Jacoby, Dana L; Maller, Bruce S; Peltier, Lisa R
2014-10-01
Market forces in health care have created substantial regulatory, legislative, and reimbursement changes that have had a significant impact on urology group practices. To maintain viability, many urology groups have merged into larger integrated entities. Although group operations vary considerably, the majority of groups have struggled with the development of a strong culture, effective decision-making, and consensus-building around shared resources, income, and expense. Creating a sustainable business model requires urology group leaders to allocate appropriate time and resources to address these issues in a proactive manner. This article outlines collaboration strategies for creating an effective culture, governance, and leadership, and provides practical suggestions for optimizing the performance of the urology group practice.
An Overview of Optimizing Strategies for Flotation Banks
Directory of Open Access Journals (Sweden)
Miguel Maldonado
2012-10-01
Full Text Available A flotation bank is a serial arrangement of cells. How to optimally operate a bank remains a challenge. This article reviews three reported strategies: air profiling, mass-pull (froth velocity profiling and Peak Air Recovery (PAR profiling. These are all ways of manipulating the recovery profile down a bank, which may be the property being exploited. Mathematical analysis has shown that a flat cell-by-cell recovery profile maximizes the separation of two floatable minerals for a given target bank recovery when the relative floatability is constant down the bank. Available bank survey data are analyzed with respect to recovery profiling. Possible variations on recovery profile to minimize entrainment are discussed.
Optimal operation of water distribution networks under local pipe failures
Institute of Scientific and Technical Information of China (English)
TIAN Yi-mei; G.Y.FU; CHI Hai-yan; LIU Ye
2007-01-01
The optimal operation of water distribution networks under local pipe failures, such as water main breaks, was proposed.Based on a hydraulic analysis and a simulation of water distribution networks, a macroscopic model for a network under a local pipe failure was established by the statistical regression. After the operation objectives under a local pipe failure were determined, the optimal operation model was developed and solved by the genetic algorithm. The program was developed and examined by a city distribution network. The optimal operation alternative shows that the electricity cost is saved approximately 11%, the income of the water corporation is increased approximately 5%, and the pressure in the water distribution network is distributed evenly to ensure the network safe operation. Therefore, the proposed method for optimal operation under local pipe failure is feasible and cost-effective.
Strategies in tower solar power plant optimization
Ramos, A.; Ramos, F.
2012-09-01
A method for optimizing a central receiver solar thermal electric power plant is studied. We parametrize the plant design as a function of eleven design variables and reduce the problem of finding optimal designs to the numerical problem of finding the minimum of a function of several variables. This minimization problem is attacked with different algorithms both local and global in nature. We find that all algorithms find the same minimum of the objective function. The performance of each of the algorithms and the resulting designs are studied for two typical cases. We describe a method to evaluate the impact of design variables in the plant performance. This method will tell us what variables are key to the optimal plant design and which ones are less important. This information can be used to further improve the plant design and to accelerate the optimization procedure.
Strategies in tower solar power plant optimization
Ramos, A
2012-01-01
A method for optimizing a central receiver solar thermal electric power plant is studied. We parametrize the plant design as a function of eleven design variables and reduce the problem of finding optimal designs to the numerical problem of finding the minimum of a function of several variables. This minimization problem is attacked with different algorithms both local and global in nature. We find that all algorithms find the same minimum of the objective function. The performance of each of the algorithms and the resulting designs are studied for two typical cases. We describe a method to evaluate the impact of design variables in the plant performance. This method will tell us what variables are key to the optimal plant design and which ones are less important. This information can be used to further improve the plant design and to accelerate the optimization procedure.
Optimization Under Uncertainty for Wake Steering Strategies
Energy Technology Data Exchange (ETDEWEB)
Quick, Julian [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Annoni, Jennifer [National Renewable Energy Laboratory (NREL), Golden, CO (United States); King, Ryan N [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dykes, Katherine L [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Fleming, Paul A [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2017-08-03
This presentation covers the motivation for this research, optimization under the uncertainty problem formulation, a two-turbine case, the Princess Amalia Wind Farm case, and conclusions and next steps.
Strategies in tower solar power plant optimization
RAMOS, A.; RAMOS, F.
2012-01-01
A method for optimizing a central receiver solar thermal electric power plant is studied. We parametrize the plant design as a function of eleven design variables and reduce the problem of finding optimal designs to the numerical problem of finding the minimum of a function of several variables. This minimization problem is attacked with different algorithms both local and global in nature. We find that all algorithms find the same minimum of the objective function. The performance of each of...
Deterministic operations research models and methods in linear optimization
Rader, David J
2013-01-01
Uniquely blends mathematical theory and algorithm design for understanding and modeling real-world problems Optimization modeling and algorithms are key components to problem-solving across various fields of research, from operations research and mathematics to computer science and engineering. Addressing the importance of the algorithm design process. Deterministic Operations Research focuses on the design of solution methods for both continuous and discrete linear optimization problems. The result is a clear-cut resource for understanding three cornerstones of deterministic operations resear
Operations Optimization of Hybrid Energy Systems under Variable Markets
Energy Technology Data Exchange (ETDEWEB)
Chen, Jun; Garcia, Humberto E.
2016-07-01
Hybrid energy systems (HES) have been proposed to be an important element to enable increasing penetration of clean energy. This paper investigates the operations flexibility of HES, and develops a methodology for operations optimization to maximize its economic value based on predicted renewable generation and market information. The proposed operations optimizer allows systematic control of energy conversion for maximal economic value, and is illustrated by numerical results.
Towards optimal saving in membrane operation
Ven, van de Wilhelmus Johannes Cornelis
2008-01-01
This work aims at the development of methods for fingerprinting filtration processes. These fingerprints can potentially be used to optimize the filtration performance of large scale dead-end hollow fiber ultrafiltration systems that are used nowadays in the production of drinking water. The develop
An approximation based global optimization strategy for structural synthesis
Sepulveda, A. E.; Schmit, L. A.
1991-01-01
A global optimization strategy for structural synthesis based on approximation concepts is presented. The methodology involves the solution of a sequence of highly accurate approximate problems using a global optimization algorithm. The global optimization algorithm implemented consists of a branch and bound strategy based on the interval evaluation of the objective function and constraint functions, combined with a local feasible directions algorithm. The approximate design optimization problems are constructed using first order approximations of selected intermediate response quantities in terms of intermediate design variables. Some numerical results for example problems are presented to illustrate the efficacy of the design procedure setforth.
Optimal management strategies for placenta accreta
National Research Council Canada - National Science Library
Eller; Porter; Soisson; Silver
2009-01-01
..., and hypogastric artery ligation. Main outcome measures Early morbidity (prolonged maternal intensive care unit admission, large volume of blood transfusion, coagulopathy, ureteral injury, or early re-operation...
Energetic optimization of the chilled water systems operation at hotels
Directory of Open Access Journals (Sweden)
Reineris Montero Laurencio
2015-12-01
Full Text Available The hotel exploitation, while continuing to satisfy the customers, needs to decrease the requests of electric power as the principal energy carrier. Solving issues regarding the occupation of a hotel integrally, taking the air conditioning as center of attention, which demands the bigger consumptions of electricity, results in a complex task. To solve this issue, a procedure was implemented to optimize the operation of the water-chilled systems. The procedure integrates an energy model with a strategy of low occupation following energetic criteria based on combinatorial-evolutionary criteria. To classify the information, the formulation of the tasks and the synthesis of the solutions, a methodology of analysis and synthesis of engineering is used. The energetic model considers the variability of the local climatology and the occupation of the selected rooms, and includes: the thermal model of the building obtained by means of artificial neural networks, the hydraulic model and the model of the compression work. These elements allow to find the variable of decision occupation, performing intermediate calculations to obtain the velocity of rotation in the centrifugal pump and the output temperature of the cooler water, minimizing the requirements of electric power in the water-chilled systems. To evaluate the states of the system, a combinatorial optimization is used through the following methods: simple exhaustive, stepped exhaustive or genetic algorithm depending on the quantity of variants of occupation. All calculation tasks and algorithms of the procedure were automated through a computer application.
Optimizing the 3R study strategy to learn from text
Reijners, Pauline; Kester, Liesbeth; Wetzels, Sandra; Kirschner, Paul A.
2013-01-01
Reijners, P. B. G., Kester, L., Wetzels, S. A. J., & Kirschner, P. A. (2013, 29 May). Optimizing the 3R study strategy to learn from text. Presentation at plenary meeting Learning & Cogntion, Heerlen, The Netherlands.
Optimizing the 3R study strategy to learn from text
Reijners, Pauline; Kester, Liesbeth; Wetzels, Sandra; Kirschner, Paul A.
2012-01-01
Reijners, P. B. G., Kester, L., Wetzels, S. A. J., & Kirschner, P. A. (2012, 21 November). Optimizing the 3R study strategy to learn from text. Presentation at research meeting Educational and Developmental Psychology, Erasmus University, Rotterdam, The Netherlands.
Optimizing the 3R study strategy to learn from text
Reijners, Pauline; Kester, Liesbeth; Wetzels, Sandra; Kirschner, Paul A.
2013-01-01
Reijners, P. B. G., Kester, L., Wetzels, S. A. J., & Kirschner, P. A. (2013, 7 November). Optimizing the 3R study strategy to learn from text. Paper presented at the ICO National Fall School, Maastricht, The Netherlands.
The construction of optimal hedging portfolio strategies of an investor
African Journals Online (AJOL)
We categorised the investor's portfolio into two folds: the initial investment and the capital gain ... We will also describe the dynamic of our stock price using Binomial lattice model ... equation to derive the optimal values of our trading strategies.
UMTS network planning, optimization, and inter-operation with GSM
Rahnema, Moe
2008-01-01
UMTS Network Planning, Optimization, and Inter-Operation with GSM is an accessible, one-stop reference to help engineers effectively reduce the time and costs involved in UMTS deployment and optimization. Rahnema includes detailed coverage from both a theoretical and practical perspective on the planning and optimization aspects of UMTS, and a number of other new techniques to help operators get the most out of their networks. Provides an end-to-end perspective, from network design to optimizationIncorporates the hands-on experiences of numerous researchersSingle
Strategy optimization for controlled Markov process with descriptive complexity constraint
Institute of Scientific and Technical Information of China (English)
JIA QingShan; ZHAO QianChuan
2009-01-01
Due to various advantages in storage and Implementation,simple strategies are usually preferred than complex strategies when the performances are close.Strategy optimization for controlled Markov process with descriptive complexity constraint provides a general framework for many such problems.In this paper,we first show by examples that the descriptive complexity and the performance of a strategy could be Independent,and use the F-matrix in the No-Free-Lunch Theorem to show the risk that approximating complex strategies may lead to simple strategies that are unboundedly worse in cardinal performance than the original complex strategies.We then develop a method that handles the descriptive complexity constraint directly,which describes simple strategies exactly and only approximates complex strategies during the optimization.The ordinal performance difference between the resulting strategies of this selective approximation method and the global optimum is quantified.Numerical examples on an engine maintenance problem show how this method Improves the solution quality.We hope this work sheds some insights to solving general strategy optimization for controlled Markov procase with descriptive complexity constraint.
Long-Run Savings and Investment Strategy Optimization
Directory of Open Access Journals (Sweden)
Russell Gerrard
2014-01-01
Full Text Available We focus on automatic strategies to optimize life cycle savings and investment. Classical optimal savings theory establishes that, given the level of risk aversion, a saver would keep the same relative amount invested in risky assets at any given time. We show that, when optimizing lifecycle investment, performance and risk assessment have to take into account the investor’s risk aversion and the maximum amount the investor could lose, simultaneously. When risk aversion and maximum possible loss are considered jointly, an optimal savings strategy is obtained, which follows from constant rather than relative absolute risk aversion. This result is fundamental to prove that if risk aversion and the maximum possible loss are both high, then holding a constant amount invested in the risky asset is optimal for a standard lifetime saving/pension process and outperforms some other simple strategies. Performance comparisons are based on downside risk-adjusted equivalence that is used in our illustration.
Immune clonal selection optimization method with combining mutation strategies
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
In artificial immune optimization algorithm, the mutation of immune cells has been considered as the key operator that determines the algorithm performance. Traditional immune optimization algorithms have used a single mutation operator, typically a Gaussian. Using a variety of mutation operators that can be combined during evolution to generate different probability density function could hold the potential for producing better solutions with less computational effort. In view of this, a linear combination...
Operational Strategies for Single-Stage Crossdocks
Wang, Jiana-Fu
2010-01-01
Because of the growing importance of hub-and-spoke operations in the trucking industry, crossdocking has become an important and effective tool to transfer freight. Companies like Wal-Mart, Costco and Home Depot are using this kind of facility in their logistics operations. In these crossdocks, efficiently operating them, thereby reducing unnecessary waiting and staging congestion for freight and workers is an important issue for managers. This dissertation uses real-time information...
Operational Readiness Simulator: Optimizing Operational Availability Using a Virtual Environment
Directory of Open Access Journals (Sweden)
Shaun Horning
2012-01-01
Full Text Available The maintenance and logistics systems that support aircraft fleets are complex and often very integrated. The complexity of these systems makes it difficult to assess the impact of events that affect operational capability, to identify the need for resources that can affect aircraft availability, or to assess the impact and potential benefits of the system and procedural changes. This problem is further complicated by the adoption of condition-based maintenance approaches resulting in dynamic maintenance planning as maintenance tasks are condition directed instead of scheduled or usage based. A proof of concept prototype for an aircraft operational readiness simulator (OR-SIM has been developed for the Canadian Forces CH-146 Griffon helicopter. The simulator provides a synthetic environment to forecast and assess the ability of a fleet, squadron, or aircraft to achieve desired flying rates and the capability of the sustainment systems to respond to the resultant demands. The prototype was used to assess several typical scenarios including adjustment of preventative maintenance schedules including impact of condition-based maintenance, variation of the annual flying rate, and investigation of deployment options. This paper provides an overview of the OR-SIM concept, prototype model, and sample investigations and a discussion of the benefits of such an operational readiness simulator.
Power consumption optimization strategy for wireless networks
DEFF Research Database (Denmark)
Cornean, Horia; Kumar, Sanjay; Marchetti, Nicola
2011-01-01
in order to reduce the total power consumption in a multi cellular network. We present an algorithm for power optimization under no interference and in presence of interference conditions, targeting to maximize the network capacity. The convergence of the algorithm is guaranteed if the interference...
Optimal Protection Coordination for Microgrid under Different Operating Modes
Directory of Open Access Journals (Sweden)
Ming-Ta Yang
2013-01-01
Full Text Available Significant consequences result when a microgrid is connected to a distribution system. This study discusses the impacts of bolted three-phase faults and bolted single line-to-ground faults on the protection coordination of a distribution system connected by a microgrid which operates in utility-only mode or in grid-connected mode. The power system simulation software is used to build the test system. The linear programming method is applied to optimize the coordination of relays, and the relays coordination simulation software is used to verify if the coordination time intervals (CTIs of the primary/backup relay pairs are adequate. In addition, this study also proposes a relays protection coordination strategy when the microgrid operates in islanding mode during a utility power outage. Because conventional CO/LCO relays are not capable of detecting high impedance fault, intelligent electrical device (IED combined with wavelet transformer and neural network is proposed to accurately detect high impedance fault and identify the fault phase.
An Equivalent Emission Minimization Strategy for Causal Optimal Control of Diesel Engines
Directory of Open Access Journals (Sweden)
Stephan Zentner
2014-02-01
Full Text Available One of the main challenges during the development of operating strategies for modern diesel engines is the reduction of the CO2 emissions, while complying with ever more stringent limits for the pollutant emissions. The inherent trade-off between the emissions of CO2 and pollutants renders a simultaneous reduction difficult. Therefore, an optimal operating strategy is sought that yields minimal CO2 emissions, while holding the cumulative pollutant emissions at the allowed level. Such an operating strategy can be obtained offline by solving a constrained optimal control problem. However, the final-value constraint on the cumulated pollutant emissions prevents this approach from being adopted for causal control. This paper proposes a framework for causal optimal control of diesel engines. The optimization problem can be solved online when the constrained minimization of the CO2 emissions is reformulated as an unconstrained minimization of the CO2 emissions and the weighted pollutant emissions (i.e., equivalent emissions. However, the weighting factors are not known a priori. A method for the online calculation of these weighting factors is proposed. It is based on the Hamilton–Jacobi–Bellman (HJB equation and a physically motivated approximation of the optimal cost-to-go. A case study shows that the causal control strategy defined by the online calculation of the equivalence factor and the minimization of the equivalent emissions is only slightly inferior to the non-causal offline optimization, while being applicable to online control.
Optimal Dynamic Advertising Strategy Under Age-Specific Market Segmentation
Krastev, Vladimir
2011-12-01
We consider the model proposed by Faggian and Grosset for determining the advertising efforts and goodwill in the long run of a company under age segmentation of consumers. Reducing this model to optimal control sub problems we find the optimal advertising strategy and goodwill.
Existence of optimal consumption strategies in markets with longevity risk
de Kort, Jan; Vellekoop, M.H.
2017-01-01
Survival bonds are financial instruments with a payoff that depends on human mortality rates. In markets that contain such bonds, agents optimizing expected utility of consumption and terminal wealth can mitigate their longevity risk. To examine how this influences optimal portfolio strategies and c
Synthesis of Optimal Strategies Using HyTech
DEFF Research Database (Denmark)
Bouyer, Patricia; Cassez, Franck; Larsen, Kim Guldstrand
2005-01-01
Priced timed (game) automata extend timed (game) automata with costs on both locations and transitions. The problem of synthesizing an optimal winning strategy for a priced timed game under some hypotheses has been shown decidable in [P. Bouyer, F. Cassez, E. Fleury, and K.G. Larsen. Optimal...
A hybrid genetic algorithm based on mutative scale chaos optimization strategy
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
In order to avoid such problems as low convergent speed and local optimal solution in simple genetic algorithms, a new hybrid genetic algorithm is proposed. In this algorithm, a mutative scale chaos optimization strategy is operated on the population after a genetic operation. And according to the searching process, the searching space of the optimal variables is gradually diminished and the regulating coefficient of the secondary searching process is gradually changed which will lead to the quick evolution of the population. The algorithm has such advantages as fast search, precise results and convenient using etc. The simulation results show that the performance of the method is better than that of simple genetic algorithms.
Optimizing Traffic Operation in Designing Specific Upgrades
Directory of Open Access Journals (Sweden)
Ebrahim Sangsefidi
2015-01-01
Full Text Available Transport forms one of the primary needs in all categories of the population in modern society; it is of paramount concern for traffic engineers, transport planners, and policy makers to understand and evaluate the quality of service being provided by the transport facilities designed by them. This paper presents an investigation in profile geometric design and traffic flow operation on two-lane two-way highways and provides analyses that will help in a better understanding of traffic operation on these facilities to select the optimum profile configuration. The effects of influencing parameters consisting of grade, length of grade, traffic composition, and traffic volume are evaluated and finally a systematic procedure to evaluate flow rate under the base condition is presented. Finally, based on these achievements an algorithm is introduced to select optimum Finished Ground of profile view. Results show that the percentage of heavy vehicles has a contributing effect on traffic operation so that the optimum profile configuration is incredibly affected by this factor. Source data have been obtained from Highway Capacity Manual (HCM as a pioneer document in respect of quantifying the concept of capacity for a transport facility.
Health benefit modelling and optimization of vehicular pollution control strategies
Sonawane, Nayan V.; Patil, Rashmi S.; Sethi, Virendra
2012-12-01
This study asserts that the evaluation of pollution reduction strategies should be approached on the basis of health benefits. The framework presented could be used for decision making on the basis of cost effectiveness when the strategies are applied concurrently. Several vehicular pollution control strategies have been proposed in literature for effective management of urban air pollution. The effectiveness of these strategies has been mostly studied as a one at a time approach on the basis of change in pollution concentration. The adequacy and practicality of such an approach is studied in the present work. Also, the assessment of respective benefits of these strategies has been carried out when they are implemented simultaneously. An integrated model has been developed which can be used as a tool for optimal prioritization of various pollution management strategies. The model estimates health benefits associated with specific control strategies. ISC-AERMOD View has been used to provide the cause-effect relation between control options and change in ambient air quality. BenMAP, developed by U.S. EPA, has been applied for estimation of health and economic benefits associated with various management strategies. Valuation of health benefits has been done for impact indicators of premature mortality, hospital admissions and respiratory syndrome. An optimization model has been developed to maximize overall social benefits with determination of optimized percentage implementations for multiple strategies. The model has been applied for sub-urban region of Mumbai city for vehicular sector. Several control scenarios have been considered like revised emission standards, electric, CNG, LPG and hybrid vehicles. Reduction in concentration and resultant health benefits for the pollutants CO, NOx and particulate matter are estimated for different control scenarios. Finally, an optimization model has been applied to determine optimized percentage implementation of specific
Mesh refinement strategy for optimal control problems
Paiva, Luis Tiago; Fontes, Fernando,
2013-01-01
International audience; Direct methods are becoming the most used technique to solve nonlinear optimal control problems. Regular time meshes having equidistant spacing are frequently used. However, in some cases these meshes cannot cope accurately with nonlinear behavior. One way to improve the solution is to select a new mesh with a greater number of nodes. Another way, involves adaptive mesh refinement. In this case, the mesh nodes have non equidistant spacing which allow a non uniform node...
DEFF Research Database (Denmark)
Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte
2011-01-01
operation strategy for a Plug-In Electric Vehicle (PEV) in relation to the hourly electricity price in order to achieve minimum energy costs of the PEV. The western Danish power system, which is currently the grid area in the world that has the largest share of wind power in its generation profiles and may...... represent the future of electricity markets in some ways, is chosen as the studied power system in this paper. The impact of the optimal operation strategy for electric vehicles together with the optimal load response to spot market price on the distribution power system with high wind power penetrations......Since the hourly spot market price is available one day ahead in Denmark, the electricity price could be transferred to the consumers and they may make some optimal charge and discharge schedules for their electric vehicles in order to minimize their energy costs. This paper presents an optimal...
DEFF Research Database (Denmark)
Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte
2011-01-01
Since the hourly spot market price is available one day ahead in Denmark, the electricity price could be transferred to the consumers and they may make some optimal charge and discharge schedules for their electric vehicles in order to minimize their energy costs. This paper presents an optimal...... operation strategy for a Plug-In Electric Vehicle (PEV) in relation to the hourly electricity price in order to achieve minimum energy costs of the PEV. The western Danish power system, which is currently the grid area in the world that has the largest share of wind power in its generation profiles and may...... represent the future of electricity markets in some ways, is chosen as the studied power system in this paper. The impact of the optimal operation strategy for electric vehicles together with the optimal load response to spot market price on the distribution power system with high wind power penetrations...
Discuss Optimal Approaches to Learning Strategy Instruction for EFL Learners
Institute of Scientific and Technical Information of China (English)
邢菊如
2009-01-01
Numerous research studies reveal that learning strategies have played an important role in language learning processes.This paper explores as English teachers.can we impmve students' language proficiency by giving them optimal learning strategy instruction and what approaches are most effective and efficient?
Optimizing the HLT Buffer Strategy with Monte Carlo Simulations
AUTHOR|(CDS)2266763
2017-01-01
This project aims to optimize the strategy of utilizing the disk buffer for the High Level Trigger (HLT) of the LHCb experiment with the help of Monte-Carlo simulations. A method is developed, which simulates the Event Filter Farm (EFF) -- a computing cluster for the High Level Trigger -- as a compound of nodes with different performance properties. In this way, the behavior of the computing farm can be analyzed at a deeper level than before. It is demonstrated that the current operating strategy might be improved when data taking is reaching a mid-year scheduled stop or the year-end technical stop. The processing time of the buffered data can be lowered by distributing the detector data according to the processing power of the nodes instead of the relative disk size as long as the occupancy level of the buffer is low enough. Moreover, this ensures that data taken and stored on the buffer at the same time is processed by different nodes nearly simultaneously, which reduces load on the infrastructure.
Optimal Portfolio Strategy under Rolling Economic Maximum Drawdown Constraints
Xiaojian Yu; Siyu Xie; Weijun Xu
2014-01-01
This paper deals with the problem of optimal portfolio strategy under the constraints of rolling economic maximum drawdown. A more practical strategy is developed by using rolling Sharpe ratio in computing the allocation proportion in contrast to existing models. Besides, another novel strategy named “REDP strategy” is further proposed, which replaces the rolling economic drawdown of the portfolio with the rolling economic drawdown of the risky asset. The simulation tests prove that REDP stra...
Institute of Scientific and Technical Information of China (English)
曾顺奇; 文福拴; 薛禹胜; 吴文可; 林振智; 戴彦
2011-01-01
The network reconfiguration procedure after a complete blackout or a local outage usually lasts a relatively long period of time and involves a lot of factors.It can be formulated as a combinatorial optimization problem with multiple variables and objectives.A chance constrained programming（CCP） model for network reconfiguration scheme optimization is developed with the operating time uncertainty taken into account.The node number of the restarted generators and the benefit from the restored loads are taken as the returns from the restoration scheme and the network reconfiguration scheme of maximum returns is searched in the process of network reconfiguration.Then a modified genetic algorithm considering the characteristics of the network reconfiguration scheme optimization problem is proposed.Finally,a sample power system is adopted to demonstrate the essential features of the model and method developed.%电力系统大停电后的网架重构阶段历时较长,涉及因素众多,是一个多目标、多变量的组合优化问题。发展了计及恢复操作时间不确定性的网架重构方案优化的机会约束规划模型。该模型以恢复的发电节点数和负荷恢复收益作为节点收益,搜索网架重构过程中收益最大的网架重构方案。之后,针对网架重构问题的特点,提出了一种改进的遗传算法求解方法。最后,通过算例说明了所述模型和方法的基本特征。
Synergy optimization and operation management on syndicate complementary knowledge cooperation
Tu, Kai-Jan
2014-10-01
The number of multi enterprises knowledge cooperation has grown steadily, as a result of global innovation competitions. I have conducted research based on optimization and operation studies in this article, and gained the conclusion that synergy management is effective means to break through various management barriers and solve cooperation's chaotic systems. Enterprises must communicate system vision and access complementary knowledge. These are crucial considerations for enterprises to exert their optimization and operation knowledge cooperation synergy to meet global marketing challenges.
Optimal scope of supply chain network & operations design
Ma, N.
2014-01-01
The increasingly complex supply chain networks and operations call for the development of decision support systems and optimization techniques that take a holistic view of supply chain issues and provide support for integrated decision-making. The economic impacts of optimized supply chain are signi
Optimal scope of supply chain network & operations design
Ma, N.
2014-01-01
The increasingly complex supply chain networks and operations call for the development of decision support systems and optimization techniques that take a holistic view of supply chain issues and provide support for integrated decision-making. The economic impacts of optimized supply chain are signi
Concrete Plant Operations Optimization Using Combined Simulation and Genetic Algorithms
Cao, Ming; Lu, Ming; Zhang, Jian-Ping
2004-01-01
This work presents a new approach for concrete plant operations optimization by combining a ready mixed concrete (RMC) production simulation tool (called HKCONSIM) with a genetic algorithm (GA) based optimization procedure. A revamped HKCONSIM computer system can be used to automate the simulation m
Concrete Plant Operations Optimization Using Combined Simulation and Genetic Algorithms
Cao, Ming; Lu, Ming; Zhang, Jian-Ping
2004-01-01
This work presents a new approach for concrete plant operations optimization by combining a ready mixed concrete (RMC) production simulation tool (called HKCONSIM) with a genetic algorithm (GA) based optimization procedure. A revamped HKCONSIM computer system can be used to automate the simulation m
Optimization of operational aircraft parameters Reducing Noise Emission
Abdallah, Lina; Khardi, Salah
2008-01-01
The objective of this paper is to develop a model and a minimization method to provide flight path optimums reducing aircraft noise in the vicinity of airports. Optimization algorithm has solved a complex optimal control problem, and generates flight paths minimizing aircraft noise levels. Operational and safety constraints have been considered and their limits satisfied. Results are here presented and discussed.
Concrete Plant Operations Optimization Using Combined Simulation and Genetic Algorithms
Cao, Ming; Lu, Ming; Zhang, Jian-Ping
2004-01-01
This work presents a new approach for concrete plant operations optimization by combining a ready mixed concrete (RMC) production simulation tool (called HKCONSIM) with a genetic algorithm (GA) based optimization procedure. A revamped HKCONSIM computer system can be used to automate the simulation
Marketing strategy of a selected tour operator
Lejčková, Lucie
2009-01-01
The objective of the thesis "Marketing strategy of a selected tour operator" is to get acquainted with the marketing strategy of MILE tour operator aiming to propose possible improvements based on carried analysis. The first part includes general theories of marketing and its specifics in tourism. The second part is the application of this theory into practice, starting with the basic characteristics of MILE tour operator, followed by analysis of its standing in the tourism market including a...
On Global Optimal Sailplane Flight Strategy
Sander, G. J.; Litt, F. X.
1979-01-01
The derivation and interpretation of the necessary conditions that a sailplane cross-country flight has to satisfy to achieve the maximum global flight speed is considered. Simple rules are obtained for two specific meteorological models. The first one uses concentrated lifts of various strengths and unequal distance. The second one takes into account finite, nonuniform space amplitudes for the lifts and allows, therefore, for dolphin style flight. In both models, altitude constraints consisting of upper and lower limits are shown to be essential to model realistic problems. Numerical examples illustrate the difference with existing techniques based on local optimality conditions.
Optimal hysteretic control for a BMAP/SM/1/N queue with two operation modes
Directory of Open Access Journals (Sweden)
Alexander N. Dudin
2000-01-01
Full Text Available We consider BMAP/SM/1 type queueing system with finite buffer of size N. The system has two operation modes, which are characterized by the matrix generating function of BMAP-input, the kernel of the semi-Markovian service process, and utilization cost. An algorithm for determining the optimal hysteresis strategy is presented.
Particle Swarm Optimization with Genetic Operators for Vehicle Routing Problem
Directory of Open Access Journals (Sweden)
P. V. PURANIK
2012-07-01
Full Text Available Vehicle Routing Problem (VRP is to find shortest route thereby minimizing total cost. VRP is a NP-hard and Combinatorial optimization problem. Such problems increase exponentially with the problem size. Various derivative based optimization techniques are employed for optimization. Derivative based optimization techniques are difficult to evaluate. Therefore parallel search algorithm emerged to solve VRP. In this work, a particle swarm optimization (PSO algorithm and Genetic algorithm (GA with crossover and mutation operator are applied to two typical functions to deal with the problem of VRP efficiently using MATLAB software. Before solving VRP, optimization of functions using PSO and GA are checked. In this paper capacitate VRP with time window (CVRPTW is proposed. The computational result shows generation of input for VRP, optimization of Rastrigin function, Rosenbrock function using PSO and GA.
Optimality of Spatially Inhomogeneous Search Strategies.
Schwarz, Karsten; Schröder, Yannick; Qu, Bin; Hoth, Markus; Rieger, Heiko
2016-08-05
We consider random search processes alternating stochastically between diffusion and ballistic motion, in which the distribution function of ballistic motion directions varies from point to point in space. The specific space dependence of the directional distribution together with the switching rates between the two modes of motion establishes a spatially inhomogeneous search strategy. We show that the mean first passage times for several standard search problems-narrow escape, reaction partner finding, reaction escape-can be minimized with a directional distribution that is reminiscent of the spatial organization of the cytoskeleton filaments of cells with a centrosome: radial ballistic transport from the center to the periphery and back, and ballistic transport in random directions within a concentric shell of thickness Δ_{opt} along the domain boundary. The results suggest that living cells realize efficient search strategies for various intracellular transport problems economically through a spatial cytoskeleton organization that involves radial microtubules in the central region and only a narrow actin cortex rather than a cell body filled with randomly oriented actin filaments.
Optimality of Spatially Inhomogeneous Search Strategies
Schwarz, Karsten; Schröder, Yannick; Qu, Bin; Hoth, Markus; Rieger, Heiko
2016-08-01
We consider random search processes alternating stochastically between diffusion and ballistic motion, in which the distribution function of ballistic motion directions varies from point to point in space. The specific space dependence of the directional distribution together with the switching rates between the two modes of motion establishes a spatially inhomogeneous search strategy. We show that the mean first passage times for several standard search problems—narrow escape, reaction partner finding, reaction escape—can be minimized with a directional distribution that is reminiscent of the spatial organization of the cytoskeleton filaments of cells with a centrosome: radial ballistic transport from the center to the periphery and back, and ballistic transport in random directions within a concentric shell of thickness Δopt along the domain boundary. The results suggest that living cells realize efficient search strategies for various intracellular transport problems economically through a spatial cytoskeleton organization that involves radial microtubules in the central region and only a narrow actin cortex rather than a cell body filled with randomly oriented actin filaments.
Directory of Open Access Journals (Sweden)
Jingxian Hao
2016-11-01
Full Text Available The rule-based logic threshold control strategy has been frequently used in energy management strategies for hybrid electric vehicles (HEVs owing to its convenience in adjusting parameters, real-time performance, stability, and robustness. However, the logic threshold control parameters cannot usually ensure the best vehicle performance at different driving cycles and conditions. For this reason, the optimization of key parameters is important to improve the fuel economy, dynamic performance, and drivability. In principle, this is a multiparameter nonlinear optimization problem. The logic threshold energy management strategy for an all-wheel-drive HEV is comprehensively analyzed and developed in this study. Seven key parameters to be optimized are extracted. The optimization model of key parameters is proposed from the perspective of fuel economy. The global optimization method, DIRECT algorithm, which has good real-time performance, low computational burden, rapid convergence, is selected to optimize the extracted key parameters globally. The results show that with the optimized parameters, the engine operates more at the high efficiency range resulting into a fuel savings of 7% compared with non-optimized parameters. The proposed method can provide guidance for calibrating the parameters of the vehicle energy management strategy from the perspective of fuel economy.
Vector optimization and monotone operators via convex duality recent advances
Grad, Sorin-Mihai
2014-01-01
This book investigates several duality approaches for vector optimization problems, while also comparing them. Special attention is paid to duality for linear vector optimization problems, for which a vector dual that avoids the shortcomings of the classical ones is proposed. Moreover, the book addresses different efficiency concepts for vector optimization problems. Among the problems that appear when the framework is generalized by considering set-valued functions, an increasing interest is generated by those involving monotone operators, especially now that new methods for approaching them by means of convex analysis have been developed. Following this path, the book provides several results on different properties of sums of monotone operators.
The Development of an Optimal Control Strategy for a Series Hydraulic Hybrid Vehicle
Directory of Open Access Journals (Sweden)
Chih-Wei Hung
2016-03-01
Full Text Available In this work, a Truck Class II series hydraulic hybrid model is established. Dynamic Programming (DP methodology is applied to derive the optimal power-splitting factor for the hybrid system for preselected driving schedules. Implementable rules are derived by extracting the optimal trajectory features from a DP scheme. The system behaviors illustrate that the improved control strategy gives a highly effective operation region for the engine and high power density characteristics for the hydraulic components.
Optimal search strategies on complex networks
Di Patti, Francesca; Piazza, Francesco
2014-01-01
Complex networks are ubiquitous in nature and play a role of paramount importance in many contexts. Internet and the cyberworld, which permeate our everyday life, are self-organized hierarchical graphs. Urban traffic flows on intricate road networks, which impact both transportation design and epidemic control. In the brain, neurons are cabled through heterogeneous connections, which support the propagation of electric signals. In all these cases, the true challenge is to unveil the mechanisms through which specific dynamical features are modulated by the underlying topology of the network. Here, we consider agents randomly hopping along the links of a graph, with the additional possibility of performing long-range hops to randomly chosen disconnected nodes with a given probability. We show that an optimal combination of the two jump rules exists that maximises the efficiency of target search, the optimum reflecting the topology of the network.
Nickel-Cadmium Battery Operation Management Optimization Using Robust Design
Blosiu, Julian O.; Deligiannis, Frank; DiStefano, Salvador
1996-01-01
In recent years following several spacecraft battery anomalies, it was determined that managing the operational factors of NASA flight NiCd rechargeable battery was very important in order to maintain space flight battery nominal performance. The optimization of existing flight battery operational performance was viewed as something new for a Taguchi Methods application.
Optimization of energy planning strategies in municipalities
DEFF Research Database (Denmark)
Petersen, Jens-Phillip
The paper evaluates the current status of community energy planning in northern Europe via a review of literature, practice and the performance of a barrier analysis for successful community energy planning. Main findings of the paper are that current community energy planning lacks a systematic...... approach, suffers from insufficient information, tools and resources. Municipalities are often unable to take on a steering role in community energy planning. To overcome these barriers and guide municipalities in the pre-project phase, a decision-support methodology, based on community energy profiles...... (CEP), is presented. The methodology was applied in a case study in Germany. With CEPs, a possibility to merge qualitative data from local settings into generic energy modelling is shown, which could contribute to improved community energy strategies....
2009-01-01
This paper describes the application of model-based predictive control (MPC) techniques to the flow management in large-scale drinking water networks including a telemetry/telecontrol system. MPC technique is used to generate flow control strategies from the sources to the consumer areas to meet future demands, optimizing performance indexes associated to operational goals such as economic cost, network safety volumes and flow control stability. The designed management strategies are...
Optimal Portfolio Strategy under Rolling Economic Maximum Drawdown Constraints
Directory of Open Access Journals (Sweden)
Xiaojian Yu
2014-01-01
Full Text Available This paper deals with the problem of optimal portfolio strategy under the constraints of rolling economic maximum drawdown. A more practical strategy is developed by using rolling Sharpe ratio in computing the allocation proportion in contrast to existing models. Besides, another novel strategy named “REDP strategy” is further proposed, which replaces the rolling economic drawdown of the portfolio with the rolling economic drawdown of the risky asset. The simulation tests prove that REDP strategy can ensure the portfolio to satisfy the drawdown constraint and outperforms other strategies significantly. An empirical comparison research on the performances of different strategies is carried out by using the 23-year monthly data of SPTR, DJUBS, and 3-month T-bill. The investment cases of single risky asset and two risky assets are both studied in this paper. Empirical results indicate that the REDP strategy successfully controls the maximum drawdown within the given limit and performs best in both return and risk.
Optimal management strategies for placenta accreta.
Eller, A G; Porter, T F; Soisson, P; Silver, R M
2009-04-01
To determine which interventions for managing placenta accreta were associated with reduced maternal morbidity. Retrospective cohort study. Two tertiary care teaching hospitals in Utah. All identified cases of placenta accreta from 1996 to 2008. Cases of placenta accreta were identified using standard ICD-9 codes for placenta accreta, placenta praevia, and caesarean hysterectomy. Medical records were then abstracted for maternal medical history, hospital course, and maternal and neonatal outcomes. Maternal and neonatal complications were compared according to antenatal suspicion of accreta, indications for delivery, preoperative preparation, attempts at placental removal before hysterectomy, and hypogastric artery ligation. Early morbidity (prolonged maternal intensive care unit admission, large volume of blood transfusion, coagulopathy, ureteral injury, or early re-operation) and late morbidity (intra-abdominal infection, hospital re-admission, or need for delayed re-operation). Results Seventy-six cases of placenta accreta were identified. When accreta was suspected, scheduled caesarean hysterectomy without attempting placental removal was associated with a significantly reduced rate of early morbidity compared with cases in which placental removal was attempted (67 versus 36%, P=0.038). Women with preoperative bilateral ureteric stents had a lower incidence of early morbidity compared with women without stents (18 versus 55%, P=0.018). Hypogastric artery ligation did not reduce maternal morbidity. Scheduled caesarean hysterectomy with preoperative ureteric stent placement and avoiding attempted placental removal are associated with reduced maternal morbidity in women with suspected placenta accreta.
Directory of Open Access Journals (Sweden)
Zeyu Chen
2015-04-01
Full Text Available Plug-in hybrid electric vehicles (PHEVs have been recognized as one of the most promising vehicle categories nowadays due to their low fuel consumption and reduced emissions. Energy management is critical for improving the performance of PHEVs. This paper proposes an energy management approach based on a particle swarm optimization (PSO algorithm. The optimization objective is to minimize total energy cost (summation of oil and electricity from vehicle utilization. A main drawback of optimal strategies is that they can hardly be used in real-time control. In order to solve this problem, a rule-based strategy containing three operation modes is proposed first, and then the PSO algorithm is implemented on four threshold values in the presented rule-based strategy. The proposed strategy has been verified by the US06 driving cycle under the MATLAB/Simulink software environment. Two different driving cycles are adopted to evaluate the generalization ability of the proposed strategy. Simulation results indicate that the proposed PSO-based energy management method can achieve better energy efficiency compared with traditional blended strategies. Online control performance of the proposed approach has been demonstrated through a driver-in-the-loop real-time experiment.
Optimized Information Transmission Scheduling Strategy Oriented to Advanced Metering Infrastructure
Directory of Open Access Journals (Sweden)
Weiming Tong
2013-01-01
Full Text Available Advanced metering infrastructure (AMI is considered to be the first step in constructing smart grid. AMI allows customers to make real-time choices about power utilization and enables power utilities to increase the effectiveness of the regional power grids by managing demand load during peak times and reducing unneeded power generation. These initiatives rely heavily on the prompt information transmission inside AMI. Aiming at the information transmission problem, this paper researches the communication scheduling strategy in AMI at a macroscopic view. First, the information flow of AMI is analyzed, and the power users are classified into several grades by their importance. Then, the defect of conventional information transmission scheduling strategy is analyzed. On this basis, two optimized scheduling strategies are proposed. In the wide area, an optimized scheduling strategy based on user importance and time critical is proposed to guarantee the important power users’ information transmission being handled promptly. In the local area, an optimized scheduling strategy based on device and information importance and time critical is proposed to guarantee the important devices and information in AMI user end system being handled promptly. At last, the two optimized scheduling strategies are simulated. The simulation results show that they can effectively improve the real-time performance and reliability of AMI information transmission.
Optimal modes of operation of two idealized magnetohydrodynamic devices
Energy Technology Data Exchange (ETDEWEB)
Okulov, N.A.
1984-01-01
A conduction channel and a conduction cylinder, idealized devices, which model the operation of conduction magnetohydrodynamic (MGD) generators (pump) and magnetohydrodynamic propulsion devices, are examined. It is shown that it is sufficient to know the operational characteristics in the idle (kh.kh.) and short circuiting (KZ) modes alone in order to determine the operational characteristics of a conduction channel in the optimal mode, that is, in a mode of most complete energy conversion. The mode with which the required speed of movement is supported with minimal expenditures of energy is called the optimal mode of operation of a conduction cylinder. It is established that the characteristics of the corresponding optimal movement are expressed through the characteristics of the so called basis movements, whose number is one less than the number of electrodes.
Optimizing Long-Term Capital Planning for Special Operations Forces
2015-06-01
TERM CAPITAL PLANNING FOR SPECIAL OPERATIONS FORCES by Gretchen M. Radke June 2015 Thesis Advisor: Emily Craparo Co-Advisor: Jonathan Alt...REPORT TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE OPTIMIZING LONG-TERM CAPITAL PLANNING FOR SPECIAL OPERATIONS FORCES 5...words) The United States Special Operations Command (USSOCOM) J8 directorate is responsible for planning long-range capital expenditure for Special
Strategies for optimizing nitrogen use by ruminants
DEFF Research Database (Denmark)
Calsamiglia, S; Ferret, A; Reynolds, C K
2010-01-01
The efficiency of N utilization in ruminants is typically low (around 25%) and highly variable (10% to 40%) compared with the higher efficiency of other production animals. The low efficiency has implications for the production performance and environment. Many efforts have been devoted to improv......The efficiency of N utilization in ruminants is typically low (around 25%) and highly variable (10% to 40%) compared with the higher efficiency of other production animals. The low efficiency has implications for the production performance and environment. Many efforts have been devoted...... to improving the efficiency of N utilization in ruminants, and while major improvements in our understanding of N requirements and metabolism have been achieved, the overall efficiency remains low. In general, maximal efficiency of N utilization will only occur at the expense of some losses in production...... performance. However, optimal production and N utilization may be achieved through the understanding of the key mechanisms involved in the control of N metabolism. Key factors in the rumen include the efficiency of N capture in the rumen (grams of bacterial N per grams of rumen available N...
DEFF Research Database (Denmark)
Anvari-Moghaddam, Amjad; Dragicevic, Tomislav; Meng, Lexuan
2016-01-01
for the proposed plan is derived based on the solution from a mixed-integer nonlinear programming (MINLP) problem. Simulation results showed that including well-sized energy storage options together with optimal operation management of generating units can improve the economic operation of the test system while...... problems to shipboard systems where some means of generation and storage are also schedulable. First, the question of whether or how much energy storage to include into the system is addressed. Both the storage power rating in MW and the capacity in MWh are optimized. Then, optimal operating strategy......Next generation power management at all scales is highly relying on the efficient scheduling and operation of different energy sources to maximize efficiency and utility. The ability to schedule and modulate the energy storage options within energy systems can also lead to more efficient use...
An Optimal Charging Strategy for PV-Based Battery Swapping Stations in a DC Distribution System
Directory of Open Access Journals (Sweden)
Shengjun Wu
2017-01-01
Full Text Available Photovoltaic- (PV- based battery swapping stations (BSSs utilize a typical integration of consumable renewable resources to supply power for electric vehicles (EVs. The charging strategy of PV-based BSSs directly influences the availability, cost, and carbon emissions of the swapping service. This paper proposes an optimal charging strategy to improve the self-consumption of PV-generated power and service availability while considering forecast errors. First, we introduce the typical structure and operation model of PV-based BSSs. Second, three indexes are presented to evaluate operational performance. Then, a particle swarm optimization (PSO algorithm is developed to calculate the optimal charging power and to minimize the charging cost for each time slot. The proposed charging strategy helps decrease the impact of forecast uncertainties on the availability of the battery swapping service. Finally, a day-ahead operation schedule, a real-time decision-making strategy, and the proposed PSO charging strategy for PV-based BSSs are simulated in a case study. The simulation results show that the proposed strategy can effectively improve the self-consumption of PV-generated power and reduce charging cost.
Strategies for Global Optimization of Temporal Preferences
Morris, Paul; Morris, Robert; Khatib, Lina; Ramakrishnan, Sailesh
2004-01-01
A temporal reasoning problem can often be naturally characterized as a collection of constraints with associated local preferences for times that make up the admissible values for those constraints. Globally preferred solutions to such problems emerge as a result of well-defined operations that compose and order temporal assignments. The overall objective of this work is a characterization of different notions of global preference, and to identify tractable sub-classes of temporal reasoning problems incorporating these notions. This paper extends previous results by refining the class of useful notions of global temporal preference that are associated with problems that admit of tractable solution techniques. This paper also answers the hitherto open question of whether problems that seek solutions that are globally preferred from a Utilitarian criterion for global preference can be found tractably.
Optimization of Secondary Concentrators with the Continuous Information Entropy Strategy
Schmidt, Tobias Christian; Ries, Harald
2010-10-01
In this contribution, a method for global optimization of noisy functions, the Continuous Information Entropy Strategy (CIES), is explained and its applicability for the optimization of solar concentrators is shown. The CIES is efficient because all decisions made during optimizations are based on criteria that are derived from the concept of information entropy. Two secondary concentrators have been optimized with the CIES. The optimized secondary concentrators convert circular light distributions of round focal spots to square light distributions to match with the shape of square PV cells. The secondary concentrators are highly efficient and have geometrical concentration ratios of 2.25 and 8 respectively. Part of this material has been published in: T. C. Schmidt, "Information Entropy-Based Decision Making in Optimization", Ph.D. Thesis, Philipps University Marburg, 2010.
Geography program, design, structure and operational strategy
Alexander, R. H.
1970-01-01
The geography program is designed to move systematically toward a capability to increase remote sensing data into operational systems for monitoring land use and related environmental change. The problems of environmental imbalance arising from rapid urbanization and other dramatic changes in land use are considered. These overall problems translate into working level problems of establishing the validity of various sensor-data combinations that will best obtain the regional land use and environmental information. The goal, to better understand, predict, and assist policy makers to regulate urban and regional land use changes resulting from population growth and technological advancement, is put forth.
Optimization model of vaccination strategy for dengue transmission
Widayani, H.; Kallista, M.; Nuraini, N.; Sari, M. Y.
2014-02-01
Dengue fever is emerging tropical and subtropical disease caused by dengue virus infection. The vaccination should be done as a prevention of epidemic in population. The host-vector model are modified with consider a vaccination factor to prevent the occurrence of epidemic dengue in a population. An optimal vaccination strategy using non-linear objective function was proposed. The genetic algorithm programming techniques are combined with fourth-order Runge-Kutta method to construct the optimal vaccination. In this paper, the appropriate vaccination strategy by using the optimal minimum cost function which can reduce the number of epidemic was analyzed. The numerical simulation for some specific cases of vaccination strategy is shown.
Optimal design of coordination control strategy for distributed generation system
Institute of Scientific and Technical Information of China (English)
WANG Ai-hua; Norapon Kanjanapadit
2009-01-01
This paper presents a novel design procedure for optimizing the power distribution strategy in distributed generation system. A coordinating controller, responsible to distribute the total load power request among multiple DG units, is suggested based on the conception of hierarchical control structure in the dynamic system.The optimal control problem was formulated as a nonlinear optimization problem subject to set of constraints.The resulting problem was solved using the Kutm-Tucker method. Computer simulation results demonstrate that the proposed method can provide better efficiency in terms of reducing total costs compared to existing methods.In addition, the proposed optimal load distribution strategy can be easily implemented in real-time thanks to the simplicity of closed-form solutions.
Optimal Watermark Embedding and Detection Strategies Under Limited Detection Resources
Merhav, Neri
2007-01-01
An information-theoretic approach is proposed to watermark embedding and detection under limited detector resources. First, we consider the attack-free scenario under which asymptotically optimal decision regions in the Neyman-Pearson sense are proposed, along with the optimal embedding rule. Later, we explore the case of zero-mean i.i.d. Gaussian covertext distribution with unknown variance under the attack-free scenario. For this case, we propose a lower bound on the exponential decay rate of the false-negative probability and prove that the optimal embedding and detecting strategy is superior to the customary linear, additive embedding strategy in the exponential sense. Finally, these results are extended to the case of memoryless attacks and general worst case attacks. Optimal decision regions and embedding rules are offered, and the worst attack channel is identified.
Operation optimization of distributed generation using artificial intelligent techniques
Directory of Open Access Journals (Sweden)
Mahmoud H. Elkazaz
2016-06-01
Full Text Available Future smart grids will require an observable, controllable and flexible network architecture for reliable and efficient energy delivery. The use of artificial intelligence and advanced communication technologies is essential in building a fully automated system. This paper introduces a new technique for online optimal operation of distributed generation (DG resources, i.e. a hybrid fuel cell (FC and photovoltaic (PV system for residential applications. The proposed technique aims to minimize the total daily operating cost of a group of residential homes by managing the operation of embedded DG units remotely from a control centre. The target is formed as an objective function that is solved using genetic algorithm (GA optimization technique. The optimal settings of the DG units obtained from the optimization process are sent to each DG unit through a fully automated system. The results show that the proposed technique succeeded in defining the optimal operating points of the DGs that affect directly the total operating cost of the entire system.
Balanced Sourcing As An Important Attribute Of Operations Strategy ...
African Journals Online (AJOL)
Balanced Sourcing As An Important Attribute Of Operations Strategy: Reality Or Myth ... Today's business context is more complex than the environment in the past due ... have serious challenges pertaining to the sustainability of their positions.
Optimal control strategies for deficit irrigation systems under different climate conditions
Schuetze, Niels; Wagner, Michael
2017-04-01
In this contribution, the suitability of different control strategies for the operation of irrigation systems under limited water and different climate conditions is investigated. To treat the climate uncertainty within a simulation optimization framework for irrigation management we formulated a probabilistic framework that is based on Monte Carlo simulations. Thus, results show which control strategy can ensure food security since higher quantiles (90% and above) are of interest. This study also demonstrates the efficiency of a stack-ordering technique for generating high productive irrigation schedules which is based on statistically appropriate sample sizes and a reliable optimal management.
NEW OPTIMAL LARGE ANGLE MANEUVER STRATEGY FOR SINGLE FLEXIBLE LINK
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
A component synthesis vibration suppression (CSVS) method for flexible structures is put forward. It can eliminate any unwanted orders of flexible vibration modes while achieves desired rigid motion. This method has robustness to uncertainty of frequency, which makes it practical in engineering. Several time optimal and time-fuel optimal control strategies are designed for a kind of single flexible link. Simulation results validate the feasibility of our method.
Optimal Control Strategies in Delayed Sharing Information Structures
Nayyar, Ashutosh; Teneketzis, Demosthenis
2010-01-01
The $n$-step delayed sharing information structure is investigated. This information structure comprises of $K$ controllers that share their information with a delay of $n$ time steps. This information structure is a link between the classical information structure, where information is shared perfectly between the controllers, and a non-classical information structure, where there is no "lateral" sharing of information among the controllers. Structural results for optimal control strategies for systems with such information structures are presented. A sequential methodology for finding the optimal strategies is also derived. The solution approach provides an insight for identifying structural results and sequential decomposition for general decentralized stochastic control problems.
Fuzzy Control Strategies in Human Operator and Sport Modeling
Ivancevic, Tijana T; Markovic, Sasa
2009-01-01
The motivation behind mathematically modeling the human operator is to help explain the response characteristics of the complex dynamical system including the human manual controller. In this paper, we present two different fuzzy logic strategies for human operator and sport modeling: fixed fuzzy-logic inference control and adaptive fuzzy-logic control, including neuro-fuzzy-fractal control. As an application of the presented fuzzy strategies, we present a fuzzy-control based tennis simulator.
Optimization Under Uncertainty for Wake Steering Strategies: Preprint
Energy Technology Data Exchange (ETDEWEB)
Quick, Julian [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Annoni, Jennifer [National Renewable Energy Laboratory (NREL), Golden, CO (United States); King, Ryan N [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dykes, Katherine L [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Fleming, Paul A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ning, Andrew [Brigham Young University
2017-05-01
Wind turbines in a wind power plant experience significant power losses because of aerodynamic interactions between turbines. One control strategy to reduce these losses is known as 'wake steering,' in which upstream turbines are yawed to direct wakes away from downstream turbines. Previous wake steering research has assumed perfect information, however, there can be significant uncertainty in many aspects of the problem, including wind inflow and various turbine measurements. Uncertainty has significant implications for performance of wake steering strategies. Consequently, the authors formulate and solve an optimization under uncertainty (OUU) problem for finding optimal wake steering strategies in the presence of yaw angle uncertainty. The OUU wake steering strategy is demonstrated on a two-turbine test case and on the utility-scale, offshore Princess Amalia Wind Farm. When we accounted for yaw angle uncertainty in the Princess Amalia Wind Farm case, inflow-direction-specific OUU solutions produced between 0% and 1.4% more power than the deterministically optimized steering strategies, resulting in an overall annual average improvement of 0.2%. More importantly, the deterministic optimization is expected to perform worse and with more downside risk than the OUU result when realistic uncertainty is taken into account. Additionally, the OUU solution produces fewer extreme yaw situations than the deterministic solution.
Seasonal-Scale Optimization of Conventional Hydropower Operations in the Upper Colorado System
Bier, A.; Villa, D.; Sun, A.; Lowry, T. S.; Barco, J.
2011-12-01
Sandia National Laboratories is developing the Hydropower Seasonal Concurrent Optimization for Power and the Environment (Hydro-SCOPE) tool to examine basin-wide conventional hydropower operations at seasonal time scales. This tool is part of an integrated, multi-laboratory project designed to explore different aspects of optimizing conventional hydropower operations. The Hydro-SCOPE tool couples a one-dimensional reservoir model with a river routing model to simulate hydrology and water quality. An optimization engine wraps around this model framework to solve for long-term operational strategies that best meet the specific objectives of the hydrologic system while honoring operational and environmental constraints. The optimization routines are provided by Sandia's open source DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) software. Hydro-SCOPE allows for multi-objective optimization, which can be used to gain insight into the trade-offs that must be made between objectives. The Hydro-SCOPE tool is being applied to the Upper Colorado Basin hydrologic system. This system contains six reservoirs, each with its own set of objectives (such as maximizing revenue, optimizing environmental indicators, meeting water use needs, or other objectives) and constraints. This leads to a large optimization problem with strong connectedness between objectives. The systems-level approach used by the Hydro-SCOPE tool allows simultaneous analysis of these objectives, as well as understanding of potential trade-offs related to different objectives and operating strategies. The seasonal-scale tool will be tightly integrated with the other components of this project, which examine day-ahead and real-time planning, environmental performance, hydrologic forecasting, and plant efficiency.
Formulation of Higher Education Institutional Strategy Using Operational Research Approaches
Labib, Ashraf; Read, Martin; Gladstone-Millar, Charlotte; Tonge, Richard; Smith, David
2014-01-01
In this paper a framework is proposed for the formulation of a higher education institutional (HEI) strategy. This work provides a practical example, through a case study, to demonstrate how the proposed framework can be applied to the issue of formulation of HEI strategy. The proposed hybrid model is based on two operational research…
Levels of Availability of a Formal Operational Strategy.
Stone, C. Addison; Day, Mary Carol
1978-01-01
A modified version of Inhelder's and Piaget's bending-rods task was administered twice in succession to 9-, 11-, and 13-year-olds. Subjects were then categorized as spontaneous, latent, or nonusers of the formal operational control-of-variables strategy according to whether they used the strategy on the first, second, or neither administration.…
Formulation of Higher Education Institutional Strategy Using Operational Research Approaches
Labib, Ashraf; Read, Martin; Gladstone-Millar, Charlotte; Tonge, Richard; Smith, David
2014-01-01
In this paper a framework is proposed for the formulation of a higher education institutional (HEI) strategy. This work provides a practical example, through a case study, to demonstrate how the proposed framework can be applied to the issue of formulation of HEI strategy. The proposed hybrid model is based on two operational research…
A Swarm Optimization Based Power Aware Clustering Strategy for WSNs
Directory of Open Access Journals (Sweden)
Harendra S. Jangwan
2017-02-01
Full Text Available The technique of division of a wireless sensor network (WSN into clusters has proved to most suitable for the reliable data communication inside the network. This approach also improves the throughput of the system along with other attributes such as rate of delivering data packet to the base station (BS and overall energy dissipation of the sensor nodes in the network. This in turn results in the increased network lifetime. As the sensor nodes are operated by battery or some other source, this introduces a constraint in energy resource. Therefore, there is a strong need to develop a novel approach to overcome this constraint, since this phenomenon leads to the degradation of the network. The swarm intelligence approach is able to cope with all such pitfalls of WSNs. In this paper, we have presented a cluster-head (CH selection technique which is based on swarm optimization with the main aim to increase the overall network lifetime. The proposed approach gives higher effects with regards to power utilization of nodes, data packets received at BS and stability period, and for this reason serves to be a higher performer as compared to Stable Election Protocol (SEP and Enhance Threshold Sensitive Stable Election Protocol(ETSSEP. MATLAB simulation outcomes exhibit that the proposed clustering strategy outperforms the SEP and ETSSEP with regards to the above noted attributes.
Solving Optimal Broadcasting Strategy in Metropolitan MANETs Using MOCELL Algorithm
Directory of Open Access Journals (Sweden)
M. Ghonamy
2010-09-01
Full Text Available Mobile ad-hoc networks (MANETs are a set of communicating devices that are able to spontaneously interconnect without any pre-existing infrastructure. In such a scenario, broadcasting becomes very important to the existence and the operation of this network. The process of optimizing the broadcast strategy of MANETs is a multi-objective problem with three objectives: (1 reaching as many stations as possible, (2 minimizing the network utilization and (3 reducing the broadcasting duration. The main contribution of this paper is that it tackles this problem by using multi-objective cellular genetic algorithm that is called MOCELL. MOCELL computes a Pareto front of solutions to empower a human designer with the ability to choose the preferred configuration for the network. Our results are compared with those obtained from the previous proposals used for solving the problem, a cellular multi-objective genetic algorithm which called cMOGA (the old version of MOCELL. We conclude that MOCELL outperforms cMOGA with respect to set coverage metric.
Wang, Jiang; Liu, Hong
2013-10-01
Lead compound optimization plays an important role in new drug discovery and development. The strategies for changing metabolic pathways can modulate pharmacokinetic properties, prolong the half life, improve metabolism stability and bioavailability of lead compounds. The strategies for changing metabolic pathways and improving metabolism stability are reviewed. These methods include blocking metabolic site, reduing lipophilicity, changing ring size, bioisosterism, and prodrug.
Operational optimization in the downstream; Otimizacao operacional no downstream
Energy Technology Data Exchange (ETDEWEB)
Silberman, Luis; Cunha, Filipe Silveira Ramos da [Petroleo Ipiranga, Porto Alegre, RS (Brazil)
2004-07-01
On the present competitive down stream's market, there is a great necessity of optimization aiming to guarantee the best price and quality of our clients. Our goal is to attend these expectations while we guarantee an efficient operation. The greatest question is how far we are from the ideal model. This way, a lot of projects have been executed during the last years aiming the operational optimization of all our activities. We divide the projects in 4 areas: Logistic (new modals distribution), Transport (transport optimization - quality and more deliveries with less trucks), Client Support (Internet Ipiranga and Support Center), Distribution Terminals Productivity (automation and environment). This work intend to present our ideal, perfect and complete Downstream Operation model. We will talk about how close we are of this ideal model and we will present the projects that we had already developed and implanted on the automation of the terminals and the logistics area. (author)
Optimizing Biorefinery Design and Operations via Linear Programming Models
Energy Technology Data Exchange (ETDEWEB)
Talmadge, Michael; Batan, Liaw; Lamers, Patrick; Hartley, Damon; Biddy, Mary; Tao, Ling; Tan, Eric
2017-03-28
The ability to assess and optimize economics of biomass resource utilization for the production of fuels, chemicals and power is essential for the ultimate success of a bioenergy industry. The team of authors, consisting of members from the National Renewable Energy Laboratory (NREL) and the Idaho National Laboratory (INL), has developed simple biorefinery linear programming (LP) models to enable the optimization of theoretical or existing biorefineries. The goal of this analysis is to demonstrate how such models can benefit the developing biorefining industry. It focuses on a theoretical multi-pathway, thermochemical biorefinery configuration and demonstrates how the biorefinery can use LP models for operations planning and optimization in comparable ways to the petroleum refining industry. Using LP modeling tools developed under U.S. Department of Energy's Bioenergy Technologies Office (DOE-BETO) funded efforts, the authors investigate optimization challenges for the theoretical biorefineries such as (1) optimal feedstock slate based on available biomass and prices, (2) breakeven price analysis for available feedstocks, (3) impact analysis for changes in feedstock costs and product prices, (4) optimal biorefinery operations during unit shutdowns / turnarounds, and (5) incentives for increased processing capacity. These biorefinery examples are comparable to crude oil purchasing and operational optimization studies that petroleum refiners perform routinely using LPs and other optimization models. It is important to note that the analyses presented in this article are strictly theoretical and they are not based on current energy market prices. The pricing structure assigned for this demonstrative analysis is consistent with $4 per gallon gasoline, which clearly assumes an economic environment that would favor the construction and operation of biorefineries. The analysis approach and examples provide valuable insights into the usefulness of analysis tools for
Optimal operation of Petlyuk distillation: Steady-state behavior
Ivar J. Halvorsen; Sigurd Skogestad
2001-01-01
The "Petlyuk" or "dividing-wall" or "fully thermally coupled" distillation column is an interesting alternative to the conventional cascaded binary columns for separation of multi-component mixtures. However, the industrial use has been limited, and difficulties in operation have been reported as one reason. With three product compositions controlled, the system has two degrees of freedom left for on-line optimization. We show that the steady-state optimal solution surface is quite narrow, an...
A Computationally Efficient Aggregation Optimization Strategy of Model Predictive Control
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
Model Predictive Control (MPC) is a popular technique and has been successfully used in various industrial applications. However, the big drawback of MPC involved in the formidable on-line computational effort limits its applicability to relatively slow and/or small processes with a moderate number of inputs. This paper develops an aggregation optimization strategy for MPC that can improve the computational efficiency of MPC. For the regulation problem, an input decaying aggregation optimization algorithm is presented by aggregating all the original optimized variables on control horizon with the decaying sequence in respect of the current control action.
Operations planning for agricultural harvesters using ant colony optimization
Directory of Open Access Journals (Sweden)
A. Bakhtiari
2013-07-01
Full Text Available An approach based on ant colony optimization for the generation for optimal field coverage plans for the harvesting operations using the optimal track sequence principle B-patterns was presented. The case where the harvester unloads to a stationary facility located out of the field area, or in the field boundary, was examined. In this operation type there are capacity constraints to the load that a primary unit, or a harvester in this specific case, can carry and consequently, it is not able to complete the task of harvesting a field area and therefore it has to leave the field area, to unload, and return to continue the task one or more times. Results from comparing the optimal plans with conventional plans generated by operators show reductions in the in-field nonworking distance in the range of 19.3-42.1% while the savings in the total non-working distance were in the range of 18-43.8%. These savings provide a high potential for the implementation of the ant colony optimization approach for the case of harvesting operations that are not supported by transport carts for the out-of-the-field removal of the crops, a practice case that is normally followed in developing countries, due to lack of resources.
Cai, Qiong; Adjiman, Claire S.; Brandon, Nigel P.
2014-12-01
The penetration of intermittent renewable energies requires the development of energy storage technologies. High temperature electrolysis using solid oxide electrolyser cells (SOECs) as a potential energy storage technology, provides the prospect of a cost-effective and energy efficient route to clean hydrogen production. The development of optimal control strategies when SOEC systems are coupled with intermittent renewable energies is discussed. Hydrogen production is examined in relation to energy consumption. Control strategies considered include maximizing hydrogen production, minimizing SOEC energy consumption and minimizing compressor energy consumption. Optimal control trajectories of the operating variables over a given period of time show feasible control for the chosen situations. Temperature control of the SOEC stack is ensured via constraints on the overall temperature difference across the cell and the local temperature gradient within the SOEC stack, to link materials properties with system performance; these constraints are successfully managed. The relative merits of the optimal control strategies are analyzed.
Operator scheduling strategy for LBS-based intelligent transportation system
Institute of Scientific and Technical Information of China (English)
WU Jing-jing; XIA Ying; GE Jun-wei; Dong-wook Lee; Hae-young Bae
2007-01-01
With the development of location technologies, advanced LBS-based ITS increasingly requires the capability of database technologies to manage the continuously arrived vehicles' location, traffic jam and other interrelated information of large amounts of traffic in the following years. And some burst arrival stream data will challenge the real-time performance and the allocation of limited resource. However, choosing a desirable database operator scheduling strategy can significantly improve the performance of the system. The path capability strategy was chosen and improved as ITS' operator scheduling strategy to meet the real-time response and the minimal memory requirement of the system.
Managing the Operations-Strategy Interface through Programme Management
DEFF Research Database (Denmark)
Meulengracht Jensen, Peter; Johansen, John; Wæhrens, Brian Vejrum
2011-01-01
This paper explores how one company with globally distributed operations, strive to manage the operations-strategy interface through programme management. The paper focuses on how the organizational context affects the programme configuration and raises a number of propositions as to how programmes...
Energy-optimal programming and scheduling of the manufacturing operations
Badea, N.; Frumuşanu, G.; Epureanu, A.
2016-08-01
The shop floor energy system covers the energy consumed for both the air conditioning and manufacturing processes. At the same time, most of energy consumed in manufacturing processes is converted in heat released in the shop floor interior and has a significant influence on the microclimate. Both these components of the energy consumption have a time variation that can be realistic assessed. Moreover, the consumed energy decisively determines the environmental sustainability of the manufacturing operation, while the expenditure for running the shop floor energy system is a significant component of the manufacturing operations cost. Finally yet importantly, the energy consumption can be fundamentally influenced by properly programming and scheduling of the manufacturing operations. In this paper, we present a method for modeling and energy-optimal programming & scheduling the manufacturing operations. In this purpose, we have firstly identified two optimization targets, namely the environmental sustainability and the economic efficiency. Then, we have defined three optimization criteria, which can assess the degree of achieving these targets. Finally, we have modeled the relationship between the optimization criteria and the parameters of programming and scheduling. In this way, it has been revealed that by adjusting these parameters one can significantly improve the sustainability and efficiency of manufacturing operations. A numerical simulation has proved the feasibility and the efficiency of the proposed method.
Perfect commuting-operator strategies for linear system games
Cleve, Richard; Liu, Li; Slofstra, William
2017-01-01
Linear system games are a generalization of Mermin's magic square game introduced by Cleve and Mittal. They show that perfect strategies for linear system games in the tensor-product model of entanglement correspond to finite-dimensional operator solutions of a certain set of non-commutative equations. We investigate linear system games in the commuting-operator model of entanglement, where Alice and Bob's measurement operators act on a joint Hilbert space, and Alice's operators must commute with Bob's operators. We show that perfect strategies in this model correspond to possibly infinite-dimensional operator solutions of the non-commutative equations. The proof is based around a finitely presented group associated with the linear system which arises from the non-commutative equations.
Activity-Based Information Integrating the operations strategy
Directory of Open Access Journals (Sweden)
José Augusto da Rocha de Araujo
2005-12-01
Full Text Available In the globalized world, companies seek for new operations strategies to ensure world corporate success. This article analyzes how the cost management models – both traditional and activity-based, aid the planning and management of corporate globalized operations. The efficacy of the models application depends on their alignment with the competitive strategy. Companies must evaluate the nature of the competition and its competitive priorities; they should then define the necessary and sufficient dependence level on costs information. In this article, three dependence levels are presented: operational, decision support and strategic control. The result of the research shows the importance of alignment between the cost management model and the competitive strategy for corporate success, and confirms the adequacy of the activity-based costing model as a supporting tool for decision taking in a global strategy. Case studies in world class companies in Brazil are presented.
A Competitive and Experiential Assignment in Search Engine Optimization Strategy
Clarke, Theresa B.; Clarke, Irvine, III
2014-01-01
Despite an increase in ad spending and demand for employees with expertise in search engine optimization (SEO), methods for teaching this important marketing strategy have received little coverage in the literature. Using Bloom's cognitive goals hierarchy as a framework, this experiential assignment provides a process for educators who may be…
A Competitive and Experiential Assignment in Search Engine Optimization Strategy
Clarke, Theresa B.; Clarke, Irvine, III
2014-01-01
Despite an increase in ad spending and demand for employees with expertise in search engine optimization (SEO), methods for teaching this important marketing strategy have received little coverage in the literature. Using Bloom's cognitive goals hierarchy as a framework, this experiential assignment provides a process for educators who may be new…
A Competitive and Experiential Assignment in Search Engine Optimization Strategy
Clarke, Theresa B.; Clarke, Irvine, III
2014-01-01
Despite an increase in ad spending and demand for employees with expertise in search engine optimization (SEO), methods for teaching this important marketing strategy have received little coverage in the literature. Using Bloom's cognitive goals hierarchy as a framework, this experiential assignment provides a process for educators who may be new…
A Particle Swarm Optimization Variant with an Inner Variable Learning Strategy
Directory of Open Access Journals (Sweden)
Guohua Wu
2014-01-01
Full Text Available Although Particle Swarm Optimization (PSO has demonstrated competitive performance in solving global optimization problems, it exhibits some limitations when dealing with optimization problems with high dimensionality and complex landscape. In this paper, we integrate some problem-oriented knowledge into the design of a certain PSO variant. The resulting novel PSO algorithm with an inner variable learning strategy (PSO-IVL is particularly efficient for optimizing functions with symmetric variables. Symmetric variables of the optimized function have to satisfy a certain quantitative relation. Based on this knowledge, the inner variable learning (IVL strategy helps the particle to inspect the relation among its inner variables, determine the exemplar variable for all other variables, and then make each variable learn from the exemplar variable in terms of their quantitative relations. In addition, we design a new trap detection and jumping out strategy to help particles escape from local optima. The trap detection operation is employed at the level of individual particles whereas the trap jumping out strategy is adaptive in its nature. Experimental simulations completed for some representative optimization functions demonstrate the excellent performance of PSO-IVL. The effectiveness of the PSO-IVL stresses a usefulness of augmenting evolutionary algorithms by problem-oriented domain knowledge.
The effect of pre-operative optimization on post-operative outcome in Crohn's disease resections
DEFF Research Database (Denmark)
El-Hussuna, Alaa; Iesalnieks, Igors; Horesh, Nir
2017-01-01
on the post-operative outcome in CD. METHOD: This is a multicentre retrospective cohort study. The primary outcome was 30-day post-operative complications. Secondary outcomes were intra-abdominal septic complications, surgical site infection (SSI), re-operation, length of post-operative stay in a hospital......BACKGROUND: The timing of surgical intervention in Crohn's disease (CD) may depend on pre-operative optimization (PO) which includes different interventions to decrease the risk for unfavourable post-operative outcome. The objective of this study was to investigate the effect of multi-model PO...
Analysis of Optimal Operation of an Energy Integrated Distillation Plant
DEFF Research Database (Denmark)
Li, Hong Wen; Hansen, C.A.; Gani, Rafiqul
2003-01-01
distillation plant is investigated more closely with the purpose of elucidating essential decisions behind planning experiments, which are suitable for identifying models and constraints. The basis for analysis of optimal operation is the type of operation upon which an application focuses. In this paper...... and their influence upon the further decisions behind the experimental design. An energy-integrated distillation column, which may exhibit fold bifurcations, is used as a relevant example process....
Operational characteristics optimization of human-computer system
Zulquernain Mallick; Irfan Anjum Badruddin magami; Khaleed Hussain Tandur
2010-01-01
Computer operational parameters are having vital influence on the operators efficiency from readability viewpoint. Four parameters namely font, text/background color, viewing angle and viewing distance are analyzed. The text reading task, in the form of English text, was presented on the computer screen to the participating subjects and their performance, measured in terms of number of words read per minute (NWRPM), was recorded. For the purpose of optimization, the Taguchi method is u...
Optimal Operation of Energy Storage in Power Transmission and Distribution
2015-01-01
In this thesis, we investigate optimal operation of energy storage units in power transmission and distribution grids. At transmission level, we investigate the problem where an investor-owned independently-operated energy storage system seeks to offer energy and ancillary services in the day-ahead and real-time markets. We specifically consider the case where a significant portion of the power generated in the grid is from renewable energy resources and there exists significant uncertainty i...
BepiColombo MPO Data Handling and Archiving Operations Strategy
Perez-Lopez, Fernando; Martinez, Santa; de la Fuente, Sara; Lefort, Jayne; Casale, Mauro
2013-08-01
This paper describes the BepiColombo MPO Data Handling and Archiving (DHA) Operations Strategy including the justification and the main advantages. This strategy was presented to the MPO Instrument Teams during the BepiColombo Data Handling and Archiving Working Group Meeting #1 held at ESAC in November 2012 and will be implemented by the BepiColombo Science Ground Segment (SGS) in coordination with the MPO Instrument Teams. The paper covers the following topics: BepiColombo Mission Overview, SGS Roles and Interfaces, DHA Strategy Drivers, DHA Strategy Workflow and Conclusions.
Optimal switching strategies for stochastic geocentric/egocentric navigation
Peleg, O
2015-01-01
Animals use a combination of egocentric navigation driven by the internal integration of environmental cues, interspersed with geocentric course correction and reorientation, often with uncertainty in sensory acquisition of information, planning and execution. Inspired directly by observations of dung beetle navigational strategies that show switching between geocentric and egocentric strategies, we consider the question of optimal strategies for the navigation of an agent along a preferred direction in the presence of multiple sources of noise. We address this using a model that takes the form of a correlated random walk at short time scales that is interspersed with reorientation events that yields a biased random walks at long time scales. We identify optimal alternation schemes and characterize their robustness in the context of noisy sensory acquisition, and performance errors linked with variations in environmental conditions and agent-environment interactions.
Optimized cascade reservoir operation considering ice flood control and power generation
Chang, Jianxia; Meng, Xuejiao; Wang, ZongZhi; Wang, Xuebin; Huang, Qiang
2014-11-01
Ice flood control is an important objective for reservoir operation in cold regions. Maintaining the reservoir outflow in a certain range is considered an effective way to remediate ice flood damage. However, this strategy may decrease the socio-economic benefit of reservoirs, for example, reduction of hydropower production. These conflicting objectives cause a dilemma for water managers when defining reservoir operation policy. This study considers seven cascade reservoirs in the upstream Yellow River, and ice flood control storage is introduced to balance the hydropower generation and ice flood control. The relation between the ice flood control storage volume of the Liujiaxia reservoir and cascade power output is analyzed. An optimization model to explore the trade-offs between hydropower generation and ice flood control requirements is developed. The model takes into account ice flood control requirements. The optimization model compared to simulation model based on the reservoir operation rule curves. The results show that the optimal operation rules are far more efficient in balancing the benefits within the power generation and ice flood control. The cascade reservoirs operation strategies proposed in this study can be effectively and suitably used in reservoir operation systems with similar conditions.
Solution of Chemical Dynamic Optimization Using the Simultaneous Strategies
Institute of Scientific and Technical Information of China (English)
LIU Xinggao; CHEN Long; HU Yunqing
2013-01-01
An approach of simultaneous strategies with two novel techniques is proposed to improve the solution accuracy of chemical dynamic optimization problems.The first technique is to handle constraints on control variables based on the finite-element collocation so as to control the approximation error for discrete optimal problems,where a set of control constraints at element knots are integrated with the procedure for optimization leading to a significant gain in the accuracy of the simultaneous strategies.The second technique is to make the mesh refinement more feasible and reliable by introducing length constraints and guideline in designing appropriate element length boundaries,so that the proposed approach becomes more efficient in adjusting elements to track optimal control profile breakpoints and ensure accurate state and control profiles.Four classic benchmarks of dynamic optimization problems are used as illustrations,and the proposed approach is compared with literature reports.The research results reveal that the proposed approach is preferable in improving the solution accuracy of chemical dynamic optimization problem.
Synthesis, design and operation optimization of a marine energy system
Energy Technology Data Exchange (ETDEWEB)
Dimopoulos, George G.; Kougioufas, Aristotelis V.; Frangopoulos, Christos A. [National Technical University of Athens, School of Naval Architecture and Marine Engineering, Heroon Polytechniou 9, 157 73 Zografou (Greece)
2008-02-15
Recent developments in the global fuel markets imposed the need of increased fuel economy and cost effectiveness of sea-going vessels. Optimization of the ship's total energy system, as a whole, is now a demand of the marine industry sector in order to address the significant increase of installation and operational costs. This study is focused on the synthesis, design and operation optimization of a marine energy system. A realistic example of a cruise liner energy system has been selected. Basic technology options have been identified and a generic energy system model has been constructed. Various configuration options, types of technologies and existence of components have been incorporated in the generic system. In addition, time varying operational requirements for this cruise liner ship have been considered, resulting in a time dependent operation optimization problem. The complete optimization problem has been solved using a novel algorithm, inspired by evolutionary and social behavior metaphors. A parametric analysis with respect to the fuel price demonstrated changes in the optimum synthesis of the system. (author)
Positive-operator-valued measure optimization of classical correlations
Hamieh, S; Kobes, R; Zaraket, H
2004-01-01
We study the problem of optimization over positive-operator-valued measures to extract classical correlation in a bipartite quantum system. The proposed method is applied to binary states only. Moreover, to illustrate this method, an explicit example is studied in detail.
Simulation and OR (operations research) in combination for practical optimization
N. van Dijk; E. van der Sluis; R. Haijema; A. Al-Ibrahim; J. van der Wal
2005-01-01
Should we pool capacities or not? This is a question that one can regularly be confronted with in operations and service management. It is a question that necessarily requires a combination of queueing (as OR discipline) and simulation (as evaluative tool) and further steps for optimization. It will
An optimizing start-up strategy for a bio-methanator.
Sbarciog, Mihaela; Loccufier, Mia; Vande Wouwer, Alain
2012-05-01
This paper presents an optimizing start-up strategy for a bio-methanator. The goal of the control strategy is to maximize the outflow rate of methane in anaerobic digestion processes, which can be described by a two-population model. The methodology relies on a thorough analysis of the system dynamics and involves the solution of two optimization problems: steady-state optimization for determining the optimal operating point and transient optimization. The latter is a classical optimal control problem, which can be solved using the maximum principle of Pontryagin. The proposed control law is of the bang-bang type. The process is driven from an initial state to a small neighborhood of the optimal steady state by switching the manipulated variable (dilution rate) from the minimum to the maximum value at a certain time instant. Then the dilution rate is set to the optimal value and the system settles down in the optimal steady state. This control law ensures the convergence of the system to the optimal steady state and substantially increases its stability region. The region of attraction of the steady state corresponding to maximum production of methane is considerably enlarged. In some cases, which are related to the possibility of selecting the minimum dilution rate below a certain level, the stability region of the optimal steady state equals the interior of the state space. Aside its efficiency, which is evaluated not only in terms of biogas production but also from the perspective of treatment of the organic load, the strategy is also characterized by simplicity, being thus appropriate for implementation in real-life systems. Another important advantage is its generality: this technique may be applied to any anaerobic digestion process, for which the acidogenesis and methanogenesis are, respectively, characterized by Monod and Haldane kinetics.
Nennie, E.D.; Savenko, S.V.; Alberts, G.J.N.; Cargnelutti, M.F.; Donkelaar, E. van
2009-01-01
With an increasing number of smart well applications being installed in the field, more knowledge is required to optimize their operation. This paper compares the benefits of various wellhead gas coning control strategies to optimize production of a thin oil rim. This study is performed within the "
Design procedure for optimizing CMOS low noise operational amplifiers
Institute of Scientific and Technical Information of China (English)
Li Zhiyuan; Ye Yizheng; Ma Jianguo
2009-01-01
This paper presents and experimentally verifies an optimized design procedure for a CMOS low noise operational amplifier.The design procedure focuses on the noise performance,which is the key requirement for low noise operational amplifiers.Based on the noise level and other specifications such as bandwidth,signal swing,slew rate,and power consumption,the device sizes and the biasing conditions are derived.In order to verify the proposed design procedure,a three-stage operational amplifier has been designed.The device parameters obtained from the proposed design procedure closely agree with the simulated results obtained by using HSPICE.
Near-Optimal Operation of Dual-Fuel Launch Vehicles
Ardema, M. D.; Chou, H. C.; Bowles, J. V.
1996-01-01
A near-optimal guidance law for the ascent trajectory from earth surface to earth orbit of a fully reusable single-stage-to-orbit pure rocket launch vehicle is derived. Of interest are both the optimal operation of the propulsion system and the optimal flight path. A methodology is developed to investigate the optimal throttle switching of dual-fuel engines. The method is based on selecting propulsion system modes and parameters that maximize a certain performance function. This function is derived from consideration of the energy-state model of the aircraft equations of motion. Because the density of liquid hydrogen is relatively low, the sensitivity of perturbations in volume need to be taken into consideration as well as weight sensitivity. The cost functional is a weighted sum of fuel mass and volume; the weighting factor is chosen to minimize vehicle empty weight for a given payload mass and volume in orbit.
Data reconciliation and optimal operation of a Catalytic naphtha reformer
Directory of Open Access Journals (Sweden)
Tore Lid
2008-10-01
Full Text Available The naphtha reforming process converts low-octane gasoline blending components to high-octane components for use in high-performance gasoline fuels. The reformer also has an important function as the producer of hydrogen to the refinery hydrotreaters. A process model based on a unit model structure, is used for estimation of the process condition using data reconciliation. Measurements are classified as redundant or non redundant and the model variables are classified as observable, barely observable or unobservable. The computed uncertainty of the measured and unmeasured variables shows that even if a variable is observable it may have a very large uncertainty and may thereby be practically unobservable. The process condition at 21 data points, sampled from two years of operation, was reconciled and used to optimize the process operation. There are large seasonal variations in the reformer product price and two operational cases are studied. In case 1, the product price is high and throughput is maximized with respect to process and product quality constraints. In case 2, the product price is low and the throughput is minimized with respect to a low constraint on the hydrogen production. Based on the characteristics of the optimal operation, a "self optimizing" control structure is suggested for each of the two operational cases.
Research on operation optimization of multi-product pipeline
Energy Technology Data Exchange (ETDEWEB)
Liang, Y.; Gong, J.; Kang, Z.; Yang, F. [Petroleum Univ., Beijing (China). College of Petroleum Engineering
2004-07-01
In order to operate complex, long-distance pipelines safely and efficiently while meeting energy demands, operators require offline optimization simulation software. This paper presented the newly developed STROBER software for simulating the operations of multi-product pipelines whose hydraulic characteristics vary continuously with batch movement in the pipeline. The software was based on a mathematical model that optimized the configuration of pumps in order to minimize the electricity costs associated with operating a multi-product pipeline. The energy conservation equation met the following restraining factors: the flow rate in an initial pumping station was as stable as possible for specific periods of time; the inlet and outlet pressures of the pumping stations and the pressures of some special points were within the preset limits; and, the off-take task was completed during a prescribed time. The optimization theory was solved using dynamic programming. The peak-to-valley ratio of electricity price was also taken into consideration in order to encourage pipeline companies to consume most electricity during off-peak periods of the electrical network. The STROBER software was successfully applied in the start-up and current operation of the LanZhou-ChengDu-ChongQing multi-product pipeline in China. This complex pipeline includes 13 off-take stations, 2 pressure-reducing stations and 4 pumping stations. The software provided off-take plans and information on pressure control. 8 refs., 2 tabs., 4 figs.
Annealing Ant Colony Optimization with Mutation Operator for Solving TSP
Directory of Open Access Journals (Sweden)
Abdulqader M. Mohsen
2016-01-01
Full Text Available Ant Colony Optimization (ACO has been successfully applied to solve a wide range of combinatorial optimization problems such as minimum spanning tree, traveling salesman problem, and quadratic assignment problem. Basic ACO has drawbacks of trapping into local minimum and low convergence rate. Simulated annealing (SA and mutation operator have the jumping ability and global convergence; and local search has the ability to speed up the convergence. Therefore, this paper proposed a hybrid ACO algorithm integrating the advantages of ACO, SA, mutation operator, and local search procedure to solve the traveling salesman problem. The core of algorithm is based on the ACO. SA and mutation operator were used to increase the ants population diversity from time to time and the local search was used to exploit the current search area efficiently. The comparative experiments, using 24 TSP instances from TSPLIB, show that the proposed algorithm outperformed some well-known algorithms in the literature in terms of solution quality.
Annealing Ant Colony Optimization with Mutation Operator for Solving TSP.
Mohsen, Abdulqader M
2016-01-01
Ant Colony Optimization (ACO) has been successfully applied to solve a wide range of combinatorial optimization problems such as minimum spanning tree, traveling salesman problem, and quadratic assignment problem. Basic ACO has drawbacks of trapping into local minimum and low convergence rate. Simulated annealing (SA) and mutation operator have the jumping ability and global convergence; and local search has the ability to speed up the convergence. Therefore, this paper proposed a hybrid ACO algorithm integrating the advantages of ACO, SA, mutation operator, and local search procedure to solve the traveling salesman problem. The core of algorithm is based on the ACO. SA and mutation operator were used to increase the ants population diversity from time to time and the local search was used to exploit the current search area efficiently. The comparative experiments, using 24 TSP instances from TSPLIB, show that the proposed algorithm outperformed some well-known algorithms in the literature in terms of solution quality.
On the robust optimization to the uncertain vaccination strategy problem
Energy Technology Data Exchange (ETDEWEB)
Chaerani, D., E-mail: d.chaerani@unpad.ac.id; Anggriani, N., E-mail: d.chaerani@unpad.ac.id; Firdaniza, E-mail: d.chaerani@unpad.ac.id [Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Padjadjaran Indonesia, Jalan Raya Bandung Sumedang KM 21 Jatinangor Sumedang 45363 (Indonesia)
2014-02-21
In order to prevent an epidemic of infectious diseases, the vaccination coverage needs to be minimized and also the basic reproduction number needs to be maintained below 1. This means that as we get the vaccination coverage as minimum as possible, thus we need to prevent the epidemic to a small number of people who already get infected. In this paper, we discuss the case of vaccination strategy in term of minimizing vaccination coverage, when the basic reproduction number is assumed as an uncertain parameter that lies between 0 and 1. We refer to the linear optimization model for vaccination strategy that propose by Becker and Starrzak (see [2]). Assuming that there is parameter uncertainty involved, we can see Tanner et al (see [9]) who propose the optimal solution of the problem using stochastic programming. In this paper we discuss an alternative way of optimizing the uncertain vaccination strategy using Robust Optimization (see [3]). In this approach we assume that the parameter uncertainty lies within an ellipsoidal uncertainty set such that we can claim that the obtained result will be achieved in a polynomial time algorithm (as it is guaranteed by the RO methodology). The robust counterpart model is presented.
DEFF Research Database (Denmark)
Liu, Zhou; Chen, Zhe; Sun, Haishun Sun;
2012-01-01
In order to prevent long term voltage instability and induced cascading events, a load shedding strategy based on the sensitivity of relay operation margin to load powers is discussed and proposed in this paper. The operation margin of critical impedance backup relay is defined to identify the ru...... into account to compensate load shedding amount calculation. And the multi-agent technology is applied for the whole strategy implementation. A test system is built in real time digital simulator (RTDS) and has demonstrated the effectiveness of the proposed strategy.......In order to prevent long term voltage instability and induced cascading events, a load shedding strategy based on the sensitivity of relay operation margin to load powers is discussed and proposed in this paper. The operation margin of critical impedance backup relay is defined to identify...... the runtime emergent states of related system component. Based on sensitivity analysis between the relay operation margin and power system state variables, an optimal load shedding strategy is applied to adjust the emergent states timely before the unwanted relay operation. Load dynamics is also taken...
An optimal routing strategy on scale-free networks
Yang, Yibo; Zhao, Honglin; Ma, Jinlong; Qi, Zhaohui; Zhao, Yongbin
Traffic is one of the most fundamental dynamical processes in networked systems. With the traditional shortest path routing (SPR) protocol, traffic congestion is likely to occur on the hub nodes on scale-free networks. In this paper, we propose an improved optimal routing (IOR) strategy which is based on the betweenness centrality and the degree centrality of nodes in the scale-free networks. With the proposed strategy, the routing paths can accurately bypass hub nodes in the network to enhance the transport efficiency. Simulation results show that the traffic capacity as well as some other indexes reflecting transportation efficiency are further improved with the IOR strategy. Owing to the significantly improved traffic performance, this study is helpful to design more efficient routing strategies in communication or transportation systems.
SSBRP User Operations Facility (UOF) Overview and Development Strategy
Picinich, Lou; Stone, Thom; Sun, Charles; Windrem, May; Givens, John J. (Technical Monitor)
1995-01-01
This paper will present the Space Station Biological Research Project (SSBRP) User Operations Facility (UOF) architecture and development strategy. A major element of the UOF at NASA Ames Research Center, the Communication and Data System (CDS) will be the primary focus of the discussions. CDS operational, telescience, security, and development objectives will be discussed along with CDS implementation strategy. The implementation strategy discussions will include: Object Oriented Analysis & Design, System & Software Prototyping, and Technology Utilization. A CDS design overview that includes: CDS Context Diagram, CDS Architecture, Object Models, Use Cases, and User Interfaces will also be presented. CDS development brings together "cutting edge" technologies and techniques such as: object oriented development, network security, multimedia networking, web-based data distribution, JAVA, and graphical user interfaces. Use of these "cutting edge" technologies and techniques translates directly to lower development and operations costs.
Optimal Operation of Energy Storage in Power Transmission and Distribution
Akhavan Hejazi, Seyed Hossein
In this thesis, we investigate optimal operation of energy storage units in power transmission and distribution grids. At transmission level, we investigate the problem where an investor-owned independently-operated energy storage system seeks to offer energy and ancillary services in the day-ahead and real-time markets. We specifically consider the case where a significant portion of the power generated in the grid is from renewable energy resources and there exists significant uncertainty in system operation. In this regard, we formulate a stochastic programming framework to choose optimal energy and reserve bids for the storage units that takes into account the fluctuating nature of the market prices due to the randomness in the renewable power generation availability. At distribution level, we develop a comprehensive data set to model various stochastic factors on power distribution networks, with focus on networks that have high penetration of electric vehicle charging load and distributed renewable generation. Furthermore, we develop a data-driven stochastic model for energy storage operation at distribution level, where the distribution of nodal voltage and line power flow are modelled as stochastic functions of the energy storage unit's charge and discharge schedules. In particular, we develop new closed-form stochastic models for such key operational parameters in the system. Our approach is analytical and allows formulating tractable optimization problems. Yet, it does not involve any restricting assumption on the distribution of random parameters, hence, it results in accurate modeling of uncertainties. By considering the specific characteristics of random variables, such as their statistical dependencies and often irregularly-shaped probability distributions, we propose a non-parametric chance-constrained optimization approach to operate and plan energy storage units in power distribution girds. In the proposed stochastic optimization, we consider
Improvement of strategies and parameters for multi-axis laser cladding operations
Calleja, A.; Tabernero, I.; Fernández, A.; Celaya, A.; Lamikiz, A.; López de Lacalle, L. N.
2014-05-01
The application of laser cladding technology is nowadays widely extended in several industrial sectors due to its advantages for high added value parts direct manufacturing and repairing. At the moment, the process is mainly applied to 3 axis or 3+2 axis strategies, being numerous works focused on the obtainment of process parameters. Some industrial application imposes the use of 5 continuous axis kinematics to perform complex parts. This fact requires new processes design and new strategies for this type of operations. The presented work evaluates the steps to be followed before accomplishing 5 axis laser cladding operations. First, the design of a test part for the experimental tests is carried out, taking into account the machine kinematics. Afterwards, both, the process control parameters and the tool path strategies are analyzed. Finally, the optimization of process parameter and strategies is presented. Therefore, the work represents a useful tool for the industrial application of 5 axis laser cladding.
Inner strategies of coping with operational work amongst SAPS officers
Directory of Open Access Journals (Sweden)
Masefako A. Gumani
2013-03-01
Full Text Available Orientation: Identification of the inner coping strategies used by South African Police Service (SAPS officers who do operational work is something the SAPS should consider to ensure the officers’ management of trauma and efficiency at work.Research purpose: The objective of this study was to describe inner coping strategies used by officers in the Vhembe district (South Africa to reconstruct stressful and traumatic experiences at work.Motivation for the study: Most studies on coping amongst SAPS officers focus on organisational stress and not on the impact of the officers’ operational work.Research design, approach and method: An exploratory design was used and 20 SAPS officers were selected through purposive sampling. In-depth face-to-face and telephone interviews, as well as diaries were used to collect data, which were analysed using content thematic data analysis.Main findings: The results showed that the main categories of coping strategies that led to management of the impact of operational work amongst the selected sample were centred around problem-focused and emotion-focused strategies, with some use of reappraisal and minimal use of avoidance. Considering the context of the officers’ work, the list of dimensions of inner coping strategies amongst SAPS officers should be extended.Practical/managerial implications: Intervention programmes designed for the SAPS, including critical incident stress debriefing, should take the operational officers’ inner strategies into account to improve the management of the impact of their work.Contribution/value-add: This study contributes to the body of knowledge on the inner coping strategies amongst SAPS officers, with special reference to operational work in a specific setting.
Optimal Input Strategy for Plug and Play Process Control Systems
DEFF Research Database (Denmark)
Kragelund, Martin Nygaard; Leth, John-Josef; Wisniewski, Rafal
2010-01-01
This paper considers the problem of optimal operation of a plant, which goal is to maintain production at minimum cost. The system considered in this work consists of a joined plant and redundant input systems. It is assumed that each input system contributes to a flow of goods into the joined part...
Energy Technology Data Exchange (ETDEWEB)
Schroeder, Hans Christian; Harder, Hans-Otto [TUeV SUeD Industrie Service GmbH, Mannheim (Germany). Kraftwerks- und Anlagenservice
2008-07-01
There are many causes and mode of actions which result in damages and a reduction of the lifetime of process engineering plants. Here, planning, design, production, assembly, acceptance, operation and maintenance play an important role. These factors play an important role in the case of future expecting operation temperatures above 600 C. Under this aspect, the authors of the contribution under consideration present the changes which can be expected regarding to the design concepts and to the operationally enhanced operating stresses from the aspect of a certified supervisory board.
Operation and maintenance strategies for wave energy converters
DEFF Research Database (Denmark)
Ambühl, Simon; Marquis, Laurent; Kofoed, Jens Peter;
2015-01-01
Inspection and maintenance costs are a significant contributor to the cost of energy for wave energy converters. There are different operation and maintenance strategies for wave energy converters. Maintenance can be performed after failure (corrective) or before a breakdown (preventive) occurs...... and maintenance costs estimations for wave energy converter applications including real weather data and damage accumulation. Furthermore, uncertainties related with costs, structural damage accumulation, inspection accuracy and different maintenance strategies can be included. This article contains a case study...
Operating strategies on HCCI combustion; Betriebsstrategien fuer die Benzinselbstzuendung
Energy Technology Data Exchange (ETDEWEB)
Babic, Goran; Bargende, Michael [Stuttgart Univ. (DE). Inst. fuer Verbrennungsmotoren und Kraftfahrzeuge (IVK)
2010-09-15
The gasoline self-ignition represents an alternative part load combustion strategy, which radically reduces the nitrogen-oxide emissions in combination with improved process efficiency. At the request of the Research Association for Combustion Engines (FVV) the Institute for Internal Combustion Engines and Automotive Engineering (IVK) of the University of Stuttgart investigated different operating strategies on gasoline self-ignition and developed methods for mode switches under close-to-production conditions. (orig.)
Research of stochastic weight strategy for extended particle swarm optimizer
Institute of Scientific and Technical Information of China (English)
XU Jun-jie; YUE Xin; XIN Zhan-hong
2008-01-01
To improve the performance of extended particle swarm optimizer, a novel means of stochastic weight deployment is proposed for the iterative equation of velocity updation. In this scheme, one of the weights is specified to a random number within the range of [0, 1] and the other two remain constant configurations. The simulations show that this weight strategy outperforms the previous deterministic approach with respect to success rate and convergence speed. The experi- ments also reveal that if the weight for global best neighbor is specified to a stochastic number, extended particle swarm optimizer achieves high and robust performance on the given multi-modal function.
Optimal search strategies on complex multi-linked networks
Di Patti, Francesca; Fanelli, Duccio; Piazza, Francesco
2015-01-01
In this paper we consider the problem of optimal search strategies on multi-linked networks, i.e. graphs whose nodes are endowed with several independent sets of links. We focus preliminarily on agents randomly hopping along the links of a graph, with the additional possibility of performing non-local hops to randomly chosen nodes with a given probability. We show that an optimal combination of the two jump rules exists that maximises the efficiency of target search, the optimum reflecting the topology of the network. We then generalize our results to multi-linked networks with an arbitrary number of mutually interfering link sets. PMID:25950716
Automatic CT simulation optimization for radiation therapy: A general strategy
Energy Technology Data Exchange (ETDEWEB)
Li, Hua, E-mail: huli@radonc.wustl.edu; Chen, Hsin-Chen; Tan, Jun; Gay, Hiram; Michalski, Jeff M.; Mutic, Sasa [Department of Radiation Oncology, Washington University, St. Louis, Missouri 63110 (United States); Yu, Lifeng [Department of Radiology, Mayo Clinic, Rochester, Minnesota 55905 (United States); Anastasio, Mark A. [Department of Biomedical Engineering, Washington University, St. Louis, Missouri 63110 (United States); Low, Daniel A. [Department of Radiation Oncology, University of California Los Angeles, Los Angeles, California 90095 (United States)
2014-03-15
Purpose: In radiation therapy, x-ray computed tomography (CT) simulation protocol specifications should be driven by the treatment planning requirements in lieu of duplicating diagnostic CT screening protocols. The purpose of this study was to develop a general strategy that allows for automatically, prospectively, and objectively determining the optimal patient-specific CT simulation protocols based on radiation-therapy goals, namely, maintenance of contouring quality and integrity while minimizing patient CT simulation dose. Methods: The authors proposed a general prediction strategy that provides automatic optimal CT simulation protocol selection as a function of patient size and treatment planning task. The optimal protocol is the one that delivers the minimum dose required to provide a CT simulation scan that yields accurate contours. Accurate treatment plans depend on accurate contours in order to conform the dose to actual tumor and normal organ positions. An image quality index, defined to characterize how simulation scan quality affects contour delineation, was developed and used to benchmark the contouring accuracy and treatment plan quality within the predication strategy. A clinical workflow was developed to select the optimal CT simulation protocols incorporating patient size, target delineation, and radiation dose efficiency. An experimental study using an anthropomorphic pelvis phantom with added-bolus layers was used to demonstrate how the proposed prediction strategy could be implemented and how the optimal CT simulation protocols could be selected for prostate cancer patients based on patient size and treatment planning task. Clinical IMRT prostate treatment plans for seven CT scans with varied image quality indices were separately optimized and compared to verify the trace of target and organ dosimetry coverage. Results: Based on the phantom study, the optimal image quality index for accurate manual prostate contouring was 4.4. The optimal tube
Transitions in optimal adaptive strategies for populations in fluctuating environments
Mayer, Andreas; Mora, Thierry; Rivoire, Olivier; Walczak, Aleksandra M.
2017-09-01
Biological populations are subject to fluctuating environmental conditions. Different adaptive strategies can allow them to cope with these fluctuations: specialization to one particular environmental condition, adoption of a generalist phenotype that compromises between conditions, or population-wise diversification (bet hedging). Which strategy provides the largest selective advantage in the long run depends on the range of accessible phenotypes and the statistics of the environmental fluctuations. Here, we analyze this problem in a simple mathematical model of population growth. First, we review and extend a graphical method to identify the nature of the optimal strategy when the environmental fluctuations are uncorrelated. Temporal correlations in environmental fluctuations open up new strategies that rely on memory but are mathematically challenging to study: We present analytical results to address this challenge. We illustrate our general approach by analyzing optimal adaptive strategies in the presence of trade-offs that constrain the range of accessible phenotypes. Our results extend several previous studies and have applications to a variety of biological phenomena, from antibiotic resistance in bacteria to immune responses in vertebrates.
Operations Strategy and –Innovation? -A Contractor Implementing Lean
DEFF Research Database (Denmark)
Koch, Christian; Simonsen, Rolf
2006-01-01
Traditional strategic management and operations strategy wants us to believe that the implementation of management concepts is a simple strategic choice made by top managers. In this paper we introduce the story of Lean Construction entering into the organisation of a Danish contractor. Lean...... concepts. The paper presents findings from empirical work in collaboration with a large Danish contractor. The case is analysed from the perspective of operation strategy and political process. It is observed how the management concept is socially constructed and negotiated through political action of key...
Future Horizons For Optimal Operation of Mosul Dam Reservoir
Directory of Open Access Journals (Sweden)
Abdulwahab Gazal
2013-05-01
Full Text Available In this study, The Discrete Differential Dynamic Programming (DDDP has been applied to the operation of Mosul dam reservoir on Tigris river, North of Iraq. The simulation technique (SM has been used to evaluate the results obtained from the (DDDP model. The aim of this study is to obtain the present and future optimal monthly reservoir operation policies for the years (2007, 2017, and 2027 through fulfilling the irrigation requirements of Jazira Irrigation Project and water supply requirements according to different operation states. The states included the operation of Northern only, Northern and Eastern; and the Northern, Eastern and Southern Jazira Irrigation Projects for minimum annual inflow in all states. The results indicated water deficit occurrence with the second and third states. For optimization model, the water deficits were distributed over long periods which helped to minimize the penalty, and the reservoir storages were within the upper and lower operating storage limits. Whereas for simulation model the water deficits were concentrated within short periods and the reservoir storages declined below the lower operating storage limit.
Survey of E-Commerce Modeling and Optimization Strategies
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
Electronic commerce is impacting almost all commercial activities. The resulting emerging commercial activities bring with them many new modeling and optimization problems. This survey reviews pioneering works in this new area, covering topics in advertising strategy, web page design, automatic pricing, auction methods, brokerage strategy, and customer behavior analysis. Mathematical models for problems in these areas and their solution algorithms are discussed. In addition to presenting and commenting on these works, we also discuss possible extensions and related problems. The objective of this survey is to encourage more researchers to pay attention to this emerging area.
Acceleration of quantum optimal control theory algorithms with mixing strategies.
Castro, Alberto; Gross, E K U
2009-05-01
We propose the use of mixing strategies to accelerate the convergence of the common iterative algorithms utilized in quantum optimal control theory (QOCT). We show how the nonlinear equations of QOCT can be viewed as a "fixed-point" nonlinear problem. The iterative algorithms for this class of problems may benefit from mixing strategies, as it happens, e.g., in the quest for the ground-state density in Kohn-Sham density-functional theory. We demonstrate, with some numerical examples, how the same mixing schemes utilized in this latter nonlinear problem may significantly accelerate the QOCT iterative procedures.
Optimizing the domain wall fermion Dirac operator using the R-Stream source-to-source compiler
Lin, Meifeng; Langston, M Harper; Meister, Benoit; Baskaran, Muthu; Izubuchi, Taku; Jung, Chulwoo
2015-01-01
The application of the Dirac operator on a spinor field, the Dslash operation, is the most computation-intensive part of the lattice QCD simulations. It is often the key kernel to optimize to achieve maximum performance on various platforms. Here we report on a project to optimize the domain wall fermion Dirac operator in Columbia Physics System (CPS) using the R-Stream source-to-source compiler. Our initial target platform is the Intel PC clusters. We discuss the optimization strategies involved before and after the automatic code generation with R-Stream and present some preliminary benchmark results.
García-Barberena, Javier; Erdocia, Ioseba
2016-05-01
The increase of electric power demand and the wish to protect the environment are leading to a change in the energy sources. Conventional energy plants are losing strength against the renewable energy plants and, in particular, solar energy plants have a huge potential to provide clean energy supply for the increasing world's energy demand. Among the existing solar technologies, Concentrating Solar Power (CSP) is one of the most promising technologies. One of the major advantages of CSP plants is the technically feasible and cost-effective integration of Thermal Energy Storage (TES) systems. To increase the plant dispatchability, it is possible to create different operational strategies defining how such TES system is used. In this work, different strategies with different overall goals have been simulated over a complete year and the results are presented and compared here to demonstrate the capabilities of the operational strategies towards an increased dispatchability and plant economic effectiveness. The analysis shows that different strategies may lead to significant differences in the plant annual production, expected economic incomes, number of power block stops, mean efficiency, etc. Specifically, it has been found that the economic incomes of a plant can be increased (+1.3%) even with a decreased total energy production (-1.5%) if the production is scheduled to follow a demand/price curve. Also, dramatic reduction in the number of turbine stops (-67%) can be achieved if the plant is operated towards this objective. The strategies presented in this study have not been optimized towards any specific objective, but only created to show the potential of well designed operational strategies in CSP plants. Therefore, many other strategies as well as optimized versions of the strategies explained below are possible and will be analyzed in future works.
Growth Strategies of Mobile Virtual Network Operators in Oman
Directory of Open Access Journals (Sweden)
Dr N.P. Singh
2010-12-01
Full Text Available The Oman telecom market consists of five Mobile Virtual Network Operators (MVNOs and two Mobile Network Operators (MNOs. MVNOs have also sealed their deals with MNOs, technology providers, advertising and marketing agencies, SIM and re-charge coupon distribution channels. All the five MVNOs in Oman have already launched their operations and are providing services. The article is an attempt to understand many facets of MVNO business in Oman. The article discusses the present status of operations of MVNOs, their growth in Oman and w orld, their tariff plans, SIM card distribution channels and marketing strategies to survive in a highly competitive Omani telecom market. A set of propositions are also identified related to success of MVNOs which are proved either true or false using secondary data collected from various sources. The article concluded in the form of synthesis of data and possible new future strategies for MVNOs in Oman.
OPF-Based Optimal Location of Two Systems Two Terminal HVDC to Power System Optimal Operation
Directory of Open Access Journals (Sweden)
Mehdi Abolfazli
2013-04-01
Full Text Available In this paper a suitable mathematical model of the two terminal HVDC system is provided for optimal power flow (OPF and optimal location based on OPF such power injection model. The ability of voltage source converter (VSC-based HVDC to independently control active and reactive power is well represented by the model. The model is used to develop an OPF-based optimal location algorithm of two systems two terminal HVDC to minimize the total fuel cost and active power losses as objective function. The optimization framework is modeled as non-linear programming (NLP and solved by Matlab and GAMS softwares. The proposed algorithm is implemented on the IEEE 14- and 30-bus test systems. The simulation results show ability of two systems two terminal HVDC in improving the power system operation. Furthermore, two systems two terminal HVDC is compared by PST and OUPFC in the power system operation from economical and technical aspects.
Optimal intervention strategies for cholera outbreak by education and chlorination
Bakhtiar, Toni
2016-01-01
This paper discusses the control of infectious diseases in the framework of optimal control approach. A case study on cholera control was studied by considering two control strategies, namely education and chlorination. We distinct the former control into one regarding person-to-person behaviour and another one concerning person-to-environment conduct. Model are divided into two interacted populations: human population which follows an SIR model and pathogen population. Pontryagin maximum principle was applied in deriving a set of differential equations which consists of dynamical and adjoin systems as optimality conditions. Then, the fourth order Runge-Kutta method was exploited to numerically solve the equation system. An illustrative example was provided to assess the effectiveness of the control strategies toward a set of control scenarios.
A NEW STOCHASTIC OPTIMAL CONTROL STRATEGY FOR HYSTERETIC MR DAMPERS
Institute of Scientific and Technical Information of China (English)
YingZuguang; NiYiqing; KoJanming
2004-01-01
A new stochastic optimal control strategy for randomly excited quasi-integrable Hamiltonian systems using magneto-theological (MR) dampers is proposed. The dynamic behavior of an MR damper is characterized by the Bouc-Wen hysteretic model. The control force produced by the MR damper is separated into a passive part incorporated in the uncontrolled system and a semi-active part to be determined. The system combining the Bouc-Wen hysteretic force is converted into an equivalent non-hysteretic nonlinear stochastic control system. Then Ito stochastic differential equations are derived from the equivalent system by using the stochastic averaging method. A dynamical programming equation for the controlled diffusion processes is established based on the stochastic dynamical programming principle. The non-clipping nonlinear optimal control law is obtained for a certain performance index by minimizing the dynamical programming equation. Finally, an example is given to illustrate the application and effectiveness of the proposed control strategy.
Using Cotton Model Simulations to Estimate Optimally Profitable Irrigation Strategies
Mauget, S. A.; Leiker, G.; Sapkota, P.; Johnson, J.; Maas, S.
2011-12-01
In recent decades irrigation pumping from the Ogallala Aquifer has led to declines in saturated thickness that have not been compensated for by natural recharge, which has led to questions about the long-term viability of agriculture in the cotton producing areas of west Texas. Adopting irrigation management strategies that optimize profitability while reducing irrigation waste is one way of conserving the aquifer's water resource. Here, a database of modeled cotton yields generated under drip and center pivot irrigated and dryland production scenarios is used in a stochastic dominance analysis that identifies such strategies under varying commodity price and pumping cost conditions. This database and analysis approach will serve as the foundation for a web-based decision support tool that will help producers identify optimal irrigation treatments under specified cotton price, electricity cost, and depth to water table conditions.
Optimized Power Dispatch Strategy for Offshore Wind Farms
DEFF Research Database (Denmark)
Hou, Peng; Hu, Weihao; Zhang, Baohua
2016-01-01
Maximizing the power production of offshore wind farms using proper control strategy has become an important issue for wind farm operators. However, the power transmitted to the onshore substation (OS) is not only related to the power production of each wind turbine (WT) but also the power losses...
Optimization of reliability allocation strategies through use of genetic algorithms
Energy Technology Data Exchange (ETDEWEB)
Campbell, J.E.; Painton, L.A.
1996-08-01
This paper examines a novel optimization technique called genetic algorithms and its application to the optimization of reliability allocation strategies. Reliability allocation should occur in the initial stages of design, when the objective is to determine an optimal breakdown or allocation of reliability to certain components or subassemblies in order to meet system specifications. The reliability allocation optimization is applied to the design of a cluster tool, a highly complex piece of equipment used in semiconductor manufacturing. The problem formulation is presented, including decision variables, performance measures and constraints, and genetic algorithm parameters. Piecewise ``effort curves`` specifying the amount of effort required to achieve a certain level of reliability for each component of subassembly are defined. The genetic algorithm evolves or picks those combinations of ``effort`` or reliability levels for each component which optimize the objective of maximizing Mean Time Between Failures while staying within a budget. The results show that the genetic algorithm is very efficient at finding a set of robust solutions. A time history of the optimization is presented, along with histograms or the solution space fitness, MTBF, and cost for comparative purposes.
Comparison of operation optimization methods in energy system modelling
DEFF Research Database (Denmark)
Ommen, Torben Schmidt; Markussen, Wiebke Brix; Elmegaard, Brian
2013-01-01
, possibilities for decoupling production constraints may be valuable. Introduction of heat pumps in the district heating network may pose this ability. In order to evaluate if the introduction of heat pumps is economically viable, we develop calculation methods for the operation patterns of each of the used...... energy technologies. In the paper, three frequently used operation optimization methods are examined with respect to their impact on operation management of the combined technologies. One of the investigated approaches utilises linear programming for optimisation, one uses linear programming with binary...... operation constraints, while the third approach uses nonlinear programming. In the present case the non-linearity occurs in the boiler efficiency of power plants and the cv-value of an extraction plant. The linear programming model is used as a benchmark, as this type is frequently used, and has the lowest...
Optimal sampling strategies for detecting zoonotic disease epidemics.
Ferguson, Jake M; Langebrake, Jessica B; Cannataro, Vincent L; Garcia, Andres J; Hamman, Elizabeth A; Martcheva, Maia; Osenberg, Craig W
2014-06-01
The early detection of disease epidemics reduces the chance of successful introductions into new locales, minimizes the number of infections, and reduces the financial impact. We develop a framework to determine the optimal sampling strategy for disease detection in zoonotic host-vector epidemiological systems when a disease goes from below detectable levels to an epidemic. We find that if the time of disease introduction is known then the optimal sampling strategy can switch abruptly between sampling only from the vector population to sampling only from the host population. We also construct time-independent optimal sampling strategies when conducting periodic sampling that can involve sampling both the host and the vector populations simultaneously. Both time-dependent and -independent solutions can be useful for sampling design, depending on whether the time of introduction of the disease is known or not. We illustrate the approach with West Nile virus, a globally-spreading zoonotic arbovirus. Though our analytical results are based on a linearization of the dynamical systems, the sampling rules appear robust over a wide range of parameter space when compared to nonlinear simulation models. Our results suggest some simple rules that can be used by practitioners when developing surveillance programs. These rules require knowledge of transition rates between epidemiological compartments, which population was initially infected, and of the cost per sample for serological tests.
Incorporate Energy Strategy into Particle Swarm Optimizer Algorithm
Institute of Scientific and Technical Information of China (English)
ZHANG Lun; DONG De-cun; LU Yan; CHEN Lan
2008-01-01
The issue of optimizing the dynamic parameters in Particle Swarm Optimizer (PSO) is addressed in this paper.An algorithm is designed which makes all particles originally endowed with a certain level energy, what here we define as EPSO (Energy Strategy PSO).During the iterative process of PSO algorithm, the Inertia Weight is updated according to the calculation of the particle's energy.The portion ratio of the current residual energy to the initial endowed energy is used as the parameter Inertia Weight which aims to update the particles' velocity efficiently.By the simulation in a graph theoritical and a functional optimization problem respectively, it could be easily found that the rate of convergence in EPSO is obviously increased.
Infomax strategies for an optimal balance between exploration and exploitation
Reddy, Gautam; Vergassola, Massimo
2016-01-01
Proper balance between exploitation and exploration is what makes good decisions, which achieve high rewards like payoff or evolutionary fitness. The Infomax principle postulates that maximization of information directs the function of diverse systems, from living systems to artificial neural networks. While specific applications are successful, the validity of information as a proxy for reward remains unclear. Here, we consider the multi-armed bandit decision problem, which features arms (slot-machines) of unknown probabilities of success and a player trying to maximize cumulative payoff by choosing the sequence of arms to play. We show that an Infomax strategy (Info-p) which optimally gathers information on the highest mean reward among the arms saturates known optimal bounds and compares favorably to existing policies. The highest mean reward considered by Info-p is not the quantity actually needed for the choice of the arm to play, yet it allows for optimal tradeoffs between exploration and exploitation.
Optimal Constrained Resource Allocation Strategies under Low Risk Circumstances
Andreica, Mugurel Ionut; Visan, Costel
2009-01-01
In this paper we consider multiple constrained resource allocation problems, where the constraints can be specified by formulating activity dependency restrictions or by using game-theoretic models. All the problems are focused on generic resources, with a few exceptions which consider financial resources in particular. The problems consider low-risk circumstances and the values of the uncertain variables which are used by the algorithms are the expected values of the variables. For each of the considered problems we propose novel algorithmic solutions for computing optimal resource allocation strategies. The presented solutions are optimal or near-optimal from the perspective of their time complexity. The considered problems have applications in a broad range of domains, like workflow scheduling in industry (e.g. in the mining and metallurgical industry) or the financial sector, motion planning, facility location and data transfer or job scheduling and resource management in Grids, clouds or other distribute...
The optimization of operating parameters on microalgae upscaling process planning.
Ma, Yu-An; Huang, Hsin-Fu; Yu, Chung-Chyi
2016-03-01
The upscaling process planning developed in this study primarily involved optimizing operating parameters, i.e., dilution ratios, during process designs. Minimal variable cost was used as an indicator for selecting the optimal combination of dilution ratios. The upper and lower mean confidence intervals obtained from the actual cultured cell density data were used as the final cell density stability indicator after the operating parameters or dilution ratios were selected. The process planning method and results were demonstrated through three case studies of batch culture simulation. They are (1) final objective cell densities were adjusted, (2) high and low light intensities were used for intermediate-scale cultures, and (3) the number of culture days was expressed as integers for the intermediate-scale culture.
Wind farm operation planning using optimal pitch angle pattern (OPAP)
Energy Technology Data Exchange (ETDEWEB)
Moskalenko, Natalia S.; Rudion, K. [Magdeburg Univ. (Germany). Chair for Electric Power Networks and Renewable Energy Sources
2011-07-01
This paper presents the possibilities of optimal operation planning to maximize the energy production from a wind farm based on optimal pitch angle pattern (OPAP). The current status of this work is to investigate the influence of the pitch angle adaptation of single wind turbines (WTs) on the overall energy yield of the farm. The approach proposed in this paper assumes a selective change of the pitch angle of the chosen WTs from the optimal value, which corresponds to the maximal utilization of kinetic energy from the wind flow, in order to minimize wake effect influence on the overall energy yield of the farm. In this paper the fundamental assumptions of the proposed approach will be specified and the calculation algorithm will be presented. Furthermore, an exemplary test system will be defined and chosen scenarios will be calculated in order to show the potentials of the OPAP method. (orig.)
Optimal line drop compensation parameters under multi-operating conditions
Wan, Yuan; Li, Hang; Wang, Kai; He, Zhe
2017-01-01
Line Drop Compensation (LDC) is a main function of Reactive Current Compensation (RCC) which is developed to improve voltage stability. While LDC has benefit to voltage, it may deteriorate the small-disturbance rotor angle stability of power system. In present paper, an intelligent algorithm which is combined by Genetic Algorithm (GA) and Backpropagation Neural Network (BPNN) is proposed to optimize parameters of LDC. The objective function proposed in present paper takes consideration of voltage deviation and power system oscillation minimal damping ratio under multi-operating conditions. A simulation based on middle area of Jiangxi province power system is used to demonstrate the intelligent algorithm. The optimization result shows that coordinate optimized parameters can meet the multioperating conditions requirement and improve voltage stability as much as possible while guaranteeing enough damping ratio.
POSSIBILITIES FOR OPTIMIZATION OF CIRCUIT ACCELERATING OPERATION OF ELECTROMAGNETS
Directory of Open Access Journals (Sweden)
S. S. Stoyanova
2005-01-01
Full Text Available The paper reveals an accelerating circuit for electromagnet operation with the help of an additional resistor R that is shunted with a capacitor C. Resistor R is connected in series with the electromagnet winding. The possibility of the circuit optimization has been substantiated with the purpose to limit the final speed with which a movable part of the electromagnet reaches a limiter. Such circuit may find its application in relay protection.
Impact of Co-Operative Learning Strategies in English
Singaravelu, G.
2010-01-01
The study illuminates the effectiveness of Co-operative Learning Strategies in learning English Grammar for the learners at secondary level. Cooperative Learning is particularly beneficial for any student learning as a second language. It promotes peer interaction, which helps the development of language and the learning of concepts with content.…
Optimizing selection of decentralized stormwater management strategies in urbanized regions
Yu, Z.; Montalto, F.
2011-12-01
A variety of decentralized stormwater options are available for implementation in urbanized regions. These strategies, which include bio-retention, porous pavement, green roof etc., vary in terms of cost, ability to reduce runoff, and site applicability. This paper explores the tradeoffs between different types of stormwater control meastures that could be applied in a typical urban study area. A nested optimization strategy first identifies the most cost-effective (e.g. runoff reduction / life cycle cost invested ) options for individual land parcel typologies, and then scales up the results with detailed attention paid to uncertainty in adoption rates, life cycle costs, and hydrologic performance. The study is performed with a custom built stochastic rainfall-runoff model (Monte Carlo techniques are used to quantify uncertainties associated with phased implementation of different strategies and different land parcel typologies under synthetic precipitation ensembles). The results are presented as a comparison of cost-effectiveness over the time span of 30 years, and state an optimized strategy on the cumulative cost-effectiveness over the period.
VI International Workshop on Nature Inspired Cooperative Strategies for Optimization
Otero, Fernando; Masegosa, Antonio
2014-01-01
Biological and other natural processes have always been a source of inspiration for computer science and information technology. Many emerging problem solving techniques integrate advanced evolution and cooperation strategies, encompassing a range of spatio-temporal scales for visionary conceptualization of evolutionary computation. This book is a collection of research works presented in the VI International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO) held in Canterbury, UK. Previous editions of NICSO were held in Granada, Spain (2006 & 2010), Acireale, Italy (2007), Tenerife, Spain (2008), and Cluj-Napoca, Romania (2011). NICSO 2013 and this book provides a place where state-of-the-art research, latest ideas and emerging areas of nature inspired cooperative strategies for problem solving are vigorously discussed and exchanged among the scientific community. The breadth and variety of articles in this book report on nature inspired methods and applications such as Swarm In...
Operations Strategy and –Innovation? -A Contractor Implementing Lean
DEFF Research Database (Denmark)
Koch, Christian; Simonsen, Rolf
2006-01-01
Traditional strategic management and operations strategy wants us to believe that the implementation of management concepts is a simple strategic choice made by top managers. In this paper we introduce the story of Lean Construction entering into the organisation of a Danish contractor. Lean...... concepts. The paper presents findings from empirical work in collaboration with a large Danish contractor. The case is analysed from the perspective of operation strategy and political process. It is observed how the management concept is socially constructed and negotiated through political action of key...... actors/brokers and coalitions. Lean Construction is shaped in the process of emergence in the organisation, where also explicit corporate strategies and other initiatives of the organization interact with the concept and the actors and coalitions surrounding it. It is analysed how Lean Construction...
Formation of strategy and policy of banking credit operations management
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O.V. Lysenok
2016-03-01
Full Text Available The article examines the strategic management of credit operations as the activities on credit strategies of banking institutions, the formation of goals, objectives, and the choice of methods to achieve them. The basis of this is the strategic management analysis of the factors affecting the lending operations, strategic planning, communication mechanisms of strategic and tactical decisions, monitoring the implementation of the strategy and timely adjustments. For the purpose of effective implementation of the developed strategy, the article argues that banks in modern conditions should develop their own internal credit policy which should cover the essential elements and principles of credit at these banks. The study determines that the credit policy is based on the factors determined by the amount of capital assets and loan portfolio, the structure of its clientele, specialization, location, presence of branch network, the situation in the money market.
Tsai, Wen-Ping; Chang, Fi-John; Chang, Li-Chiu; Herricks, Edwin E.
2015-11-01
Flow regime is the key driver of the riverine ecology. This study proposes a novel hybrid methodology based on artificial intelligence (AI) techniques for quantifying riverine ecosystems requirements and delivering suitable flow regimes that sustain river and floodplain ecology through optimizing reservoir operation. This approach addresses issues to better fit riverine ecosystem requirements with existing human demands. We first explored and characterized the relationship between flow regimes and fish communities through a hybrid artificial neural network (ANN). Then the non-dominated sorting genetic algorithm II (NSGA-II) was established for river flow management over the Shihmen Reservoir in northern Taiwan. The ecosystem requirement took the form of maximizing fish diversity, which could be estimated by the hybrid ANN. The human requirement was to provide a higher satisfaction degree of water supply. The results demonstrated that the proposed methodology could offer a number of diversified alternative strategies for reservoir operation and improve reservoir operational strategies producing downstream flows that could meet both human and ecosystem needs. Applications that make this methodology attractive to water resources managers benefit from the wide spread of Pareto-front (optimal) solutions allowing decision makers to easily determine the best compromise through the trade-off between reservoir operational strategies for human and ecosystem needs.
Dynamic simulation and optimal real-time operation of CHP systems for buildings
Cho, Hee Jin
Combined Cooling, Heating, and Power (CHP) systems have been widely recognized as a key alternative for electric and thermal energy generation because of their outstanding energy efficiency, reduced environmental emissions, and relative independence from centralized power grids. The systems provide simultaneous onsite or near-site electric and thermal energy generation in a single, integrated package. As CHP becomes increasingly popular worldwide and its total capacity increases rapidly, the research on the topics of CHP performance assessment, design, and operational strategy become increasingly important. Following this trend of research activities to improve energy efficiency, environmental emissions, and operational cost, this dissertation focuses on the following aspects: (a) performance evaluation of a CHP system using a transient simulation model; (b) development of a dynamic simulation model of a power generation unit that can be effectively used in transient simulations of CHP systems; (c) investigation of real-time operation of CHP systems based on optimization with respect to operational cost, primary energy consumption, and carbon dioxide emissions; and (d) development of optimal supervisory feed-forward control that can provide realistic real-time operation of CHP systems with electric and thermal energy storages using short-term weather forecasting. The results from a transient simulation of a CHP system show that technical and economical performance can be readily evaluated using the transient model and that the design, component selection, and control of a CHP system can be improved using this model. The results from the case studies using optimal real-time operation strategies demonstrate that CHP systems with an energy dispatch algorithm have the potential to yield savings in operational cost, primary energy consumption, and carbon dioxide emissions with respect to a conventional HVAC system. Finally, the results from the case study using a
Directory of Open Access Journals (Sweden)
Dr.B.Subramanyam
2013-02-01
Full Text Available In this paper, Particle Swarm optimization(PSO and Artificial Bee Colony (ABC algorithms are used to determine the optimal bidding strategy in competitive auction market implementation. The deregulated power industry meets the challenges of increase their profits and also minimize the associadted risks of the system. Themarket includes generating companies(Gencos and large Consumers. The demand prediction of the system has been determined by the neural network, which is trained by using the previous day demand dataset, the training process is achieved by the back propagation algorithm. The fitness of the system compared with PSO and ABC technique, the maximized fitness is the optimal bidding strategy of the system . The results for two techniques will be analyzed in this paper. The implementation of the two techniques could be implemented in theMATLAB Platform.
Multi-objective nested algorithms for optimal reservoir operation
Delipetrev, Blagoj; Solomatine, Dimitri
2016-04-01
The optimal reservoir operation is in general a multi-objective problem, meaning that multiple objectives are to be considered at the same time. For solving multi-objective optimization problems there exist a large number of optimization algorithms - which result in a generation of a Pareto set of optimal solutions (typically containing a large number of them), or more precisely, its approximation. At the same time, due to the complexity and computational costs of solving full-fledge multi-objective optimization problems some authors use a simplified approach which is generically called "scalarization". Scalarization transforms the multi-objective optimization problem to a single-objective optimization problem (or several of them), for example by (a) single objective aggregated weighted functions, or (b) formulating some objectives as constraints. We are using the approach (a). A user can decide how many multi-objective single search solutions will generate, depending on the practical problem at hand and by choosing a particular number of the weight vectors that are used to weigh the objectives. It is not guaranteed that these solutions are Pareto optimal, but they can be treated as a reasonably good and practically useful approximation of a Pareto set, albeit small. It has to be mentioned that the weighted-sum approach has its known shortcomings because the linear scalar weights will fail to find Pareto-optimal policies that lie in the concave region of the Pareto front. In this context the considered approach is implemented as follows: there are m sets of weights {w1i, …wni} (i starts from 1 to m), and n objectives applied to single objective aggregated weighted sum functions of nested dynamic programming (nDP), nested stochastic dynamic programming (nSDP) and nested reinforcement learning (nRL). By employing the multi-objective optimization by a sequence of single-objective optimization searches approach, these algorithms acquire the multi-objective properties
Research of Ant Colony Optimized Adaptive Control Strategy for Hybrid Electric Vehicle
Directory of Open Access Journals (Sweden)
Linhui Li
2014-01-01
Full Text Available Energy management control strategy of hybrid electric vehicle has a great influence on the vehicle fuel consumption with electric motors adding to the traditional vehicle power system. As vehicle real driving cycles seem to be uncertain, the dynamic driving cycles will have an impact on control strategy’s energy-saving effect. In order to better adapt the dynamic driving cycles, control strategy should have the ability to recognize the real-time driving cycle and adaptively adjust to the corresponding off-line optimal control parameters. In this paper, four types of representative driving cycles are constructed based on the actual vehicle operating data, and a fuzzy driving cycle recognition algorithm is proposed for online recognizing the type of actual driving cycle. Then, based on the equivalent fuel consumption minimization strategy, an ant colony optimization algorithm is utilized to search the optimal control parameters “charge and discharge equivalent factors” for each type of representative driving cycle. At last, the simulation experiments are conducted to verify the accuracy of the proposed fuzzy recognition algorithm and the validity of the designed control strategy optimization method.
An Optimal Portfolio and Capital Management Strategy for Basel III Compliant Commercial Banks
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Grant E. Muller
2014-01-01
Full Text Available We model a Basel III compliant commercial bank that operates in a financial market consisting of a treasury security, a marketable security, and a loan and we regard the interest rate in the market as being stochastic. We find the investment strategy that maximizes an expected utility of the bank’s asset portfolio at a future date. This entails obtaining formulas for the optimal amounts of bank capital invested in different assets. Based on the optimal investment strategy, we derive a model for the Capital Adequacy Ratio (CAR, which the Basel Committee on Banking Supervision (BCBS introduced as a measure against banks’ susceptibility to failure. Furthermore, we consider the optimal investment strategy subject to a constant CAR at the minimum prescribed level. We derive a formula for the bank’s asset portfolio at constant (minimum CAR value and present numerical simulations on different scenarios. Under the optimal investment strategy, the CAR is above the minimum prescribed level. The value of the asset portfolio is improved if the CAR is at its (constant minimum value.
A Regional Time-of-Use Electricity Price Based Optimal Charging Strategy for Electrical Vehicles
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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.
Sobh, Tarek M.; Tibrewal, Abhilasha
2006-01-01
Operating systems theory primarily concentrates on the optimal use of computing resources. This paper presents an alternative approach to teaching and studying operating systems design and concepts by way of parametrically optimizing critical operating system functions. Detailed examples of two critical operating systems functions using the…
Optimal reservoir operation policies using novel nested algorithms
Delipetrev, Blagoj; Jonoski, Andreja; Solomatine, Dimitri
2015-04-01
Historically, the two most widely practiced methods for optimal reservoir operation have been dynamic programming (DP) and stochastic dynamic programming (SDP). These two methods suffer from the so called "dual curse" which prevents them to be used in reasonably complex water systems. The first one is the "curse of dimensionality" that denotes an exponential growth of the computational complexity with the state - decision space dimension. The second one is the "curse of modelling" that requires an explicit model of each component of the water system to anticipate the effect of each system's transition. We address the problem of optimal reservoir operation concerning multiple objectives that are related to 1) reservoir releases to satisfy several downstream users competing for water with dynamically varying demands, 2) deviations from the target minimum and maximum reservoir water levels and 3) hydropower production that is a combination of the reservoir water level and the reservoir releases. Addressing such a problem with classical methods (DP and SDP) requires a reasonably high level of discretization of the reservoir storage volume, which in combination with the required releases discretization for meeting the demands of downstream users leads to computationally expensive formulations and causes the curse of dimensionality. We present a novel approach, named "nested" that is implemented in DP, SDP and reinforcement learning (RL) and correspondingly three new algorithms are developed named nested DP (nDP), nested SDP (nSDP) and nested RL (nRL). The nested algorithms are composed from two algorithms: 1) DP, SDP or RL and 2) nested optimization algorithm. Depending on the way we formulate the objective function related to deficits in the allocation problem in the nested optimization, two methods are implemented: 1) Simplex for linear allocation problems, and 2) quadratic Knapsack method in the case of nonlinear problems. The novel idea is to include the nested
Harmonic component detection: Optimized Spectral Kurtosis for operational modal analysis
Dion, J.-L.; Tawfiq, I.; Chevallier, G.
2012-01-01
This work is a contribution in the field of Operational Modal Analysis to identify the modal parameters of mechanical structures using only measured responses. The study deals with structural responses coupled with harmonic components amplitude and frequency modulated in a short range, a common combination for mechanical systems with engines and other rotating machines in operation. These harmonic components generate misleading data interpreted erroneously by the classical methods used in OMA. The present work attempts to differentiate maxima in spectra stemming from harmonic components and structural modes. The detection method proposed is based on the so-called Optimized Spectral Kurtosis and compared with others definitions of Spectral Kurtosis described in the literature. After a parametric study of the method, a critical study is performed on numerical simulations and then on an experimental structure in operation in order to assess the method's performance.
Directory of Open Access Journals (Sweden)
A. M. Dalavi
2015-09-01
Full Text Available Optimization of hole-making operations plays a crucial role in which tool travel and tool switch scheduling are the two major issues. Industrial applications such as moulds, dies, engine block etc. consist of large number of holes having different diameters, depths and surface finish. This results into to a large number of machining operations like drilling, reaming or tapping to achieve the final size of individual hole. Optimal sequence of operations and associated cutting speeds, which reduce the overall processing cost of these hole-making operations are essential to reach desirable products. In order to achieve this, an attempt is made by developing an effective methodology. An example of the injection mould is considered to demonstrate the proposed approach. The optimization of this example is carried out using recently developed particle swarm optimization (PSO algorithm. The results obtained using PSO are compared with those obtained using tabu search method. It is observed that results obtained using PSO are slightly better than those obtained using tabu search method.
An integrated framework for gas turbine based power plant operational modeling and optimization
Zhao, Yongjun
The deregulation of the electric power market introduced a strong element of competition. Power plant operators strive to develop advanced operational strategies to maximize the profitability in the dynamic electric power market. New methodologies for gas turbine power plant operational modeling and optimization are needed for power plant operation to enhance operational decision making, and therefore to maximize power plant profitability by reducing operations and maintenance cost and increasing revenue. In this study, a profit based, lifecycle oriented, and unit specific methodology for gas turbine based power plant operational modeling was developed, with the power plant performance, reliability, maintenance, and market dynamics considered simultaneously. The generic methodology is applicable for a variety of optimization problems, and several applications were implemented using this method. A multiple time-scale method was developed for gas turbine power plants long term generation scheduling. This multiple time-scale approach allows combining the detailed granularity of the day-to-day operations with global (seasonal) trends, while keeping the resulting optimization model relatively compact. Using the multiple time-scale optimization method, a profit based outage planning method was developed, and the key factors for this profit based approach include power plant aging, performance degradation, reliability degradation, and, importantly, the energy market dynamics. Also a novel approach for gas turbine based power plant sequential preventive maintenance scheduling was introduced, and a profit based sequential preventive maintenance scheduling was developed for more effective maintenance scheduling. Methods to evaluate the impact of upgrade packages on gas turbine power plant performance, reliability, and economics were developed, and TIES methodology was applied for effective evaluation and selection of gas turbine power plant upgrade packages.
Energy Optimal Control Strategy of PHEV Based on PMP Algorithm
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Tiezhou Wu
2017-01-01
Full Text Available Under the global voice of “energy saving” and the current boom in the development of energy storage technology at home and abroad, energy optimal control of the whole hybrid electric vehicle power system, as one of the core technologies of electric vehicles, is bound to become a hot target of “clean energy” vehicle development and research. This paper considers the constraints to the performance of energy storage system in Parallel Hybrid Electric Vehicle (PHEV, from which lithium-ion battery frequently charges/discharges, PHEV largely consumes energy of fuel, and their are difficulty in energy recovery and other issues in a single cycle; the research uses lithium-ion battery combined with super-capacitor (SC, which is hybrid energy storage system (Li-SC HESS, working together with internal combustion engine (ICE to drive PHEV. Combined with PSO-PI controller and Li-SC HESS internal power limited management approach, the research proposes the PHEV energy optimal control strategy. It is based on revised Pontryagin’s minimum principle (PMP algorithm, which establishes the PHEV vehicle simulation model through ADVISOR software and verifies the effectiveness and feasibility. Finally, the results show that the energy optimization control strategy can improve the instantaneity of tracking PHEV minimum fuel consumption track, implement energy saving, and prolong the life of lithium-ion batteries and thereby can improve hybrid energy storage system performance.
Cost Effectiveness Analysis of Optimal Malaria Control Strategies in Kenya
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Gabriel Otieno
2016-03-01
Full Text Available Malaria remains a leading cause of mortality and morbidity among the children under five and pregnant women in sub-Saharan Africa, but it is preventable and controllable provided current recommended interventions are properly implemented. Better utilization of malaria intervention strategies will ensure the gain for the value for money and producing health improvements in the most cost effective way. The purpose of the value for money drive is to develop a better understanding (and better articulation of costs and results so that more informed, evidence-based choices could be made. Cost effectiveness analysis is carried out to inform decision makers on how to determine where to allocate resources for malaria interventions. This study carries out cost effective analysis of one or all possible combinations of the optimal malaria control strategies (Insecticide Treated Bednets—ITNs, Treatment, Indoor Residual Spray—IRS and Intermittent Preventive Treatment for Pregnant Women—IPTp for the four different transmission settings in order to assess the extent to which the intervention strategies are beneficial and cost effective. For the four different transmission settings in Kenya the optimal solution for the 15 strategies and their associated effectiveness are computed. Cost-effective analysis using Incremental Cost Effectiveness Ratio (ICER was done after ranking the strategies in order of the increasing effectiveness (total infections averted. The findings shows that for the endemic regions the combination of ITNs, IRS, and IPTp was the most cost-effective of all the combined strategies developed in this study for malaria disease control and prevention; for the epidemic prone areas is the combination of the treatment and IRS; for seasonal areas is the use of ITNs plus treatment; and for the low risk areas is the use of treatment only. Malaria transmission in Kenya can be minimized through tailor-made intervention strategies for malaria control
Braun, Robert Joseph
The advent of maturing fuel cell technologies presents an opportunity to achieve significant improvements in energy conversion efficiencies at many scales; thereby, simultaneously extending our finite resources and reducing "harmful" energy-related emissions to levels well below that of near-future regulatory standards. However, before realization of the advantages of fuel cells can take place, systems-level design issues regarding their application must be addressed. Using modeling and simulation, the present work offers optimal system design and operation strategies for stationary solid oxide fuel cell systems applied to single-family detached dwellings. A one-dimensional, steady-state finite-difference model of a solid oxide fuel cell (SOFC) is generated and verified against other mathematical SOFC models in the literature. Fuel cell system balance-of-plant components and costs are also modeled and used to provide an estimate of system capital and life cycle costs. The models are used to evaluate optimal cell-stack power output, the impact of cell operating and design parameters, fuel type, thermal energy recovery, system process design, and operating strategy on overall system energetic and economic performance. Optimal cell design voltage, fuel utilization, and operating temperature parameters are found using minimization of the life cycle costs. System design evaluations reveal that hydrogen-fueled SOFC systems demonstrate lower system efficiencies than methane-fueled systems. The use of recycled cell exhaust gases in process design in the stack periphery are found to produce the highest system electric and cogeneration efficiencies while achieving the lowest capital costs. Annual simulations reveal that efficiencies of 45% electric (LHV basis), 85% cogenerative, and simple economic paybacks of 5--8 years are feasible for 1--2 kW SOFC systems in residential-scale applications. Design guidelines that offer additional suggestions related to fuel cell
Hemoglobin optimization and transfusion strategies in patients undergoing cardiac surgery
Institute of Scientific and Technical Information of China (English)
Mahdi; Najafi; David; Faraoni
2015-01-01
Although red blood cells(RBCs) transfusion is sometimes associated with adverse reactions,anemia could also lead to increased morbidity and mortality in highrisk patients. For these reasons,the definition of perioperative strategies that aims to detect and treat preoperative anemia,prevent excessive blood loss,and define "optimal" transfusion algorithms is crucial. Although the treatment with preoperative iron and erythropoietin has been recommended in some specific conditions,several controversies exist regarding the benefit-to-risk balance associated with these treatments. Further studies are needed to better define the indications,dosage,and route of administration for preoperative iron with or without erythropoietin supplementation. Although restrictive transfusion strategies in patients undergoing cardiac surgery have been shown to effectively reduce the incidence and the amount of RBCs transfusion without increase in side effects,some high-risk patients(e.g.,symptomatic acute coronary syndrome) could benefit from higher hemoglobin concentrations. Despite all efforts made last decade,a significant amount of work remains to be done to improve hemoglobin optimization and transfusion strategies in patients undergoing cardiac surgery.
Evolving Nash-optimal poker strategies using evolutionary computation
Institute of Scientific and Technical Information of China (English)
Hanyang QUEK; Chunghoong WOO; Kaychen TAN; Arthur TAY
2009-01-01
This paper focuses on the development of a competitive computer player for the one versus one Texas Hold'em poker using evolutionary algorithms (EA). A Texas Hold'em game engine is first constructed where an efficient odds" calculator is programmed to allow for the abstraction of a player's cards, which yield important but complex information. Effort is directed to realize an optimal player that will play close to the Nash equilibrium (NE) by proposing a new fitness criterion. Preliminary studies on a simplified version of poker highlighted the intransitivity nature of poker.The evolved player displays strategies that are logical but reveals insights that are hard to comprehend e.g., bluffing.The player is then benchmarked against Poki and PSOpti,which is the best heads-up Texas Hold'em artificial intelligence to date and plays closest to the optimal Nash equilibrium. Despite the much constrained chromosomal strategy representation, simulated results verified that evolutionary algorithms are effective in creating strategies that are comparable to Poki and PSOpti in the absence of expert knowledge.
Nonlinear Burn Control and Operating Point Optimization in ITER
Boyer, Mark; Schuster, Eugenio
2013-10-01
Control of the fusion power through regulation of the plasma density and temperature will be essential for achieving and maintaining desired operating points in fusion reactors and burning plasma experiments like ITER. In this work, a volume averaged model for the evolution of the density of energy, deuterium and tritium fuel ions, alpha-particles, and impurity ions is used to synthesize a multi-input multi-output nonlinear feedback controller for stabilizing and modulating the burn condition. Adaptive control techniques are used to account for uncertainty in model parameters, including particle confinement times and recycling rates. The control approach makes use of the different possible methods for altering the fusion power, including adjusting the temperature through auxiliary heating, modulating the density and isotopic mix through fueling, and altering the impurity density through impurity injection. Furthermore, a model-based optimization scheme is proposed to drive the system as close as possible to desired fusion power and temperature references. Constraints are considered in the optimization scheme to ensure that, for example, density and beta limits are avoided, and that optimal operation is achieved even when actuators reach saturation. Supported by the NSF CAREER award program (ECCS-0645086).
Optimization strategy for element sizing in hybrid power systems
del Real, Alejandro J.; Arce, Alicia; Bordons, Carlos
This paper presents a procedure to evaluate the optimal element sizing of hybrid power systems. In order to generalize the problem, this work exploits the "energy hub" formulation previously presented in the literature, defining an energy hub as an interface among energy producers, consumers and the transportation infrastructure. The resulting optimization minimizes an objective function which is based on costs and efficiencies of the system elements, while taking into account the hub model, energy and power constraints and estimated operational conditions, such as energy prices, input power flow availability and output energy demand. The resulting optimal architecture also constitutes a framework for further real-time control designs. Moreover, an example of a hybrid storage system is considered. In particular, the architecture of a hybrid plant incorporating a wind generator, batteries and intermediate hydrogen storage is optimized, based on real wind data and averaged residential demands, also taking into account possible estimation errors. The hydrogen system integrates an electrolyzer, a fuel cell stack and hydrogen tanks. The resulting optimal cost of such hybrid power plant is compared with the equivalent hydrogen-only and battery-only systems, showing improvements in investment costs of almost 30% in the worst case.
Optimization strategy for element sizing in hybrid power systems
Energy Technology Data Exchange (ETDEWEB)
del Real, Alejandro J.; Arce, Alicia; Bordons, Carlos [Departamento de Ingenieria de Sistemas y Automatica, Universidad de Sevilla, 41092 Sevilla (Spain)
2009-08-01
This paper presents a procedure to evaluate the optimal element sizing of hybrid power systems. In order to generalize the problem, this work exploits the ''energy hub'' formulation previously presented in the literature, defining an energy hub as an interface among energy producers, consumers and the transportation infrastructure. The resulting optimization minimizes an objective function which is based on costs and efficiencies of the system elements, while taking into account the hub model, energy and power constraints and estimated operational conditions, such as energy prices, input power flow availability and output energy demand. The resulting optimal architecture also constitutes a framework for further real-time control designs. Moreover, an example of a hybrid storage system is considered. In particular, the architecture of a hybrid plant incorporating a wind generator, batteries and intermediate hydrogen storage is optimized, based on real wind data and averaged residential demands, also taking into account possible estimation errors. The hydrogen system integrates an electrolyzer, a fuel cell stack and hydrogen tanks. The resulting optimal cost of such hybrid power plant is compared with the equivalent hydrogen-only and battery-only systems, showing improvements in investment costs of almost 30% in the worst case. (author)
PLIO: a generic tool for real-time operational predictive optimal control of water networks.
Cembrano, G; Quevedo, J; Puig, V; Pérez, R; Figueras, J; Verdejo, J M; Escaler, I; Ramón, G; Barnet, G; Rodríguez, P; Casas, M
2011-01-01
This paper presents a generic tool, named PLIO, that allows to implement the real-time operational control of water networks. Control strategies are generated using predictive optimal control techniques. This tool allows the flow management in a large water supply and distribution system including reservoirs, open-flow channels for water transport, water treatment plants, pressurized water pipe networks, tanks, flow/pressure control elements and a telemetry/telecontrol system. Predictive optimal control is used to generate flow control strategies from the sources to the consumer areas to meet future demands with appropriate pressure levels, optimizing operational goals such as network safety volumes and flow control stability. PLIO allows to build the network model graphically and then to automatically generate the model equations used by the predictive optimal controller. Additionally, PLIO can work off-line (in simulation) and on-line (in real-time mode). The case study of Santiago-Chile is presented to exemplify the control results obtained using PLIO off-line (in simulation).
Optimal Bidding of a Microgrid Based on Probabilistic Analysis of Island Operation
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Siyoung Lee
2016-10-01
Full Text Available Island operation of a microgrid increases operation survivability and reliability when there is a large accident in a main grid. However, because a microgrid typically has limited generation capability, a microgrid operator (MGO has to take the risk of island operation into account in its market participation and generation scheduling to ensure efficient operation. In this paper, a microgrid islanding event is interpreted as a trade suspension of a contract, and a set of islanding rules is presented in the form of a market rule. The risk of island operation is evaluated by modeling the microgrid islanding stochastically using an islanding probability function, which is defined in the form of a conditional probability to reflect the influence of outside conditions. An optimal bidding strategy is obtained for the MGO by formulating and solving an optimization problem to minimize the expected operating cost. The effectiveness of the proposed method was investigated by numerical simulations in which the proposed method and two other methods were applied to the same microgrid. Numerical sensitivity analyses of the coefficients of the islanding probability function were conducted to determine how an MGO copes with changes in outside conditions.
Optimal Constant DC Link Voltage Operation of aWave Energy Converter
Directory of Open Access Journals (Sweden)
Mats Leijon
2013-04-01
Full Text Available This article proposes a simple and reliable damping strategy for wave powerfarm operation of small-scale point-absorber converters. The strategy is based on passiverectification onto a constant DC-link, making it very suitable for grid integration of the farm.A complete model of the system has been developed in Matlab Simulink, and uses real sitedata as input. The optimal constant DC-voltage is evaluated as a function of the significantwave height and energy period of the waves. The total energy output of the WEC is derivedfor one year of experimental site data. The energy output is compared for two cases, onewhere the optimal DC-voltage is determined and held constant at half-hour basis throughoutthe year, and one where a selected value of the DC-voltage is kept constant throughout theyear regardless of sea state.
Cheng, Wei-Chen; Hsu, Nien-Sheng; Cheng, Wen-Ming; Yeh, William W.-G.
2011-10-01
This paper develops alternative strategies for European call options for water purchase under hydrological uncertainties that can be used by water resources managers for decision making. Each alternative strategy maximizes its own objective over a selected sequence of future hydrology that is characterized by exceedance probability. Water trade provides flexibility and enhances water distribution system reliability. However, water trade between two parties in a regional water distribution system involves many issues, such as delivery network, reservoir operation rules, storage space, demand, water availability, uncertainty, and any existing contracts. An option is a security giving the right to buy or sell an asset; in our case, the asset is water. We extend a flow path-based water distribution model to include reservoir operation rules. The model simultaneously considers both the physical distribution network as well as the relationships between water sellers and buyers. We first test the model extension. Then we apply the proposed optimization model for European call options to the Tainan water distribution system in southern Taiwan. The formulation lends itself to a mixed integer linear programming model. We use the weighing method to formulate a composite function for a multiobjective problem. The proposed methodology provides water resources managers with an overall picture of water trade strategies and the consequence of each strategy. The results from the case study indicate that the strategy associated with a streamflow exceedence probability of 50% or smaller should be adopted as the reference strategy for the Tainan water distribution system.
Computer teaching process optimization strategy analysis of thinking ability
Directory of Open Access Journals (Sweden)
Luo Liang
2016-01-01
Full Text Available As is known to all, computer is a college student in a university course, one of the basic course in the process of education for college students which lay a theoretical foundation for the next professional learning. At the same time, in recent years, countries and universities attach great importance to and focus on computer teaching for young college students, the purpose is to improve students’ thinking ability, eventually to promote college students’ ability to use computational thinking to solve and analyze the problems of daily life. Therefore, this article on how to the calculation of optimization in the process of computer teaching college students thinking ability on further discussion and analysis, and then explore the strategies and methods, so as to promote the computer teaching in the process of the cultivation of thinking ability and optimize the computer
Strategy of Concurrent Optimization for an Assembly Sequence
Institute of Scientific and Technical Information of China (English)
YANG Bo; LIU Lu-ning; ZE Xiang-bo
2005-01-01
An effective constraint release based approach to realize concurrent optimization for an assembly sequence is proposed. To quantify the measurement of assembly efficiency, a mathematical model of concurrency evaluation index was put forward at first, and then a technology to quantify assembly constraints was developed by application of some fuzzy logic algorithms. In the process of concurrent optimization of the assembly sequence, two kinds of constraints were involved. One was self-constraints of components, which was used to evaluate the assemble capability of components under the condition of full-freedom. Another was an assembly constraint between components represented by geometric constraints between points, lines and planes under physical restriction conditions. The concept of connection strength degree (CSD) was introduced as one efficient indicator and the value of it was evaluated by the intersection of the two constraints mentioned above. The equivalent constraints describing the connection weights between components were realized by a well designed constraints reduction, and then the connection weights based complete assembly liaison graph was applied to release virtual connections between components. Under a given threshold value, a decomposition and reconstituting strategy for the graph with the focus on high assembly concurrency was used to realize an optimized assembly concurrency evaluation index. Finally, the availability of the approach was illustrated in an example to optimize the assembly of a shift pump.
Design of an operational transconductance amplifier applying multiobjective optimization techniques
Directory of Open Access Journals (Sweden)
Roberto Pereira-Arroyo
2014-02-01
Full Text Available In this paper, the problem at hand consists in the sizing of an Operational Transconductance Amplifier (OTA. The Pareto front is introduced as a useful analysis concept in order to explore the design space of such analog circuit. A genetic algorithm (GA is employed to automatically detect this front in a process that efficiently finds optimal parameterizations and their corresponding values in an aggregate fitness space. Since the problem is treated as a multi-objective optimization task, different measures of the amplifier like the transconductance, the slew rate, the linear range and the input capacitance are used as fitness functions. Finally, simulation results are presented, using a standard 0,5μm CMOS technology.
Optimized Algorithms for Prediction within Robotic Tele-Operative Interfaces
Martin, Rodney A.; Wheeler, Kevin R.; SunSpiral, Vytas; Allan, Mark B.
2006-01-01
Robonaut, the humanoid robot developed at the Dexterous Robotics Laboratory at NASA Johnson Space Center serves as a testbed for human-robot collaboration research and development efforts. One of the primary efforts investigates how adjustable autonomy can provide for a safe and more effective completion of manipulation-based tasks. A predictive algorithm developed in previous work was deployed as part of a software interface that can be used for long-distance tele-operation. In this paper we provide the details of this algorithm, how to improve upon the methods via optimization, and also present viable alternatives to the original algorithmic approach. We show that all of the algorithms presented can be optimized to meet the specifications of the metrics shown as being useful for measuring the performance of the predictive methods. Judicious feature selection also plays a significant role in the conclusions drawn.
Process of Market Strategy Optimization Using Distributed Computing Systems
Directory of Open Access Journals (Sweden)
Nowicki Wojciech
2015-12-01
Full Text Available If market repeatability is assumed, it is possible with some real probability to deduct short term market changes by making some calculations. The algorithm, based on logical and statistically reasonable scheme to make decisions about opening or closing position on a market, is called an automated strategy. Due to market volatility, all parameters are changing from time to time, so there is need to constantly optimize them. This article describes a team organization process when researching market strategies. Individual team members are merged into small groups, according to their responsibilities. The team members perform data processing tasks through a cascade organization, providing solutions to speed up work related to the use of remote computing resources. They also work out how to store results in a suitable way, according to the type of task, and facilitate the publication of a large amount of results.
Sequential optimizing strategy in multi-dimensional bounded forecasting games
Kumon, Masayuki; Takeuchi, Kei
2009-01-01
We propose a sequential optimizing betting strategy in the multi-dimensional bounded forecasting game in the framework of game-theoretic probability of Shafer and Vovk (2001). By studying the asymptotic behavior of its capital process, we prove a generalization of the strong law of large numbers, where the convergence rate of the sample mean vector depends on the growth rate of the quadratic variation process. The growth rate of the quadratic variation process may be slower than the number of rounds or may even be zero. We also introduce an information criterion for selecting efficient betting items. These results are then applied to multiple asset trading strategies in discrete-time and continuous-time games. In the case of continuous-time game we present a measure of the jaggedness of a vector-valued continuous process. Our results are examined by several numerical examples.
Directory of Open Access Journals (Sweden)
Carmen Fullana-Belda
2013-10-01
Full Text Available Traditional uneven-aged forest management seeks a balance between equilibrium stand structure and economic profitability, which often leads to harvesting strategies concentrated in the larger diameter classes. The sustainability (i.e., population persistence over time and influence of such economically optimal strategies on the equilibrium position of a stand (given by the stable diameter distribution have not been sufficiently investigated in prior forest literature. This article therefore proposes a discrete optimal control model to analyze the sustainability and stability of the economically optimal harvesting strategies of uneven-aged Pinus nigra stands. For this model, we rely on an objective function that integrates financial data of harvesting operations with a projection matrix model that can describe the population dynamics. The model solution reveals the optimal management schedules for a wide variety of scenarios. To measure the distance between the stable diameter distribution and the economically optimal harvesting strategy distribution, the model uses Keyfitz’s delta, which returns high values for all the scenarios and, thus, suggests that those economically optimal harvesting strategies have an unstabilizing influence on the equilibrium positions. Moreover, the economically optimal harvesting strategies were unsustainable for all the scenarios.
An intelligent factory-wide optimal operation system for continuous production process
Ding, Jinliang; Chai, Tianyou; Wang, Hongfeng; Wang, Junwei; Zheng, Xiuping
2016-03-01
In this study, a novel intelligent factory-wide operation system for a continuous production process is designed to optimise the entire production process, which consists of multiple units; furthermore, this system is developed using process operational data to avoid the complexity of mathematical modelling of the continuous production process. The data-driven approach aims to specify the structure of the optimal operation system; in particular, the operational data of the process are used to formulate each part of the system. In this context, the domain knowledge of process engineers is utilised, and a closed-loop dynamic optimisation strategy, which combines feedback, performance prediction, feed-forward, and dynamic tuning schemes into a framework, is employed. The effectiveness of the proposed system has been verified using industrial experimental results.
Operations Strategy and –Innovation? -A Contractor Implementing Lean
DEFF Research Database (Denmark)
Koch, Christian; Simonsen, Rolf
2006-01-01
concepts. The paper presents findings from empirical work in collaboration with a large Danish contractor. The case is analysed from the perspective of operation strategy and political process. It is observed how the management concept is socially constructed and negotiated through political action of key......Traditional strategic management and operations strategy wants us to believe that the implementation of management concepts is a simple strategic choice made by top managers. In this paper we introduce the story of Lean Construction entering into the organisation of a Danish contractor. Lean...... Construction is viewed as a management concept and the journey into the construction company witness not only that top management is very little involved, but also that the concept is negotiated and promoted by a number of actors and coalitions competing for attention and resources with a number of other...
Geometric Process-Based Maintenance and Optimization Strategy for the Energy Storage Batteries
Directory of Open Access Journals (Sweden)
Yan Li
2016-01-01
Full Text Available Renewable energy is critical for improving energy structure and reducing environment pollution. But its strong fluctuation and randomness have a serious effect on the stability of the microgrid without the coordination of the energy storage batteries. The main factors that influence the development of the energy storage system are the lack of valid operation and maintenance management as well as the cost control. By analyzing the typical characteristics of the energy storage batteries in their life cycle, the geometric process-based model including the deteriorating system and the improving system is firstly built for describing the operation process, the preventive maintenance process, and the corrective maintenance process. In addition, this paper proposes an optimized management strategy, which aims to minimize the long-run average cost of the energy storage batteries by defining the time interval of the detection and preventive maintenance process as well as the optimal corrective maintenance times, subjected to the state of health and the reliability conditions. The simulation is taken under the built model by applying the proposed energy storage batteries’ optimized management strategy, which verifies the effectiveness and applicability of the management strategy, denoting its obvious practicality on the current application.
Optimal operation of integrated processes. Studies on heat recovery systems
Energy Technology Data Exchange (ETDEWEB)
Glemmestad, Bjoern
1997-12-31
Separators, reactors and a heat exchanger network (HEN) for heat recovery are important parts of an integrated plant. This thesis deals with the operation of HENs, in particular, optimal operation. The purpose of heat integration is to save energy, but the HEN also introduces new interactions and feedback into the overall plant. A prerequisite for optimisation is that there are extra degrees of freedom left after regulatory control is implemented. It is shown that extra degrees of freedom may not always be utilized for energy optimisation, and a quantitative expression for the degrees of freedom that can be so utilized are presented. A simplified expression that is often valid is also deduced. The thesis presents some improvements and generalisations of a structure based method that has been proposed earlier. Structural information is used to divide possible manipulations into three categories depending on how each manipulation affects the utility consumption. By means of these categories and two heuristic rules for operability, the possible manipulations are ordered in a priority table. This table is used to determine which manipulation should be preferred and which manipulation should be selected if an active manipulation is saturated. It is shown that the method may correspond to split-range control. A method that uses parametric information in addition to structural information is proposed. In this method, the optimal control structure is found through solving an integer programming problem. The thesis also proposes a method that combines the use of steady state optimisation and optimal selection of measurements. 86 refs., 46 figs., 8 tabs.
Operational Strategy of CBPs for load balancing of Operators in Advanced Main Control Room
Energy Technology Data Exchange (ETDEWEB)
Kim, Seunghwan; Kim, Yochan; Jung, Wondea [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2014-05-15
With the using of a computer-based control room in an APR1400 (Advanced Pressurized Reactor-1400), the operators' behaviors in the main control room had changed. However, though the working environment of operators has been changed a great deal, digitalized interfaces can also change the cognitive tasks or activities of operators. First, a shift supervisor (SS) can confirm/check the conduction of the procedures and the execution of actions of board operators (BOs) while confirming directly the operation variables without relying on the BOs. Second, all operators added to their work the use of a new CBP and Soft Controls, increasing their procedural workload. New operational control strategies of CBPs are necessary for load balancing of operator's task load in APR1400. In this paper, we compared the workloads of operators in an APR1400 who work with two different usages of the CBP. They are SS oriented usage and SS-BO collaborative usage. In this research, we evaluated the workloads of operators in an advanced main control room by the COCOA method. Two types of CBP usages were defined and the effects of these usages on the workloads were investigated. The obtained results showed that the workloads between operators in a control room can be balanced according to the CBP usages by assigning control authority to the operators.
Determining the Bayesian optimal sampling strategy in a hierarchical system.
Energy Technology Data Exchange (ETDEWEB)
Grace, Matthew D.; Ringland, James T.; Boggs, Paul T.; Pebay, Philippe Pierre
2010-09-01
Consider a classic hierarchy tree as a basic model of a 'system-of-systems' network, where each node represents a component system (which may itself consist of a set of sub-systems). For this general composite system, we present a technique for computing the optimal testing strategy, which is based on Bayesian decision analysis. In previous work, we developed a Bayesian approach for computing the distribution of the reliability of a system-of-systems structure that uses test data and prior information. This allows for the determination of both an estimate of the reliability and a quantification of confidence in the estimate. Improving the accuracy of the reliability estimate and increasing the corresponding confidence require the collection of additional data. However, testing all possible sub-systems may not be cost-effective, feasible, or even necessary to achieve an improvement in the reliability estimate. To address this sampling issue, we formulate a Bayesian methodology that systematically determines the optimal sampling strategy under specified constraints and costs that will maximally improve the reliability estimate of the composite system, e.g., by reducing the variance of the reliability distribution. This methodology involves calculating the 'Bayes risk of a decision rule' for each available sampling strategy, where risk quantifies the relative effect that each sampling strategy could have on the reliability estimate. A general numerical algorithm is developed and tested using an example multicomponent system. The results show that the procedure scales linearly with the number of components available for testing.
Environmental operations strategies: European approaches and research challenges
Álvarez Gil, María José; Rivera Camino, Jaime
1998-01-01
Since the environment has very recently emerged as a strategic issue, work has only begun to investigate the conceptual linkages between strategic management and the environment. A thoroughly revision of both academic and professional literature evidences that such scarcity of research doubles, or even trebles, when the scenery of the European Operations Management Strategies is considered. The main objective of this paper is, therefore, to discuss the impact of the design of the environmenta...
Operational strategies for contamination control of composite materials
Hansen, Patricia A.
1992-01-01
Composite materials, used on many instruments, are a potential contamination source for sensitive sensors, especially for sensors or detectors cooled below -80 C. It is a well known fact that composite materials absorb water during fabrication, integration, test, and launch activities and desorb this water under vacuum conditions. Water absorption can be divided into two types: shallow water and deep water. Shallow water is generally about 500 A thick on a clean material surface and is easily desorbed under vacuum conditions. Deep water is a function of the material and is absorbed into the bulk of the material. Deep water can outgas for weeks, months, or years, depending on the vent path, the amount of absorbed water, and the temperature of the material. Several operational strategies have been successfully employed on the Wide Field Planetary Camera. The operational strategies include ultradry gaseous nitrogen purge, dew point of less than -80 C, and vacuum bake-out with verification of outgassing rates. The nitrogen purge is instituted during the fabrication phase and is continued through launch activities. Great care is taken to avoid extended periods of time that the material is exposed to the ambient environment (50 percent relative humidity). On-orbit operational strategies include heat-up and cool-down scenarios which allow the deep water to be sufficiently outgassed before cooling the sensors or detectors.
Optimized green operation of LTE networks in the presence of multiple electricity providers
Ghazzai, Hakim
2012-12-01
Energy efficiency aspects in cellular networks can significantly contribute to the reduction of greenhouse gas emissions and help to save the environment. The base station (BS) sleeping strategy has become a well-known technique to achieve energy savings by switching off redundant BSs mainly for lightly loaded networks. Besides, introducing renewable energies as alternative power sources becomes a real challenge to network operators. In this paper, we propose a method that reduces the energy consumption of BSs by not only shutting down underutilized BSs but also by optimizing the amounts of energy procured from different retailers (Renewable energy and electricity retailers). We formulate an optimization problem that leads to the maximization of the profit of a Long-Term Evolution (LTE) cellular operator, and at the same time to the minimization of CO2 emissions in green wireless cellular networks without affecting the desired Quality of Service. © 2012 IEEE.
Optimizing Wellfield Operation in a Variable Power Price Regime
DEFF Research Database (Denmark)
Bauer-Gottwein, Peter; Schneider, Raphael; Davidsen, Claus
2016-01-01
of operating the combined wellfield-storage-demand system over the course of a 2-year planning period based on a time series of observed price on the Danish power market and a deterministic, time-varying hourly water demand. In the SDP setup, hourly pumping rates are the decision variables. Constraints include......-rate pumping benchmark. Minor savings up to 10% were found in the baseline scenario, while the scenario with constant EFP and unlimited pumping rate resulted in savings up to 40%. Key factors determining potential cost savings obtained by flexible wellfield operation under a variable power price regime......Wellfield management is a multiobjective optimization problem. One important objective has been energy efficiency in terms of minimizing the energy footprint (EFP) of delivered water (MWh/m3). However, power systems in most countries are moving in the direction of deregulated markets and price...
Energy Technology Data Exchange (ETDEWEB)
Boonchuay, Chanwit [Energy Field of Study, School of Environment, Resources and Development, Asian Institute of Technology (Thailand); Ongsakul, Weerakorn, E-mail: ongsakul@ait.asi [Energy Field of Study, School of Environment, Resources and Development, Asian Institute of Technology (Thailand)
2011-02-15
In this paper, an optimal risky bidding strategy for a generating company (GenCo) by self-organising hierarchical particle swarm optimisation with time-varying acceleration coefficients (SPSO-TVAC) is proposed. A significant risk index based on mean-standard deviation ratio (MSR) is maximised to provide the optimal bid prices and quantities. The Monte Carlo (MC) method is employed to simulate rivals' behaviour in competitive environment. Non-convex operating cost functions of thermal generating units and minimum up/down time constraints are taken into account. The proposed bidding strategy is implemented in a multi-hourly trading in a uniform price spot market and compared to other particle swarm optimisation (PSO). Test results indicate that the proposed SPSO-TVAC approach can provide a higher MSR than the other PSO methods. It is potentially applicable to risk management of profit variation of GenCo in spot market.
Directory of Open Access Journals (Sweden)
Vesna Tornjanski
2017-02-01
Full Text Available This paper sets out to extend and deepen the understanding the ways toward economic sustainability through efficient and effective growth operations strategies, quality management and operational excellence in banking. In this study we define new quality management practices based on developed conceptual architecture of digital platform for operations function in banking. Additionally, we employ decision making framework consisted of two parts: introduction of new operations services using Total Unduplicated Reach and Frequency (TURF statistical analysis and segregation of core from actual and augmented operations services utilizing Analytic Network Process (ANP method based on BOCR model. Proposed quality management practices were used for the first time in this paper for particular purposes and have the high potential to impact the excellence in banking business. The study can contribute to operations management, quality management, innovation management, IT management, business process management and decision making in service organizations.
Optimal Operation of Network-Connected Combined Heat and Powers for Customer Profit Maximization
Directory of Open Access Journals (Sweden)
Da Xie
2016-06-01
Full Text Available Network-connected combined heat and powers (CHPs, owned by a community, can export surplus heat and electricity to corresponding heat and electric networks after community loads are satisfied. This paper proposes a new optimization model for network-connected CHP operation. Both CHPs’ overall efficiency and heat to electricity ratio (HTER are assumed to vary with loading levels. Based on different energy flow scenarios where heat and electricity are exported to the network from the community or imported, four profit models are established accordingly. They reflect the different relationships between CHP energy supply and community load demand across time. A discrete optimization model is then developed to maximize the profit for the community. The models are derived from the intervals determined by the daily operation modes of CHP and real-time buying and selling prices of heat, electricity and natural gas. By demonstrating the proposed models on a 1 MW network-connected CHP, results show that the community profits are maximized in energy markets. Thus, the proposed optimization approach can help customers to devise optimal CHP operating strategies for maximizing benefits.
Taxing Strategies for Carbon Emissions: A Bilevel Optimization Approach
Directory of Open Access Journals (Sweden)
Wei Wei
2014-04-01
Full Text Available This paper presents a quantitative and computational method to determine the optimal tax rate among generating units. To strike a balance between the reduction of carbon emission and the profit of energy sectors, the proposed bilevel optimization model can be regarded as a Stackelberg game between the government agency and the generation companies. The upper-level, which represents the government agency, aims to limit total carbon emissions within a certain level by setting optimal tax rates among generators according to their emission performances. The lower-level, which represents decision behaviors of the grid operator, tries to minimize the total production cost under the tax rates set by the government. The bilevel optimization model is finally reformulated into a mixed integer linear program (MILP which can be solved by off-the-shelf MILP solvers. Case studies on a 10-unit system as well as a provincial power grid in China demonstrate the validity of the proposed method and its capability in practical applications.
Directory of Open Access Journals (Sweden)
Mohammad Aghaei
2013-10-01
Full Text Available To maintain and achieve optimal growth, development and to be more competitive, organizations need a comprehensive and coherent plan compatible with their objectives and goals which is called strategic planning. This research aims to analyse strategically “Etka Chain Stores” and to propose optimal strategies by using SWOT model and based on fuzzy logic. The scope of this research is limited to “Etka Chain stores in Tehran”. As instrumentation, a questioner, consisting of 138 questions, was used. The data have been extracted from interviews to managers and the expert in Etka Chain stores and from studying the available reports in the organization. Validity and reliability of research have been measured. The research consists of two main and four subsidiary questions and lacks hypothesis and regarding type of the objective, this research is an applied one and regarding the data gathering, it is experimental-descriptive and a case study. Analysing the data consists of five steps. In the first step, all the documents, interviews to organization experts and “Etka Chain stores” reports were analysed by tests and a list of environmental opportunities and threats together with strengths and weaknesses was prepared. In the second step, all the above-mentioned factors were screened and opportunities, threats, strengths and weaknesses were identified. In the third stage, by using key factors and SWOT model, the most suitable strategies for the company have been proposed. In the fifth step, an operational program is proposed. The findings of the research indicate that to be more competitive in key axis which includes customers, supply chain, expanses control, competitive smartness, human resources and operational productivity, the company should adopt suitable strategies. In this regard, the suitable strategies were identified, codified and proposed. In this research, planning a strategic management model, analysing value chain for spotting
Infomax Strategies for an Optimal Balance Between Exploration and Exploitation
Reddy, Gautam; Celani, Antonio; Vergassola, Massimo
2016-06-01
Proper balance between exploitation and exploration is what makes good decisions that achieve high reward, like payoff or evolutionary fitness. The Infomax principle postulates that maximization of information directs the function of diverse systems, from living systems to artificial neural networks. While specific applications turn out to be successful, the validity of information as a proxy for reward remains unclear. Here, we consider the multi-armed bandit decision problem, which features arms (slot-machines) of unknown probabilities of success and a player trying to maximize cumulative payoff by choosing the sequence of arms to play. We show that an Infomax strategy (Info-p) which optimally gathers information on the highest probability of success among the arms, saturates known optimal bounds and compares favorably to existing policies. Conversely, gathering information on the identity of the best arm in the bandit leads to a strategy that is vastly suboptimal in terms of payoff. The nature of the quantity selected for Infomax acquisition is then crucial for effective tradeoffs between exploration and exploitation.
Optimal measurement strategies for effective suppression of drift errors
Energy Technology Data Exchange (ETDEWEB)
Yashchuk, Valeriy V.
2009-04-16
Drifting of experimental set-ups with change of temperature or other environmental conditions is the limiting factor of many, if not all, precision measurements. The measurement error due to a drift is, in some sense, in-between random noise and systematic error. In the general case, the error contribution of a drift cannot be averaged out using a number of measurements identically carried out over a reasonable time. In contrast to systematic errors, drifts are usually not stable enough for a precise calibration. Here a rather general method for effective suppression of the spurious effects caused by slow drifts in a large variety of instruments and experimental set-ups is described. An analytical derivation of an identity, describing the optimal measurement strategies suitable for suppressing the contribution of a slow drift described with a certain order polynomial function, is presented. A recursion rule as well as a general mathematical proof of the identity is given. The effectiveness of the discussed method is illustrated with an application of the derived optimal scanning strategies to precise surface slope measurements with a surface profiler.
Web malware spread modelling and optimal control strategies
Liu, Wanping; Zhong, Shouming
2017-02-01
The popularity of the Web improves the growth of web threats. Formulating mathematical models for accurate prediction of malicious propagation over networks is of great importance. The aim of this paper is to understand the propagation mechanisms of web malware and the impact of human intervention on the spread of malicious hyperlinks. Considering the characteristics of web malware, a new differential epidemic model which extends the traditional SIR model by adding another delitescent compartment is proposed to address the spreading behavior of malicious links over networks. The spreading threshold of the model system is calculated, and the dynamics of the model is theoretically analyzed. Moreover, the optimal control theory is employed to study malware immunization strategies, aiming to keep the total economic loss of security investment and infection loss as low as possible. The existence and uniqueness of the results concerning the optimality system are confirmed. Finally, numerical simulations show that the spread of malware links can be controlled effectively with proper control strategy of specific parameter choice.
Applications of Optimal Building Energy System Selection and Operation
Energy Technology Data Exchange (ETDEWEB)
Marnay, Chris; Stadler, Michael; Siddiqui, Afzal; DeForest, Nicholas; Donadee, Jon; Bhattacharya, Prajesh; Lai, Judy
2011-04-01
Berkeley Lab has been developing the Distributed Energy Resources Customer Adoption Model (DER-CAM) for several years. Given load curves for energy services requirements in a building microgrid (u grid), fuel costs and other economic inputs, and a menu of available technologies, DER-CAM finds the optimum equipment fleet and its optimum operating schedule using a mixed integer linear programming approach. This capability is being applied using a software as a service (SaaS) model. Optimisation problems are set up on a Berkeley Lab server and clients can execute their jobs as needed, typically daily. The evolution of this approach is demonstrated by description of three ongoing projects. The first is a public access web site focused on solar photovoltaic generation and battery viability at large commercial and industrial customer sites. The second is a building CO2 emissions reduction operations problem for a University of California, Davis student dining hall for which potential investments are also considered. And the third, is both a battery selection problem and a rolling operating schedule problem for a large County Jail. Together these examples show that optimization of building u grid design and operation can be effectively achieved using SaaS.
Directory of Open Access Journals (Sweden)
Jun Yang
2015-08-01
Full Text Available The carbon emissions trading market and direct power purchases by large consumers are two promising directions of power system development. To trace the carbon emission flow in the power grid, the theory of carbon emission flow is improved by allocating power loss to the load side. Based on the improved carbon emission flow theory, an optimal dispatch model is proposed to optimize the cost of both large consumers and the power grid, which will benefit from the carbon emissions trading market. Moreover, to better simulate reality, the direct purchase of power by large consumers is also considered in this paper. The OPF (optimal power flow method is applied to solve the problem. To evaluate our proposed optimal dispatch strategy, an IEEE 30-bus system is used to test the performance. The effects of the price of carbon emissions and the price of electricity from normal generators and low-carbon generators with regards to the optimal dispatch are analyzed. The simulation results indicate that the proposed strategy can significantly reduce both the operation cost of the power grid and the power utilization cost of large consumers.
Operational controlling - a tool of translating strategy into action
Directory of Open Access Journals (Sweden)
2011-03-01
Full Text Available . Enterprises have a lot of problems with realization their strategic aims in the fast changing and competitive business arena from many years. Effective execution of strategic plan needs its translating into action, task results and indicators of everyday activities. The success on the market is attainable by communicating strategic and operating goals on the each level of organizational structure and their connecting with budget of units or employee motivation. The scorecards balancing in finance, customer, process and development perspectives is very useful for pointing - what do we control with? or - what do we have to achieve? But doesn't answer to question about ways of enterprise managing. Main aim of the article is proving that operational controlling system is a essential tool for translating strategy into action. The Balanced Scorecard methodology should to take into consideration system and process connection of enterprise with procurement, co-operation or distribution supply chain also.
Radio Access Sharing Strategies for Multiple Operators in Cellular Networks
DEFF Research Database (Denmark)
Popovska Avramova, Andrijana; Iversen, Villy Bæk
2015-01-01
deployments (required for coverage enhancement), increased base station utilization, and reduced overall power consumption. Today, network sharing in the radio access part is passive and limited to cell sites. With the introduction of Cloud Radio Access Network and Software Defined Networking adoption......Mobile operators are moving towards sharing network capacity in order to reduce capital and operational expenditures, while meeting the increasing demand for mobile broadband data services. Radio access network sharing is a promising technique that leads to reduced number of physical base station...... to the radio access network, the possibility for sharing baseband processing and radio spectrum becomes an important aspect of network sharing. This paper investigates strategies for active sharing of radio access among multiple operators, and analyses the individual benefits depending on the sharing degree...
Chanda, Emmanuel; Mukonka, Victor M; Kamuliwo, Mulakwa; Macdonald, Michael B; Haque, Ubydul
2013-01-08
While consensus on malaria vector control policy and strategy has stimulated unprecedented political-will, backed by international funding organizations and donors, vector control interventions are expansively being implemented based on assumptions with unequaled successes. This manuscript reports on the strategies, achievements and challenges of the past and contemporary malaria vector control efforts in Zambia. All available information and accessible archived documentary records on malaria vector control in Zambia were reviewed. Retrospective analysis of routine surveillance data from the Health Management Information System (HMIS), data from population-based household surveys and various operations research reports was conducted to assess the status in implementing policies and strategies. Empirical evidence is critical for informing policy decisions and tailoring interventions to local settings. Thus, the World Health Organization (WHO) encourages the adoption of the integrated vector management (IVM) strategy which is a rational decision making process for optimal use of available resources. One of the key features of IVM is capacity building at the operational level to plan, implement, monitor and evaluate vector control and its epidemiological and entomological impact. In Zambia, great progress has been made in implementing WHO-recommended vector control policies and strategies within the context of the IVM Global Strategic framework with strong adherence to its five key attributes. The country has solid, consistent and coordinated policies, strategies and guidelines for malaria vector control. The Zambian experience demonstrates the significance of a coordinated multi-pronged IVM approach effectively operationalized within the context of a national health system.
Operational characteristics optimization of human-computer system
Directory of Open Access Journals (Sweden)
Zulquernain Mallick
2010-09-01
Full Text Available Computer operational parameters are having vital influence on the operators efficiency from readability viewpoint. Four parameters namely font, text/background color, viewing angle and viewing distance are analyzed. The text reading task, in the form of English text, was presented on the computer screen to the participating subjects and their performance, measured in terms of number of words read per minute (NWRPM, was recorded. For the purpose of optimization, the Taguchi method is used to find the optimal parameters to maximize operators’ efficiency for performing readability task. Two levels of each parameter have been considered in this study. An orthogonal array, the signal-to-noise (S/N ratio and the analysis of variance (ANOVA were employed to investigate the operators’ performance/efficiency. Results showed that Times Roman font, black text on white background, 40 degree viewing angle and 60 cm viewing distance, the subjects were quite comfortable, efficient and read maximum number of words per minute. Text/background color was dominant parameter with a percentage contribution of 76.18% towards the laid down objective followed by font type at 18.17%, viewing distance 7.04% and viewing angle 0.58%. Experimental results are provided to confirm the effectiveness of this approach.
Survey strategy optimization for the Atacama Cosmology Telescope
De Bernardis, F.; Stevens, J. R.; Hasselfield, M.; Alonso, D.; Bond, J. R.; Calabrese, E.; Choi, S. K.; Crowley, K. T.; Devlin, M.; Dunkley, J.; Gallardo, P. A.; Henderson, S. W.; Hilton, M.; Hlozek, R.; Ho, S. P.; Huffenberger, K.; Koopman, B. J.; Kosowsky, A.; Louis, T.; Madhavacheril, M. S.; McMahon, J.; Næss, S.; Nati, F.; Newburgh, L.; Niemack, M. D.; Page, L. A.; Salatino, M.; Schillaci, A.; Schmitt, B. L.; Sehgal, N.; Sievers, J. L.; Simon, S. M.; Spergel, D. N.; Staggs, S. T.; van Engelen, A.; Vavagiakis, E. M.; Wollack, E. J.
2016-07-01
In recent years there have been significant improvements in the sensitivity and the angular resolution of the instruments dedicated to the observation of the Cosmic Microwave Background (CMB). ACTPol is the first polarization receiver for the Atacama Cosmology Telescope (ACT) and is observing the CMB sky with arcmin resolution over 2000 sq. deg. Its upgrade, Advanced ACTPol (AdvACT), will observe the CMB in five frequency bands and over a larger area of the sky. We describe the optimization and implementation of the ACTPol and AdvACT surveys. The selection of the observed fields is driven mainly by the science goals, that is, small angular scale CMB measurements, B-mode measurements and cross-correlation studies. For the ACTPol survey we have observed patches of the southern galactic sky with low galactic foreground emissions which were also chosen to maximize the overlap with several galaxy surveys to allow unique cross-correlation studies. A wider field in the northern galactic cap ensured significant additional overlap with the BOSS spectroscopic survey. The exact shapes and footprints of the fields were optimized to achieve uniform coverage and to obtain cross-linked maps by observing the fields with different scan directions. We have maximized the efficiency of the survey by implementing a close to 24 hour observing strategy, switching between daytime and nighttime observing plans and minimizing the telescope idle time. We describe the challenges represented by the survey optimization for the significantly wider area observed by AdvACT, which will observe roughly half of the low-foreground sky. The survey strategies described here may prove useful for planning future ground-based CMB surveys, such as the Simons Observatory and CMB Stage IV surveys.
Nanaeda, Kimihiro; Mueller, Fabian; Brouwer, Jacob; Samuelsen, Scott
Operating strategies of solid oxide fuel cell (SOFC) combined heat and power (CHP) systems are developed and evaluated from a utility, and end-user perspective using a fully integrated SOFC-CHP system dynamic model that resolves the physical states, thermal integration and overall efficiency of the system. The model can be modified for any SOFC-CHP system, but the present analysis is applied to a hotel in southern California based on measured electric and heating loads. Analysis indicates that combined heat and power systems can be operated to benefit both the end-users and the utility, providing more efficient electric generation as well as grid ancillary services, namely dispatchable urban power. Design and operating strategies considered in the paper include optimal sizing of the fuel cell, thermal energy storage to dispatch heat, and operating the fuel cell to provide flexible grid power. Analysis results indicate that with a 13.1% average increase in price-of-electricity (POE), the system can provide the grid with a 50% operating range of dispatchable urban power at an overall thermal efficiency of 80%. This grid-support operating mode increases the operational flexibility of the SOFC-CHP system, which may make the technology an important utility asset for accommodating the increased penetration of intermittent renewable power.
Using Chemical Reaction Kinetics to Predict Optimal Antibiotic Treatment Strategies
Abel zur Wiesch, Pia; Cohen, Ted
2017-01-01
Identifying optimal dosing of antibiotics has proven challenging—some antibiotics are most effective when they are administered periodically at high doses, while others work best when minimizing concentration fluctuations. Mechanistic explanations for why antibiotics differ in their optimal dosing are lacking, limiting our ability to predict optimal therapy and leading to long and costly experiments. We use mathematical models that describe both bacterial growth and intracellular antibiotic-target binding to investigate the effects of fluctuating antibiotic concentrations on individual bacterial cells and bacterial populations. We show that physicochemical parameters, e.g. the rate of drug transmembrane diffusion and the antibiotic-target complex half-life are sufficient to explain which treatment strategy is most effective. If the drug-target complex dissociates rapidly, the antibiotic must be kept constantly at a concentration that prevents bacterial replication. If antibiotics cross bacterial cell envelopes slowly to reach their target, there is a delay in the onset of action that may be reduced by increasing initial antibiotic concentration. Finally, slow drug-target dissociation and slow diffusion out of cells act to prolong antibiotic effects, thereby allowing for less frequent dosing. Our model can be used as a tool in the rational design of treatment for bacterial infections. It is easily adaptable to other biological systems, e.g. HIV, malaria and cancer, where the effects of physiological fluctuations of drug concentration are also poorly understood. PMID:28060813
Using Chemical Reaction Kinetics to Predict Optimal Antibiotic Treatment Strategies.
Abel Zur Wiesch, Pia; Clarelli, Fabrizio; Cohen, Ted
2017-01-01
Identifying optimal dosing of antibiotics has proven challenging-some antibiotics are most effective when they are administered periodically at high doses, while others work best when minimizing concentration fluctuations. Mechanistic explanations for why antibiotics differ in their optimal dosing are lacking, limiting our ability to predict optimal therapy and leading to long and costly experiments. We use mathematical models that describe both bacterial growth and intracellular antibiotic-target binding to investigate the effects of fluctuating antibiotic concentrations on individual bacterial cells and bacterial populations. We show that physicochemical parameters, e.g. the rate of drug transmembrane diffusion and the antibiotic-target complex half-life are sufficient to explain which treatment strategy is most effective. If the drug-target complex dissociates rapidly, the antibiotic must be kept constantly at a concentration that prevents bacterial replication. If antibiotics cross bacterial cell envelopes slowly to reach their target, there is a delay in the onset of action that may be reduced by increasing initial antibiotic concentration. Finally, slow drug-target dissociation and slow diffusion out of cells act to prolong antibiotic effects, thereby allowing for less frequent dosing. Our model can be used as a tool in the rational design of treatment for bacterial infections. It is easily adaptable to other biological systems, e.g. HIV, malaria and cancer, where the effects of physiological fluctuations of drug concentration are also poorly understood.
Optimizing and controlling earthmoving operations using spatial technologies
Alshibani, Adel
This thesis presents a model designed for optimizing, tracking, and controlling earthmoving operations. The proposed model utilizes, Genetic Algorithm (GA), Linear Programming (LP), and spatial technologies including Global Positioning Systems (GPS) and Geographic Information Systems (GIS) to support the management functions of the developed model. The model assists engineers and contractors in selecting near optimum crew formations in planning phase and during construction, using GA and LP supported by the Pathfinder Algorithm developed in a GIS environment. GA is used in conjunction with a set of rules developed to accelerate the optimization process and to avoid generating and evaluating hypothetical and unrealistic crew formations. LP is used to determine quantities of earth to be moved from different borrow pits and to be placed at different landfill sites to meet project constraints and to minimize the cost of these earthmoving operations. On the one hand, GPS is used for onsite data collection and for tracking construction equipment in near real-time. On the other hand, GIS is employed to automate data acquisition and to analyze the collected spatial data. The model is also capable of reconfiguring crew formations dynamically during the construction phase while site operations are in progress. The optimization of the crew formation considers: (1) construction time, (2) construction direct cost, or (3) construction total cost. The model is also capable of generating crew formations to meet, as close as possible, specified time and/or cost constraints. In addition, the model supports tracking and reporting of project progress utilizing the earned-value concept and the project ratio method with modifications that allow for more accurate forecasting of project time and cost at set future dates and at completion. The model is capable of generating graphical and tabular reports. The developed model has been implemented in prototype software, using Object
OPTIMIZATION OF BIOCIDE STRATEGIES ON FINE PAPER MACHINES
Directory of Open Access Journals (Sweden)
Jani Kiuru
2010-05-01
Full Text Available In this study a rapid at-line ATP (adenosine triphosphate analysis is applied in papermaking. This ATP analysis takes less than a minute, and the information can be utilized instantly to adapt the biocide program. The study shows the effect of different biocide strategies at paper mills. Comparison is made between oxidative and reductive biocides on the one hand, and on the other hand between continuous vs. batch additions of biocide. Continuous biocide addition keeps the microbial activity at a constant level. However, a long production period without a boil-out might result in accumulation of resistant bacteria, which cannot be eliminated without changing the biocide strategy. Batch addition of biocide creates a high temporary concentration of biocide in the process. This causes lower temporary microbial activity in the process, but between the doses the microbial activity may rise to an intolerable level. Batch addition causes chemical variation to the wet end of a paper machine more easily than continuous addition. This can affect the performance of papermaking chemicals and cause problems with retention, fixing, etc. Both biocide addition strategies can be used if they are monitored and optimized properly. Rapid ATP analysis is a suitable tool for both purposes.
Signal/noise optimization strategies for stochastically estimated correlation functions
Detmold, William
2014-01-01
Numerical studies of quantum field theories usually rely upon an accurate determination of stochastically estimated correlation functions in order to extract information about the spectrum of the theory and matrix elements of operators. The reliable determination of such correlators is often hampered by an exponential degradation of signal/noise at late time separations. We demonstrate that it is sometimes possible to achieve significant enhancements of signal/noise by appropriately optimizing correlators with respect to the source and sink interpolating operators, and highlight the large range of possibilities that are available for this task. The ideas are discussed for both a toy model, and single hadron correlators in the context of quantum chromodynamics.
Skinner, Brian
2011-01-01
When facing a heavily-favored opponent, an underdog must be willing to assume greater-than-average risk. In statistical language, one would say that an underdog must be willing to adopt a strategy whose outcome has a larger-than-average variance. The difficult question is how much risk a team should be willing to accept. This is equivalent to asking how much the team should be willing to sacrifice from its mean score in order to increase the score's variance. In this paper a general, analytical method is developed for addressing this question quantitatively. Under the assumption that every play in a game is statistically independent, both the mean and the variance of a team's offensive output can be described using the binomial distribution. This description allows for direct calculations of the winning probability when a particular strategy is employed, and therefore allows one to calculate optimal offensive strategies. This paper develops this method for calculating optimal strategies exactly and then prese...
Optimal inspection and Repair Strategies for Structural Systems
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Faber, Michael Havbro
1992-01-01
A model for reliability-based repair and maintenance strategies of structural systems is described. The total expected costs in the lifetime of the structure are minimized with the number of inspections, the number and positions of the inspected points, the inspection efforts, the repair criteria...... to be inspected and to select the location of the points to be inspected. It is shown how information obtained through inspections and through the periods of normal operating of the structure can be used to update the inspection and maintenance planning. Finally, a small example is given illustrating...
Energy Technology Data Exchange (ETDEWEB)
Zheng, Xiaoyu; Ishikawa, Jun; Sugiyama, Tomoyuki; Maryyama, Yu [Nuclear Safety Research Center, Japan Atomic Energy Agency, Ibaraki (Japan)
2017-03-15
Containment venting is one of several essential measures to protect the integrity of the final barrier of a nuclear reactor during severe accidents, by which the uncontrollable release of fission products can be avoided. The authors seek to develop an optimization approach to venting operations, from a simulation-based perspective, using an integrated severe accident code, THALES2/KICHE. The effectiveness of the containment-venting strategies needs to be verified via numerical simulations based on various settings of the venting conditions. The number of iterations, however, needs to be controlled to avoid cumbersome computational burden of integrated codes. Bayesian optimization is an efficient global optimization approach. By using a Gaussian process regression, a surrogate model of the “black-box” code is constructed. It can be updated simultaneously whenever new simulation results are acquired. With predictions via the surrogate model, upcoming locations of the most probable optimum can be revealed. The sampling procedure is adaptive. Compared with the case of pure random searches, the number of code queries is largely reduced for the optimum finding. One typical severe accident scenario of a boiling water reactor is chosen as an example. The research demonstrates the applicability of the Bayesian optimization approach to the design and establishment of containment-venting strategies during severe accidents.
Strategies for optimizing algal biology for enhanced biomass production
Directory of Open Access Journals (Sweden)
Amanda N. Barry
2015-02-01
Full Text Available One of the more environmentally sustainable ways to produce high energy density (oils feed stocks for the production of liquid transportation fuels is from biomass. Photosynthetic carbon capture combined with biomass combustion (point source and subsequent carbon capture and sequestration (BECCS has also been proposed in the Intergovernmental Panel on Climate Change Report as one of the most effective and economical strategies to remediate atmospheric greenhouse gases. To maximize photosynthetic carbon capture efficiency and energy-return-on-investment, we must develop biomass production systems that achieve the greatest yields with the lowest inputs. Numerous studies have demonstrated that microalgae have among the greatest potentials for biomass production. This is in part due to the fact that all alga cells are photoautotrophic, they have active carbon concentrating mechanisms to increase photosynthetic productivity, and all the biomass is harvestable unlike plants. All photosynthetic organisms, however, convert only a fraction of the solar energy they capture into chemical energy (reduced carbon or biomass. To increase aerial carbon capture rates and biomass productivity it will be necessary to identify the most robust algal strains and increase their biomass production efficiency often by genetic manipulation. We review recent large-scale efforts to identify the best biomass producing strains and metabolic engineering strategies to improve aerial productivity. These strategies include optimization of photosynthetic light-harvesting antenna size to increase energy capture and conversion efficiency and the potential development of advanced molecular breeding techniques. To date, these strategies have resulted in up to two-fold increases in biomass productivity.
ALARM STRATEGY AND COMPLEXITY: PREDICTIONS OF OPERATOR RESPONSE
Energy Technology Data Exchange (ETDEWEB)
Austin Ragsdale; Roger Lew; Brian Dyre; Ronald Boring; David Gertman
2012-07-01
Decision support for operators is not new, and much has been written regarding the potential usefulness of digital support systems and alarm filtering strategies. However, determining the appropriate characteristics of decision support tools is difficult, especially when alarms can vary in the manner which diagnostic information is formulated and displayed and when event scenario types are complex and numerous. When first reviewed, the advantages or disadvantages of a particular alarm approach may not be apparent to the designer or analyst. The present research focuses on the review of two particular alarm strategies, binary alarm type (BAT) and likelihood alarm type (LAT), and reviews their influence upon accuracy, bias, and trust for tasks performed at a computer workstation capable of replicating a series of control-room-like alarms. The findings are discussed in terms of the of the performance advantages of likelihood alarm technology and related research as an aid to the alarm design process.
An Optimization Approach to Coexistence of Bluetooth and Wi-Fi Networks Operating in ISM Environment
Klajbor, Tomasz; Rak, Jacek; Wozniak, Jozef
Unlicensed ISM band is used by various wireless technologies. Therefore, issues related to ensuring the required efficiency and quality of operation of coexisting networks become essential. The paper addresses the problem of mutual interferences between IEEE 802.11b transmitters (commercially named Wi-Fi) and Bluetooth (BT) devices.An optimization approach to modeling the topology of BT scatternets is introduced, resulting in more efficient utilization of ISM environment consisting of BT and Wi-Fi networks. To achieve it, the Integer Linear Programming approach has been proposed. Example results presented in the paper illustrate significant benefits of using the proposed modeling strategy.
Optimal Operation of Plug-In Electric Vehicles in Power Systems with High Wind Power Penetrations
DEFF Research Database (Denmark)
Hu, Weihao; Su, Chi; Chen, Zhe
2013-01-01
The Danish power system has a large penetration of wind power. The wind fluctuation causes a high variation in the power generation, which must be balanced by other sources. The battery storage based Plug-In Electric Vehicles (PEV) may be a possible solution to balance the wind power variations...... in the power systems with high wind power penetrations. In this paper, the integration of plug-in electric vehicles in the power systems with high wind power penetrations is proposed and discussed. Optimal operation strategies of PEV in the spot market are proposed in order to decrease the energy cost for PEV...
Energy Technology Data Exchange (ETDEWEB)
Belhomme, Boris
2011-07-01
The levelized costs of a solar tower power plant are mainly influenced by the operational strategy of its heliostat field. Ensuring an efficient utilization of the heliostat field during the plant operation and therewith a high overall efficiency requires an optimal aim point strategy. The objective of the present work is to develop a computer-aided method for the optimization of aim point strategies. One main prerequisite for this kind of optimization is a realistic evaluation of a given aim point configuration. For this purpose an efficient ray tracing model for a fast and precise calculation of the flux density distribution caused by heliostats is developed as a first step. It is validated by a comparison of simulated and measured flux density distributions. By coupling the ray tracing model and a physical model of a receiver any variable of the receiver model can act as optimization variable. In a second step a method for the optimization of aim point configurations is developed. By defining a finite number of fixed aims points, the present problems becomes a combinatorial optimization problem. Due to the problem complexity, an exact solution can usually not be determined. On the other hand, this allows applying algorithms for the global optimization of combinatorial problems. Accordingly the Ant Colony Optimization metaheuristic is applied and adapted to the aim point optimization problem. By means of two selected example cases the general suitability of the method for the purpose of aim point optimization is proved and the influence of different optimization parameters on the optimization process is investigated. (orig.)
A generic operational strategy to qualify translational safety biomarkers.
Matheis, Katja; Laurie, David; Andriamandroso, Christiane; Arber, Nadir; Badimon, Lina; Benain, Xavier; Bendjama, Kaïdre; Clavier, Isabelle; Colman, Peter; Firat, Hüseyin; Goepfert, Jens; Hall, Steve; Joos, Thomas; Kraus, Sarah; Kretschmer, Axel; Merz, Michael; Padro, Teresa; Planatscher, Hannes; Rossi, Annamaria; Schneiderhan-Marra, Nicole; Schuppe-Koistinen, Ina; Thomann, Peter; Vidal, Jean-Marc; Molac, Béatrice
2011-07-01
The importance of using translational safety biomarkers that can predict, detect and monitor drug-induced toxicity during human trials is becoming increasingly recognized. However, suitable processes to qualify biomarkers in clinical studies have not yet been established. There is a need to define clear scientific guidelines to link biomarkers to clinical processes and clinical endpoints. To help define the operational approach for the qualification of safety biomarkers the IMI SAFE-T consortium has established a generic qualification strategy for new translational safety biomarkers that will allow early identification, assessment and management of drug-induced injuries throughout R&D. Copyright © 2011 Elsevier Ltd. All rights reserved.
Recursive Algorithm and Alternate Operation Strategy in Sequential Tests
Institute of Scientific and Technical Information of China (English)
XU Hong-lin; CHEN Zhan-qi; GUO Lue
2009-01-01
Based on the sequential probability ratio test (SPRT) developed by Wald, an improved method for successful probability test of missile flight is proposed. A recursive algorithm and its program in Matlab are designed to calculate the real risk level of the sequential test decision and the average number of samples under various test conditions. A concept, that is "rejecting as soon as possible", is put forward and an alternate operation strategy is conducted. The simulation results show that it can reduce the test expenses.
Hierarchical Control for Optimal and Distributed Operation of Microgrid Systems
DEFF Research Database (Denmark)
Meng, Lexuan
of the underlying communication features (sampling time, topology, parameters, etc.). System dynamics and sensitivity analysis are conducted based on the proposed model. A MG central controller is also developed based on the experimental system in the intelligent MG lab in Aalborg University for providing...... are also conducted in order to ensure safe operation during the optimization procedure. In addition, as the secondary and tertiary controls require global information to perform the functions, they are usually implemented in centralized fashion. In this sense the communication links are required from...... the central unit to each local unit, a single point of failure in the central controller may jerpodize the safety of the whole system, and the flexibility of the system is limited. Consequently, this project proposes the application of dynamic consensus algorithm (DCA) into existing hierarchical control...
Optimal operating points of oscillators using nonlinear resonators.
Kenig, Eyal; Cross, M C; Villanueva, L G; Karabalin, R B; Matheny, M H; Lifshitz, Ron; Roukes, M L
2012-11-01
We demonstrate an analytical method for calculating the phase sensitivity of a class of oscillators whose phase does not affect the time evolution of the other dynamic variables. We show that such oscillators possess the possibility for complete phase noise elimination. We apply the method to a feedback oscillator which employs a high Q weakly nonlinear resonator and provide explicit parameter values for which the feedback phase noise is completely eliminated and others for which there is no amplitude-phase noise conversion. We then establish an operational mode of the oscillator which optimizes its performance by diminishing the feedback noise in both quadratures, thermal noise, and quality factor fluctuations. We also study the spectrum of the oscillator and provide specific results for the case of 1/f noise sources.
A digital processing strategy to optimize hearing aid outputs directly.
Blamey, Peter J; Martin, Lois F A; Fiket, Hayley J
2004-01-01
A new amplification strategy (ADRO), based on 64 independently operating channels, was compared with a nine-channel wide dynamic range compression strategy (WDRC). Open-platform in-the-ear hearing instruments were configured either with ADRO or the manufacturer's WDRC strategy. Twenty-two subjects with mild to moderate hearing loss took home the ADRO or WDRC hearing aids. After three weeks' acclimatization, the aids were evaluated using monosyllables in quiet at 50 to 65 dB SPL and sentences in eight-talker babble. The acclimatization and evaluation were repeated in the second phase of the balanced reverse-block blind experimental design. The ADRO program showed a statistically significant mean advantage of 7.85% word score (95% confidence interval 3.19% to 12.51%; p = 0.002) and 6.41% phoneme score for the monosyllables in quiet (95% confidence interval 2.03% to 10.79%; p = 0.006). A statistically significant advantage of 7.25% was also found for the ADRO program in background noise (95% confidence interval 1.95% to 12.55%; p = 0.010). The results are consistent with earlier data for listeners with moderate to severe hearing loss.
Directory of Open Access Journals (Sweden)
Liudong Zhang
2014-01-01
Full Text Available An uncertain monthly reservoirs operation and multicrop deficit irrigation model was proposed under conjunctive use of underground and surface water for water resources optimization management. The objective is to maximize the total crop yield of the entire irrigation districts. Meanwhile, ecological water remained for the downstream demand. Because of the shortage of water resources, the monthly crop water production function was adopted for multiperiod deficit irrigation management. The model reflects the characteristics of water resources repetitive transformation in typical inland rivers irrigation system. The model was used as an example for water resources optimization management in Shiyang River Basin, China. Uncertainties in reservoir management shown as fuzzy probability were treated through chance-constraint parameter for decision makers. Necessity of dominance (ND was used to analyse the advantages of the method. The optimization results including reservoirs real-time operation policy, deficit irrigation management, and the available water resource allocation could be used to provide decision support for local irrigation management. Besides, the strategies obtained could help with the risk analysis of reservoirs operation stochastically.
Optimal Operation Method for Microgrid with Wind/PV/Diesel Generator/Battery and Desalination
Directory of Open Access Journals (Sweden)
Qingfeng Tang
2014-01-01
Full Text Available The power supply mode of island microgrid with a variety of complementary energy resources is one of the most effective ways to solve the problem of future island power supply. Based on the characteristics of seawater desalination system and water demand of island residents, a power allocation strategy for seawater desalination load, storage batteries, and diesel generators is proposed with the overall consideration of the economic and environmental benefits of system operation. Furthermore, a multiobjective optimal operation model for the island microgrid with wind/photovoltaic/diesel/storage and seawater desalination load is also proposed. It first establishes the objective functions which include the life loss of storage batteries and the fuel cost of diesel generators. Finally, the model is solved by the nondominated sorting genetic algorithm (NSGA-II. The island microgrid in a certain district is taken as an example to verify the effectiveness of the proposed optimal method. The results provide the theoretical and technical basis for the optimal operation of island microgrid.
Installation and first operation of the negative ion optimization experiment
Energy Technology Data Exchange (ETDEWEB)
De Muri, Michela, E-mail: michela.demuri@igi.cnr.it [INFN-LNL, v.le dell’Università 2, I-35020 Legnaro, PD (Italy); Consorzio RFX, CNR, ENEA, INFN, Università di Padova, A cciaierie Venete SpA – Corso Stati Uniti 4, 35127 Padova (Italy); Cavenago, Marco [INFN-LNL, v.le dell’Università 2, I-35020 Legnaro, PD (Italy); Serianni, Gianluigi; Veltri, Pierluigi; Bigi, Marco; Pasqualotto, Roberto; Barbisan, Marco; Recchia, Mauro; Zaniol, Barbara [Consorzio RFX, CNR, ENEA, INFN, Università di Padova, A cciaierie Venete SpA – Corso Stati Uniti 4, 35127 Padova (Italy); Kulevoy, Timour; Petrenko, Sergey [ITEP, B. Cheremushkinskaya 25, 117218 Moscow (Russian Federation); Baseggio, Lucio; Cervaro, Vannino; Agostini, Fabio Degli; Franchin, Luca; Laterza, Bruno [Consorzio RFX, CNR, ENEA, INFN, Università di Padova, A cciaierie Venete SpA – Corso Stati Uniti 4, 35127 Padova (Italy); Minarello, Alessandro [INFN-LNL, v.le dell’Università 2, I-35020 Legnaro, PD (Italy); Rossetto, Federico [Consorzio RFX, CNR, ENEA, INFN, Università di Padova, A cciaierie Venete SpA – Corso Stati Uniti 4, 35127 Padova (Italy); Sattin, Manuele [INFN-LNL, v.le dell’Università 2, I-35020 Legnaro, PD (Italy); Zucchetti, Simone [Consorzio RFX, CNR, ENEA, INFN, Università di Padova, A cciaierie Venete SpA – Corso Stati Uniti 4, 35127 Padova (Italy)
2015-10-15
Highlights: • Negative ion sources are key components of the neutral beam injectors. • The NIO1 experiment is a RF ion source, 60 kV–135 mA hydrogen negative ion beam. • NIO1 can contribute to beam extraction and optics thanks to quick replacement and upgrading of parts. • This work presents installation, status and first experiments results of NIO1. - Abstract: Negative ion sources are key components of the neutral beam injectors for thermonuclear fusion experiments. The NIO1 experiment is a radio frequency ion source generating a 60 kV–135 mA hydrogen negative ion beam. The beam is composed of nine beamlets over an area of about 40 × 40 mm{sup 2}. This experiment is jointly developed by Consorzio RFX and INFN-LNL, with the purpose of providing and optimizing a test ion source, capable of working in continuous mode and in conditions similar to those foreseen for the larger ion sources of the ITER neutral beam injectors. At present research and development activities on these ion sources still address several important issues related to beam extraction and optics optimization, to which the NIO1 test facility can contribute thanks to its modular design, which allows for quick replacement and upgrading of components. This contribution presents the installation phases, the status of the test facility and the results of the first experiments, which have demonstrated that the source can operate in continuous mode.
Directory of Open Access Journals (Sweden)
B. Thamaraikannan
2014-01-01
Full Text Available This paper studies in detail the background and implementation of a teaching-learning based optimization (TLBO algorithm with differential operator for optimization task of a few mechanical components, which are essential for most of the mechanical engineering applications. Like most of the other heuristic techniques, TLBO is also a population-based method and uses a population of solutions to proceed to the global solution. A differential operator is incorporated into the TLBO for effective search of better solutions. To validate the effectiveness of the proposed method, three typical optimization problems are considered in this research: firstly, to optimize the weight in a belt-pulley drive, secondly, to optimize the volume in a closed coil helical spring, and finally to optimize the weight in a hollow shaft. have been demonstrated. Simulation result on the optimization (mechanical components problems reveals the ability of the proposed methodology to find better optimal solutions compared to other optimization algorithms.
Hybridized genetic-immune based strategy to obtain optimal feasible assembly sequences
Directory of Open Access Journals (Sweden)
Bala Murali Gunji
2017-06-01
Full Text Available An appropriate sequence of assembly operations increases the productivity and enhances product quality there by decrease the overall cost and manufacturing lead time. Achieving such assembly sequence is a complex combinatorial optimization problem with huge search space and multiple assembly qualifying criteria. The purpose of the current research work is to develop an intelligent strategy to obtain an optimal assembly sequence subjected to the assembly predicates. This paper presents a novel hybrid artificial intelligent technique, which executes Artificial Immune System (AIS in combination with the Genetic Algorithm (GA to find out an optimal feasible assembly sequence from the possible assembly sequence. Two immune models are introduced in the current research work: (1 Bone marrow model for generating possible assembly sequence and reduce the system redundancy and (2 Negative selection model for obtaining feasible assembly sequence. Later, these two models are integrated with GA in order to obtain an optimal assembly sequence. The proposed AIS-GA algorithm aims at enhancing the performance of AIS by incorporating GA as a local search strategy to achieve global optimum solution for assemblies with large number of parts. The proposed algorithm is implemented on a mechanical assembly composed of eleven parts joined by several connectors. The method is found to be successful in achieving global optimum solution with less computational time compared to traditional artificial intelligent techniques.
Optimizing clinical environments for knowledge translation: strategies for nursing leaders.
Scott, Shannon D; VandenBeld, Brenda; Cummings, Greta G
2011-10-01
Using findings from our recent study that found that a context of uncertainty in the work environment hindered nurses' research utilization, we suggest strategies for nurse managers and leaders to optimize clinical environments and support efforts to put research into clinical practice (knowledge translation). Two important sources of uncertainty were the complexity of teamwork and inconsistency in management and leadership styles. To reduce the uncertainty arising from teamwork, we propose (a) clarifying nurses' scopes of practice, (b) increasing knowledge sharing through supporting journal clubs and enhanced computer access and (c) creating safe venues for multidisciplinary dialogue. To reduce uncertainty arising from variations in management and leadership, we propose (a) developing policies that enhance the consistency of leadership and clarify the strategic direction of the management team, (b) clearly communicating those policies to nurses and (c) providing explicit rationales for treatment changes. Small, incremental steps can be taken to realize substantive changes in clinical environments in order to optimize nursing work environments for knowledge translation.
[Optimal allocation of irrigation water resources based on systematical strategy].
Cheng, Shuai; Zhang, Shu-qing
2015-01-01
With the development of the society and economy, as well as the rapid increase of population, more and more water is needed by human, which intensified the shortage of water resources. The scarcity of water resources and growing competition of water in different water use sectors reduce water availability for irrigation, so it is significant to plan and manage irrigation water resources scientifically and reasonably for improving water use efficiency (WUE) and ensuring food security. Many investigations indicate that WUE can be increased by optimization of water use. However, present studies focused primarily on a particular aspect or scale, which lack systematic analysis on the problem of irrigation water allocation. By summarizing previous related studies, especially those based on intelligent algorithms, this article proposed a multi-level, multi-scale framework for allocating irrigation water, and illustrated the basic theory of each component of the framework. Systematical strategy of optimal irrigation water allocation can not only control the total volume of irrigation water on the time scale, but also reduce water loss on the spatial scale. It could provide scientific basis and technical support for improving the irrigation water management level and ensuring the food security.
Optimal Order Strategy in Uncertain Demands with Free Shipping Option
Directory of Open Access Journals (Sweden)
Qing-Chun Meng
2014-01-01
Full Text Available Free shipping with conditions has become one of the most effective marketing tools; more and more companies especially e-business companies prefer to offer free shipping to buyers whenever their orders exceed the minimum quantity specified by them. But in practice, the demands of buyers are uncertain, which are affected by weather, season, and many other factors. Firstly, we model the centralization ordering problem of retailers who face stochastic demands when suppliers offer free shipping, in which limited distributional information such as known mean, support, and some deviation measures of the random data is needed only. Then, based on the linear decision rule mainly for stochastic programming, we analyze the optimal order strategies of retailers and discuss the approximate solution. Further, we present the core allocation between all retailers via dual and cooperative game theory. The existence of core shows that each retailer is pleased to cooperate with others in the centralization problem. Finally, a numerical example is implemented to discuss how uncertain data and parameters affect the optimal solution.
Evolving strategies for optimal care management and plan benefit designs.
Cruickshank, John M
2012-11-01
As a prevalent, complex disease, diabetes presents a challenge to managed care. Strategies to optimize type 2 diabetes care management and treatment outcomes have been evolving over the past several years. Novel economic incentive programs (eg, those outlined in the Patient Protection and Affordable Care Act of 2010 that tie revenue from Medicare Advantage plans to the quality of healthcare delivered) are being implemented, as are evidence-based interventions designed to optimize treatment, reduce clinical complications, and lower the total financial burden of the disease. Another step that can improve outcomes is to align managed care diabetes treatment algorithms with national treatment guidelines. In addition, designing the pharmacy benefit to emphasize the overall value of treatment and minimize out-of-pocket expenses for patients can be an effective approach to reducing prescription abandonment. The implementation of emerging models of care that encourage collaboration between providers, support lifestyle changes, and engage patients to become partners in their own treatment also appears to be effective.
Optimal mission planning of GEO on-orbit refueling in mixed strategy
Chen, Xiao-qian; Yu, Jing
2017-04-01
The mission planning of GEO on-orbit refueling (OOR) in Mixed strategy is studied in this paper. Specifically, one SSc will be launched to an orbital slot near the depot when multiple GEO satellites are reaching their end of lives. The SSc replenishes fuel from the depot and then extends the lifespan of the target satellites via refueling. In the mixed scenario, only some of the target satellites could be served by the SSc, and the remaining ones will be fueled by Pseudo SScs (the target satellite which has already been refueled by the SSc and now has sufficient fuel for its operation as well as the fuel to refuel other target satellites is called Pseudo SSc here). The mission sequences and fuel mass of the SSc and Pseudo SScs, the dry mass of the SSc are used as design variables, whereas the economic benefit of the whole mission is used as design objective. The economic cost and benefit models are stated first, and then a mathematical optimization model is proposed. A comprehensive solution method involving enumeration, particle swarm optimization and modification is developed. Numerical examples are carried out to demonstrate the effectiveness of the model and solution method. Economic efficiencies of different OOR strategies are compared and discussed. The mixed strategy would perform better than the other strategies only when the target satellites satisfy some conditions. This paper presents an available mixed strategy scheme for users and analyzes its advantages and disadvantages by comparing with some other OOR strategies, providing helpful references to decision makers. The best strategy in practical applications depends on the specific demands and user preference.
Wake Mitigation Strategies for Optimizing Wind Farm Power Production
Dilip, Deepu; Porté-Agel, Fernando
2016-04-01
Although wind turbines are designed individually for optimum power production, they are often arranged into groups of closely spaced turbines in a wind farm rather than in isolation. Consequently, most turbines in a wind farm do not operate in unobstructed wind flows, but are affected by the wakes of turbines in front of them. Such wake interference significantly reduces the overall power generation from wind farms and hence, development of effective wake mitigation strategies is critical for improving wind farm efficiency. One approach towards this end is based on the notion that the operation of each turbine in a wind farm at its optimum efficiency might not lead to optimum power generation from the wind farm as a whole. This entails a down regulation of individual turbines from its optimum operating point, which can be achieved through different methods such as pitching the turbine blades, changing the turbine tip speed ratio or yawing of the turbine, to name a few. In this study, large-eddy simulations of a two-turbine arrangement with the second turbine fully in the wake of the first are performed. Different wake mitigation techniques are applied to the upstream turbine, and the effects of these on its wake characteristics are investigated. Results for the combined power from the two turbines for each of these methods are compared to a baseline scenario where no wake mitigation strategies are employed. Analysis of the results shows the potential for improved power production from such wake control methods. It should be noted, however, that the magnitude of the improvement is strongly affected by the level of turbulence in the incoming atmospheric flow.
Optimal Pharmacologic Treatment Strategies in Obesity and Type 2 Diabetes
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Gayotri Goswami
2014-06-01
Full Text Available The prevalence of obesity has increased to pandemic levels worldwide and is related to increased risk of morbidity and mortality. Metabolic comorbidities are commonly associated with obesity and include metabolic syndrome, pre-diabetes, and type 2 diabetes. Even if the prevalence of obesity remains stable until 2030, the anticipated numbers of people with diabetes will more than double as a consequence of population aging and urbanization. Weight reduction is integral in the prevention of diabetes among obese adults with pre-diabetes. Lifestyle intervention and weight reduction are also key in the management of type 2 diabetes. Weight loss is challenging for most obese patients, but for those with diabetes, it can pose an even greater challenge due to the weight gain associated with many treatment regimens. This article will review optimal treatment strategies for patients with comorbid obesity and type 2 diabetes. The role of anti-obesity agents in diabetes will also be reviewed. This literature review will provide readers with current strategies for the pharmacologic treatment of obesity and diabetes with a focus on the weight outcomes related to diabetes treatments.
Control and operation cost optimization of the HISS cryogenic system
Porter, J.; Bieser, F.; Anderson, D.
1983-08-01
The Heavy Ion Spectrometer System (HISS) relies upon superconducting coils of cryostable design to provide a maximum particle bending field of 3 tesla. A previous paper describes the cryogenic facility including helium refrigeration and gas management. A control strategy which has allowed full time unattended operation, along with significant nitrogen and power cost reductions is discussed. Reduction of liquid nitrogen consumption was accomplished by using the sensible heat available in the cold exhaust gas. Measured nitrogen throughput agrees with calculations for sensible heat utilization of zero to 70%. Calculated consumption saving over this range is 40 liters per hour for conductive losses to the supports only. It is found that the measured throughput differential for the total system is higher.
Control and operation cost optimization of the HISS cryogenic system
Energy Technology Data Exchange (ETDEWEB)
Porter, J.; Bieser, F.; Anderson, D.
1983-08-01
The Heavy Ion Spectrometer System (HISS) relies upon superconducting coils of cryostable design to provide a maximum particle bending field of 3 tesla. A previous paper describes the cryogenic facility including helium refrigeration and gas management. This paper discusses a control strategy which has allowed full time unattended operation, along with significant nitrogen and power cost reductions. Reduction of liquid nitrogen consumption has been accomplished by making use of the sensible heat available in the cold exhaust gas. Measured nitrogen throughput agrees with calculations for sensible heat utilization of zero to 70%. Calculated consumption saving over this range is 40 liters per hour for conductive losses to the supports only. The measured throughput differential for the total system is higher.
Water quality permitting: From end-of-pipe to operational strategies.
Meng, Fanlin; Fu, Guangtao; Butler, David
2016-09-15
End-of-pipe permitting is a widely practised approach to control effluent discharges from wastewater treatment plants. However, the effectiveness of the traditional regulation paradigm is being challenged by increasingly complex environmental issues, ever growing public expectations on water quality and pressures to reduce operational costs and greenhouse gas emissions. To minimise overall environmental impacts from urban wastewater treatment, an operational strategy-based permitting approach is proposed and a four-step decision framework is established: 1) define performance indicators to represent stakeholders' interests, 2) optimise operational strategies of urban wastewater systems in accordance to the indicators, 3) screen high performance solutions, and 4) derive permits of operational strategies of the wastewater treatment plant. Results from a case study show that operational cost, variability of wastewater treatment efficiency and environmental risk can be simultaneously reduced by at least 7%, 70% and 78% respectively using an optimal integrated operational strategy compared to the baseline scenario. However, trade-offs exist between the objectives thus highlighting the need of expansion of the prevailing wastewater management paradigm beyond the narrow focus on effluent water quality of wastewater treatment plants. Rather, systems thinking should be embraced by integrated control of all forms of urban wastewater discharges and coordinated regulation of environmental risk and treatment cost effectiveness. It is also demonstrated through the case study that permitting operational strategies could yield more environmentally protective solutions without entailing more cost than the conventional end-of-pipe permitting approach. The proposed four-step permitting framework builds on the latest computational techniques (e.g. integrated modelling, multi-objective optimisation, visual analytics) to efficiently optimise and interactively identify high performance
A simple quasi-dynamic model of a district heating system used for operational optimization
Energy Technology Data Exchange (ETDEWEB)
Boehm, Benny
1998-12-01
Equivalent models of DH (District Heating) systems are being developed and verified. The models will be used for operational optimization of DH systems. By nature this requires transient models of the DH network, however, some insight can be gained even from a steady state model of the DH network demonstrating the importance of the many parameters which are needed in the models. The temperature level as well as the line heat demand is low in Danish DH systems compared to many foreign DH systems. It has been advocated that the supply temperature should always be kept as low as possible in order to minimize the operational costs. However, this is not true in all cases as the optimum operational strategy will minimize the sum of the heat loss cost and the pumping cost. Thus in case of high line heat demands the supply temperature should not always be kept as low as possible. It has been shown that a simple model, i.e. one pipe - one bypass - one house, can be used for operational optimization, both in the steady state and in the transient case. What remains to be shown is how well this simple model can represent a whole district heating system. The optimization was carried out with matlab routines and with the high number of simulations performed, the computing time is rather long. Even, though much work has already been done, it is still not perfectly clear which demands must be put on simulation and optimization time steps in order to achieve a reliable solution without too much computational effort. (LN)
Optimizing Wind And Hydropower Generation Within Realistic Reservoir Operating Policy
Magee, T. M.; Clement, M. A.; Zagona, E. A.
2012-12-01
Previous studies have evaluated the benefits of utilizing the flexibility of hydropower systems to balance the variability and uncertainty of wind generation. However, previous hydropower and wind coordination studies have simplified non-power constraints on reservoir systems. For example, some studies have only included hydropower constraints on minimum and maximum storage volumes and minimum and maximum plant discharges. The methodology presented here utilizes the pre-emptive linear goal programming optimization solver in RiverWare to model hydropower operations with a set of prioritized policy constraints and objectives based on realistic policies that govern the operation of actual hydropower systems, including licensing constraints, environmental constraints, water management and power objectives. This approach accounts for the fact that not all policy constraints are of equal importance. For example target environmental flow levels may not be satisfied if it would require violating license minimum or maximum storages (pool elevations), but environmental flow constraints will be satisfied before optimizing power generation. Additionally, this work not only models the economic value of energy from the combined hydropower and wind system, it also captures the economic value of ancillary services provided by the hydropower resources. It is recognized that the increased variability and uncertainty inherent with increased wind penetration levels requires an increase in ancillary services. In regions with liberalized markets for ancillary services, a significant portion of hydropower revenue can result from providing ancillary services. Thus, ancillary services should be accounted for when determining the total value of a hydropower system integrated with wind generation. This research shows that the end value of integrated hydropower and wind generation is dependent on a number of factors that can vary by location. Wind factors include wind penetration level
Sue-Ann, Goh; Ponnambalam, S. G.
This paper focuses on the operational issues of a Two-echelon Single-Vendor-Multiple-Buyers Supply chain (TSVMBSC) under vendor managed inventory (VMI) mode of operation. To determine the optimal sales quantity for each buyer in TSVMBC, a mathematical model is formulated. Based on the optimal sales quantity can be obtained and the optimal sales price that will determine the optimal channel profit and contract price between the vendor and buyer. All this parameters depends upon the understanding of the revenue sharing between the vendor and buyers. A Particle Swarm Optimization (PSO) is proposed for this problem. Solutions obtained from PSO is compared with the best known results reported in literature.
Four Operational Strategies For The Tower of Pisa
Bartolozzi, F.
The operational strategies proposed for safeguarding the Leaning Tower all agree on the urgent need to lay a sub-foundation for guaranteeing the stability of the foundation soil, considerably decreasing the current pressure to a value compatible with its resistance characteristics. Their second common property is the creation of a static beneficial effect on the material forming the monument. This effect may be achieved by reducing the pressure in the material forming the Tower, by making the present inclination decrease considerably, or by means of a reinforcement ring on the most stressed parts of the Tower - if the present inclination is to remain unchanged - or with the combined action of both the inclination decrease and the reinforcement ring. Clearly, the choice of each operation must be made within the framework of the present and particular resistance conditions of the material. On the other hand, the four techniques differ structurally and operationally. The former aspects refer to laying structural elements, all equally effective, but different in conception and function - such as pillars, beams, hinges and tubular devices to be laid in order to integrate the common sub-foundation and to be utilised with respect to each operational technique. The operational differences mainly depend on the different executive needs with respect to the structural elements to be laid. The operational aspect of the fourth technique is very simple, but particularly delicate, as are all techniques concerning the Tower. In relation to this, the operation must clearly be managed by a highly qualified and professional group of technicians and workers using the most appropriate and modern technological apparatus. I believe that the considerable delicacy of the operational stage does not obstruct the application of the proposed techniques, both because of the precarious safety conditions of the building (requiring a radical solution), and because the operations put into
Toolgraph Design of Optimal and Feasible Control Strategies for Time-Varying Dynamical Systems
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Z. Kowalczuk
2012-01-01
Full Text Available The paper presents a new method for designing optimal and feasible control strategies for time-variant dynamical processes. The key point of the presented idea lies in utilizing a flow graph structure for representing pertinent properties of the autonomous dynamics of a given dynamical process in a time-and-state space, which is composed of certain elementary segments. The structure is referred to as a time-and-state space toolgraph. In the procedure, each segment of the temporary state space is assigned a node of the time-and-state space toolgraph. The flow values are proportional to the cost of driving the operational point of the dynamical process between the centers of adjacent segments. Any of the discrete optimization algorithms can be applied to search for a cheapest path connecting the initial and terminal points of the sought optimal piecewise-linear trajectory of the operational points in the considered time-and-state space. Additional assumptions or restrictions concerning arbitrary forbidden zones for the operational points can be easily taken into account. In such cases the nodes representing the segments partially or entirely belonging to the finite forbidden zones are deposed from the toolgraph structure.
DEFF Research Database (Denmark)
He, Guannan; Chen, Qixin; Kang, Chongqing
2016-01-01
Large-scale battery storage will become an essential part of the future smart grid. This paper investigates the optimal bidding strategy for battery storage in power markets. Battery storage could increase its profitability by providing fast regulation service under a performance-based regulation...... degree. Thus, we incorporate a battery cycle life model into a profit maximization model to determine the optimal bids in day-ahead energy, spinning reserve, and regulation markets. Then a decomposed online calculation method to compute cycle life under different operational strategies is proposed...
Many-body decoherence dynamics and optimized operation of a single-photon switch
Murray, C. R.; Gorshkov, A. V.; Pohl, T.
2016-09-01
We develop a theoretical framework to characterize the decoherence dynamics due to multi-photon scattering in an all-optical switch based on Rydberg atom induced nonlinearities. By incorporating the knowledge of this decoherence process into optimal photon storage and retrieval strategies, we establish optimized switching protocols for experimentally relevant conditions, and evaluate the corresponding limits in the achievable fidelities. Based on these results we work out a simplified description that reproduces recent experiments (Nat. Commun. 7 12480) and provides a new interpretation in terms of many-body decoherence involving multiple incident photons and multiple gate excitations forming the switch. Aside from offering insights into the operational capacity of realistic photon switching capabilities, our work provides a complete description of spin wave decoherence in a Rydberg quantum optics setting, and has immediate relevance to a number of further applications employing photon storage in Rydberg media.
Energy Technology Data Exchange (ETDEWEB)
Ren, Hongbo [Ritsumeikan Global Innovation Research Organization, Ritsumeikan University, 603-8577 Kyoto (Japan); Zhou, Weisheng; Nakagami, Ken' ichi [College of Policy Sciences, Ritsumeikan University, 603-8577 Kyoto (Japan); Gao, Weijun; Wu, Qiong [Faculty of Environmental Engineering, The University of Kitakyushu, 808-0135 Kitakyushu (Japan)
2010-12-15
Along with the continuing global warming, the environmental constraints are expected to play more and more important role in the operation of distributed energy resource (DER) systems, besides the economic objective. In this study, a multi-objective optimization model is developed to analyze the optimal operating strategy of a DER system while combining the minimization of energy cost with the minimization of environmental impact which is assessed in terms of CO{sub 2} emissions. The trade-off curve is obtained by using the compromise programming method. As an illustrative example, the DER system installed in an eco-campus in Japan has been selected for case study. The distributed technologies under consideration include photovoltaics (PV), fuel cell and gas engine for providing electrical and thermal demands. The obtained results demonstrate that increasing the satisfaction degree of economic objective leads to increased CO{sub 2} emissions. The operation of the DER system is more sensitive when environmental objective is paid more attention. Moreover, according to the sensitivity analysis, the consideration of electricity buy-back, carbon tax, as well as fuel switching to biogas, has more or less effect on the operation of DER systems. (author)
Directory of Open Access Journals (Sweden)
Chenghong Gu
2015-12-01
Full Text Available This paper develops a discrete operation optimization model for combined heat and powers (CHPs in deregulated energy markets to maximize owners’ profits, where energy price forecasting is included. First, a single input and multi-output (SIMO model for typical CHPs is established, considering the varying ratio between heat and electricity outputs at different loading levels. Then, the energy prices are forecasted with a gray forecasting model and revised in real-time based on the actual prices by using the least squares method. At last, a discrete optimization model and corresponding dynamic programming algorithm are developed to design the optimal operation strategies for CHPs in real-time. Based on the forecasted prices, the potential operating strategy which may produce the maximum profits is pre-developed. Dynamic modification is then conducted to adjust the pre-developed operating strategy after the actual prices are known. The proposed method is implemented on a 1 MW CHP on a typical day. Results show the optimized profits comply well with those derived from real-time prices after considering dynamic modification process.
Altomare, Cristina; Guglielmann, Raffaella; Riboldi, Marco; Bellazzi, Riccardo; Baroni, Guido
2015-02-01
In high precision photon radiotherapy and in hadrontherapy, it is crucial to minimize the occurrence of geometrical deviations with respect to the treatment plan in each treatment session. To this end, point-based infrared (IR) optical tracking for patient set-up quality assessment is performed. Such tracking depends on external fiducial points placement. The main purpose of our work is to propose a new algorithm based on simulated annealing and augmented Lagrangian pattern search (SAPS), which is able to take into account prior knowledge, such as spatial constraints, during the optimization process. The SAPS algorithm was tested on data related to head and neck and pelvic cancer patients, and that were fitted with external surface markers for IR optical tracking applied for patient set-up preliminary correction. The integrated algorithm was tested considering optimality measures obtained with Computed Tomography (CT) images (i.e. the ratio between the so-called target registration error and fiducial registration error, TRE/FRE) and assessing the marker spatial distribution. Comparison has been performed with randomly selected marker configuration and with the GETS algorithm (Genetic Evolutionary Taboo Search), also taking into account the presence of organs at risk. The results obtained with SAPS highlight improvements with respect to the other approaches: (i) TRE/FRE ratio decreases; (ii) marker distribution satisfies both marker visibility and spatial constraints. We have also investigated how the TRE/FRE ratio is influenced by the number of markers, obtaining significant TRE/FRE reduction with respect to the random configurations, when a high number of markers is used. The SAPS algorithm is a valuable strategy for fiducial configuration optimization in IR optical tracking applied for patient set-up error detection and correction in radiation therapy, showing that taking into account prior knowledge is valuable in this optimization process. Further work will be
Strategies of Yota (Scartel - 4G Operator in Russian Federation
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Netra Pal Singh
2013-12-01
Full Text Available Russian Federation is one of the high growth markets for telecom services which are expected to reach $48.5 billion by 2013. With the granting of 4G LTE licenses, it is expected that 4G market in Russian Federation will be dominated by four cellular operators, i.e., MTS, Beeline, and MegaFon, Rostelecom along with two new startups, i.e., Osnova Telecom and Red Telecom (Iladi (2010. In addition, other companies such as Yota, Synterra, COMSTAR, Freshtel etc. are also operating in Russian WiMax & LTE telecom market to provide similar services. This paper is an attempt to analyze some of the parameters of LTE turn Yota WiMax Telecom Operator in Russian Federation. The paper covers current achievements of Yota, its reach in Russian Federation, its network size & technology, its services, expansion plans for future, strategies for survival (in question in a highly competitive market of big companies, and its ultimate fate.
Adaptive hybrid optimization strategy for calibration and parameter estimation of physical models
Vesselinov, Velimir V
2011-01-01
A new adaptive hybrid optimization strategy, entitled squads, is proposed for complex inverse analysis of computationally intensive physical models. The new strategy is designed to be computationally efficient and robust in identification of the global optimum (e.g. maximum or minimum value of an objective function). It integrates a global Adaptive Particle Swarm Optimization (APSO) strategy with a local Levenberg-Marquardt (LM) optimization strategy using adaptive rules based on runtime performance. The global strategy optimizes the location of a set of solutions (particles) in the parameter space. The LM strategy is applied only to a subset of the particles at different stages of the optimization based on the adaptive rules. After the LM adjustment of the subset of particle positions, the updated particles are returned to the APSO strategy. The advantages of coupling APSO and LM in the manner implemented in squads is demonstrated by comparisons of squads performance against Levenberg-Marquardt (LM), Particl...
Chemically optimizing operational efficiency of molecular rotary motors.
Conyard, Jamie; Cnossen, Arjen; Browne, Wesley R; Feringa, Ben L; Meech, Stephen R
2014-07-09
Unidirectional molecular rotary motors that harness photoinduced cis-trans (E-Z) isomerization are promising tools for the conversion of light energy to mechanical motion in nanoscale molecular machines. Considerable progress has been made in optimizing the frequency of ground-state rotation, but less attention has been focused on excited-state processes. Here the excited-state dynamics of a molecular motor with electron donor and acceptor substituents located to modify the excited-state reaction coordinate, without altering its stereochemistry, are studied. The substituents are shown to modify the photochemical yield of the isomerization without altering the motor frequency. By combining 50 fs resolution time-resolved fluorescence with ultrafast transient absorption spectroscopy the underlying excited-state dynamics are characterized. The Franck-Condon excited state relaxes in a few hundred femtoseconds to populate a lower energy dark state by a pathway that utilizes a volume conserving structural change. This is assigned to pyramidalization at a carbon atom of the isomerizing bridging double bond. The structure and energy of the dark state thus reached are a function of the substituent, with electron-withdrawing groups yielding a lower energy longer lived dark state. The dark state is coupled to the Franck-Condon state and decays on a picosecond time scale via a coordinate that is sensitive to solvent friction, such as rotation about the bridging bond. Neither subpicosecond nor picosecond dynamics are sensitive to solvent polarity, suggesting that intramolecular charge transfer and solvation are not key driving forces for the rate of the reaction. Instead steric factors and medium friction determine the reaction pathway, with the sterically remote substitution primarily influencing the energetics. Thus, these data indicate a chemical method of optimizing the efficiency of operation of these molecular motors without modifying their overall rotational frequency.
Li, Zejing
2012-01-01
This dissertation is mainly devoted to the research of two problems - the continuous-time portfolio optimization in different Wishart models and the effects of discrete rebalancing on portfolio wealth distribution and optimal portfolio strategy.
Optimal control strategies for tuberculosis treatment: a case study in Angola
Silva, Cristiana J
2012-01-01
We apply optimal control theory to a tuberculosis model given by a system of ordinary differential equations. Optimal control strategies are proposed to minimize the cost of interventions. Numerical simulations are given using data from Angola.
Selection, optimization, and compensation strategies : Interactive effects on daily work engagement
Zacher, Hannes; Chan, Felicia; Bakker, Arnold B.; Demerouti, Evangelia
2015-01-01
The theory of selective optimization with compensation (SOC) proposes that the "orchestrated" use of three distinct action regulation strategies (selection, optimization, and compensation) leads to positive employee outcomes. Previous research examined overall scores and additive models (i.e., main
Computing Optimal Stochastic Portfolio Execution Strategies: A Parametric Approach Using Simulations
Moazeni, Somayeh; Coleman, Thomas F.; Li, Yuying
2010-09-01
Computing optimal stochastic portfolio execution strategies under appropriate risk consideration presents great computational challenge. We investigate a parametric approach for computing optimal stochastic strategies using Monte Carlo simulations. This approach allows reduction in computational complexity by computing coefficients for a parametric representation of a stochastic dynamic strategy based on static optimization. Using this technique, constraints can be similarly handled using appropriate penalty functions. We illustrate the proposed approach to minimize the expected execution cost and Conditional Value-at-Risk (CVaR).
Optimizing strategies to improve interprofessional practice for veterans, part 1
Directory of Open Access Journals (Sweden)
Bhattacharya SB
2014-04-01
Full Text Available Shelley B Bhattacharya,1–3 Michelle I Rossi,1,2 Jennifer M Mentz11Geriatric Research Education and Clinical Center (GRECC, Veteran's Affairs Pittsburgh Healthcare System, 2University of Pittsburgh Medical Center, Pittsburgh, PA, USA; 3Albert Schweitzer Fellowship Program, Pittsburgh, PA, USAIntroduction: Interprofessional patient care is a well-recognized path that health care systems are striving toward. The Veteran's Affairs (VA system initiated interprofessional practice (IPP models with their Geriatric Evaluation and Management (GEM programs. GEM programs incorporate a range of specialties, including but not limited to, medicine, nursing, social work, physical therapy and pharmacy, to collaboratively evaluate veterans. Despite being a valuable resource, they are now faced with significant cut-backs, including closures. The primary goal of this project was to assess how the GEM model could be optimized at the Pittsburgh, Pennsylvania VA to allow for the sustainability of this important IPP assessment. Part 1 of the study evaluated the IPP process using program, patient, and family surveys. Part 2 examined how well the geriatrician matched patients to specialists in the GEM model. This paper describes Part 1 of our study.Methods: Three strategies were used: 1 a national GEM program survey; 2 a veteran/family satisfaction survey; and 3 an absentee assessment.Results: Twenty-six of 92 programs responded to the GEM IPP survey. Six strategies were shared to optimize IPP models throughout the country. Of the 34 satisfaction surveys, 80% stated the GEM clinic was beneficial, 79% stated their concerns were addressed, and 100% would recommend GEM to their friends. Of the 24 absentee assessments, the top three reasons for missing the appointments were transportation, medical illnesses, and not knowing/remembering about the appointment. Absentee rate diminished from 41% to 19% after instituting a reminder phone call policy.Discussion: Maintaining the
2016-06-10
TRANSLATING WEST AFRICAN STRATEGY WITH AIRPOWER MEANS: A QUALITATIVE COMPARISON OF TACTICAL AIRLIFT SHAPING OPERATIONS A thesis...Translating West African Strategy with Airpower Means: A Qualitative Comparison of Tactical Airlift Shaping Operations 5a. CONTRACT NUMBER 5b. GRANT...ABSTRACT TRANSLATING WEST AFRICAN STRATEGY WITH AIRPOWER MEANS: A QUALITATIVE COMPARISON OF TACTICAL AIRLIFT SHAPING OPERATIONS , by Maj Matthew C
Optimal pandemic influenza vaccine allocation strategies for the Canadian population.
Directory of Open Access Journals (Sweden)
Ashleigh R Tuite
Full Text Available BACKGROUND: The world is currently confronting the first influenza pandemic of the 21(st century. Influenza vaccination is an effective preventive measure, but the unique epidemiological features of swine-origin influenza A (H1N1 (pH1N1 introduce uncertainty as to the best strategy for prioritization of vaccine allocation. We sought to determine optimal prioritization of vaccine distribution among different age and risk groups within the Canadian population, to minimize influenza-attributable morbidity and mortality. METHODOLOGY/PRINCIPAL FINDINGS: We developed a deterministic, age-structured compartmental model of influenza transmission, with key parameter values estimated from data collected during the initial phase of the epidemic in Ontario, Canada. We examined the effect of different vaccination strategies on attack rates, hospitalizations, intensive care unit admissions, and mortality. In all scenarios, prioritization of high-risk individuals (those with underlying chronic conditions and pregnant women, regardless of age, markedly decreased the frequency of severe outcomes. When individuals with underlying medical conditions were not prioritized and an age group-based approach was used, preferential vaccination of age groups at increased risk of severe outcomes following infection generally resulted in decreased mortality compared to targeting vaccine to age groups with higher transmission, at a cost of higher population-level attack rates. All simulations were sensitive to the timing of the epidemic peak in relation to vaccine availability, with vaccination having the greatest impact when it was implemented well in advance of the epidemic peak. CONCLUSIONS/SIGNIFICANCE: Our model simulations suggest that vaccine should be allocated to high-risk groups, regardless of age, followed by age groups at increased risk of severe outcomes. Vaccination may significantly reduce influenza-attributable morbidity and mortality, but the benefits are
An Improved Brain Storm Optimization with Differential Evolution Strategy for Applications of ANNs
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Zijian Cao
2015-01-01
Full Text Available Brain Storm Optimization (BSO algorithm is a swarm intelligence algorithm inspired by human being’s behavior of brainstorming. The performance of BSO is maintained by the creating process of ideas, but when it cannot find a better solution for some successive iterations, the result will be so inefficient that the population might be trapped into local optima. In this paper, we propose an improved BSO algorithm with differential evolution strategy and new step size method. Firstly, differential evolution strategy is incorporated into the creating operator of ideas to allow BSO jump out of stagnation, owing to its strong searching ability. Secondly, we introduce a new step size control method that can better balance exploration and exploitation at different searching generations. Finally, the proposed algorithm is first tested on 14 benchmark functions of CEC 2005 and then is applied to train artificial neural networks. Comparative experimental results illustrate that the proposed algorithm performs significantly better than the original BSO.
Energy Technology Data Exchange (ETDEWEB)
Cao, Cuiwen; Zhang, Yakun; Gu, Xingsheng [Ministry of Education, East China Univ. of Science and Technology, Shanghai (China). Key Lab. of Advanced Control and Optimization for Chemical Processes
2013-07-01
Optimizing operation parameters for Texaco coal-water slurry gasifier with the consideration of multiple objectives is a complicated nonlinear constrained problem concerning 3 BP neural networks. In this paper, multi-objective 3-layer mixed cultural differential evolution (MO-3LM-CDE) algorithms which comprise of 4 multi-objective strategies and a 3LM-CDE algorithm are firstly presented. Then they are tested in 6 benchmark functions. Finally, the MO-3LM-CDE algorithms are applied to optimize 3 control parameters of the Texaco coal-water slurry gasifier in methanol production of a real-world chemical plant. The simulation results show that multi-objective optimal results are better than the respective single-objective optimal operations.
Optimizing Wellfield Operation in a Variable Power Price Regime.
Bauer-Gottwein, Peter; Schneider, Raphael; Davidsen, Claus
2016-01-01
Wellfield management is a multiobjective optimization problem. One important objective has been energy efficiency in terms of minimizing the energy footprint (EFP) of delivered water (MWh/m(3) ). However, power systems in most countries are moving in the direction of deregulated markets and price variability is increasing in many markets because of increased penetration of intermittent renewable power sources. In this context the relevant management objective becomes minimizing the cost of electric energy used for pumping and distribution of groundwater from wells rather than minimizing energy use itself. We estimated EFP of pumped water as a function of wellfield pumping rate (EFP-Q relationship) for a wellfield in Denmark using a coupled well and pipe network model. This EFP-Q relationship was subsequently used in a Stochastic Dynamic Programming (SDP) framework to minimize total cost of operating the combined wellfield-storage-demand system over the course of a 2-year planning period based on a time series of observed price on the Danish power market and a deterministic, time-varying hourly water demand. In the SDP setup, hourly pumping rates are the decision variables. Constraints include storage capacity and hourly water demand fulfilment. The SDP was solved for a baseline situation and for five scenario runs representing different EFP-Q relationships and different maximum wellfield pumping rates. Savings were quantified as differences in total cost between the scenario and a constant-rate pumping benchmark. Minor savings up to 10% were found in the baseline scenario, while the scenario with constant EFP and unlimited pumping rate resulted in savings up to 40%. Key factors determining potential cost savings obtained by flexible wellfield operation under a variable power price regime are the shape of the EFP-Q relationship, the maximum feasible pumping rate and the capacity of available storage facilities.
Gavrishchaka, Valeriy V.; Kovbasinskaya, Maria; Monina, Maria
2008-11-01
Novelty detection is a very desirable additional feature of any practical classification or forecasting system. Novelty and rare patterns detection is the main objective in such applications as fault/abnormality discovery in complex technical and biological systems, fraud detection and risk management in financial and insurance industry. Although many interdisciplinary approaches for rare event modeling and novelty detection have been proposed, significant data incompleteness due to the nature of the problem makes it difficult to find a universal solution. Even more challenging and much less formalized problem is novelty detection in complex strategies and models where practical performance criteria are usually multi-objective and the best state-of-the-art solution is often not known due to the complexity of the task and/or proprietary nature of the application area. For example, it is much more difficult to detect a series of small insider trading or other illegal transactions mixed with valid operations and distributed over long time period according to a well-designed strategy than a single, large fraudulent transaction. Recently proposed boosting-based optimization was shown to be an effective generic tool for the discovery of stable multi-component strategies/models from the existing parsimonious base strategies/models in financial and other applications. Here we outline how the same framework can be used for novelty and fraud detection in complex strategies and models.
The Analysis of Operations Management Strategies of IKEA
Institute of Scientific and Technical Information of China (English)
吴梦柯
2012-01-01
The Analysis of Operations Management Strategies oflKEA IKEA, as a multinational corporation, is a world famous home furniture company whose vision is ＂To provide better life for everYone＂. IKEA was founded in 1943 by Ingvar Karaprad, a young entrepreneur from Elmtaryd, Sweden. Initially Kamprad sold a wide range of products such as pencils, nylon stockings, wallets and watches via mail order. In 1948 Ikea started offering furniture for sale, and three years later the first edition of the Ikea catalogue was released. The first IKEA store opened in 1958 in Almhult, Sweden. From i958, the company expanded fast, opening its first store abroad in 1963. Since then, IKEA has expanded to 38 countries and 301 stores：
[Current operative techniques and strategies in endocrine surgery].
Gürtler, Thomas; Weber, Markus
2011-06-01
Technical advances and focusing on subsets modified endocrine surgery in the last ten years tremendously. There is on one side a clear trend towards minimal invasive approaches, first of all in the surgery of the adrenal glands, where the transperitoneal or retroperitoneal laparoscopic adrenalectomy has become the gold standard for tumors up to a size of 10 cm in diameter. But also in pancreatic endocrine surgery for small tumors localized in the pancreas tail and up to a certain extend in thyroid and parathyroid surgery, laparoscopic or video assisted techniques are used. On the other side more precise techniques allow a more complete and radical removal of endocrine tissue, especially in thyroid surgery. This article presents a summary of current operative techniques and strategies in endocrine surgery.
Optimization of operational planning for wind/hydro hybrid water supply systems
Energy Technology Data Exchange (ETDEWEB)
Vieira, Filipe; Ramos, Helena M. [Department of Civil Engineering, Instituto Superior Tecnico, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal)
2009-03-15
Water supply systems (WSS) frequently present high-energy consumption values, which correspond to the major expenses of these systems. Energy costs are a function of its real consumption and of the variability of the daily energy tariff. This paper presents a model of optimization for the energy efficiency in a water supply system. The system is equipped with a pump station and presents excess of available energy in the gravity branch. First, a water turbine is introduced in the system in order to use this excess of hydraulic available energy. Then, an optimization method to define the pump operation planning along the 24 h of simulation, as well as the analysis of the economic benefits resulting from the profit of wind energy to supply the water pumping, while satisfying the system constraints and population demands, is implemented, in order to minimize the global operational costs. The model, developed in MATLAB, uses linear programming and provides the planning strategy to take in each time step, which will influence the following hours. The simulation period considered is one day, sub-divided in hourly time steps. The rules obtained as output of the optimization procedures are subsequently introduced in a hydraulic simulator (e.g. EPANET), in order to verify the system behaviour along the simulation period. The results are compared with the normal operating mode (i.e. without optimization algorithm) and show that energy cost's savings are achieved dependently of the initial reservoir levels or volume. The insertion of the water turbine also generates significant economical benefits for the water supply system. (author)
Leaf Area Adjustment As an Optimal Drought-Adaptation Strategy
Manzoni, S.; Beyer, F.; Thompson, S. E.; Vico, G.; Weih, M.
2014-12-01
Leaf phenology plays a major role in land-atmosphere mass and energy exchanges. Much work has focused on phenological responses to light and temperature, but less to leaf area changes during dry periods. Because the duration of droughts is expected to increase under future climates in seasonally-dry as well as mesic environments, it is crucial to (i) predict drought-related phenological changes and (ii) to develop physiologically-sound models of leaf area dynamics during dry periods. Several optimization criteria have been proposed to model leaf area adjustment as soil moisture decreases. Some theories are based on the plant carbon (C) balance, hypothesizing that leaf area will decline when instantaneous net photosynthetic rates become negative (equivalent to maximization of cumulative C gain). Other theories draw on hydraulic principles, suggesting that leaf area should adjust to either maintain a constant leaf water potential (isohydric behavior) or to avoid leaf water potentials with negative impacts on photosynthesis (i.e., minimization of water stress). Evergreen leaf phenology is considered as a control case. Merging these theories into a unified framework, we quantify the effect of phenological strategy and climate forcing on the net C gain over the entire growing season. By accounting for the C costs of leaf flushing and the gains stemming from leaf photosynthesis, this metric assesses the effectiveness of different phenological strategies, under different climatic scenarios. Evergreen species are favored only when the dry period is relatively short, as they can exploit most of the growing season, and only incur leaf maintenance costs during the short dry period. In contrast, deciduous species that lower maintenance costs by losing leaves are advantaged under drier climates. Moreover, among drought-deciduous species, isohydric behavior leads to lowest C gains. Losing leaves gradually so as to maintain a net C uptake equal to zero during the driest period in
A systematic approach: optimization of healthcare operations with knowledge management.
Wickramasinghe, Nilmini; Bali, Rajeev K; Gibbons, M Chris; Choi, J H James; Schaffer, Jonathan L
2009-01-01
Effective decision making is vital in all healthcare activities. While this decision making is typically complex and unstructured, it requires the decision maker to gather multispectral data and information in order to make an effective choice when faced with numerous options. Unstructured decision making in dynamic and complex environments is challenging and in almost every situation the decision maker is undoubtedly faced with information inferiority. The need for germane knowledge, pertinent information and relevant data are critical and hence the value of harnessing knowledge and embracing the tools, techniques, technologies and tactics of knowledge management are essential to ensuring efficiency and efficacy in the decision making process. The systematic approach and application of knowledge management (KM) principles and tools can provide the necessary foundation for improving the decision making processes in healthcare. A combination of Boyd's OODA Loop (Observe, Orient, Decide, Act) and the Intelligence Continuum provide an integrated, systematic and dynamic model for ensuring that the healthcare decision maker is always provided with the appropriate and necessary knowledge elements that will help to ensure that healthcare decision making process outcomes are optimized for maximal patient benefit. The example of orthopaedic operating room processes will illustrate the application of the integrated model to support effective decision making in the clinical environment.
Studies on optimal design and operation of integrated distillation arrangements
Energy Technology Data Exchange (ETDEWEB)
Christiansen, Atle Christer
1997-12-31
During the last decades, there has been growing concern in the chemical engineering environment over the task of developing more cost- and energy efficient process equipment. This thesis discusses measures for improving the end-use energy efficiency of separation systems. It emphasises a certain class of integrated distillation arrangements, in particular it considers means for direct coupling of distillation columns so as to use the underlying physics to facilitate more energy efficient separations. The numerical methods discussed are well suited to solve models of distillation columns. A tear and grid method is proposed that to some extent exploits the sparsity, since the number of tear variables required for solving a distillation model usually is rather small. The parameter continuation method described is well suited for ill-conditioned problems. The analysis of integrated columns is extended beyond the scope of numerical simulations by means of analytical results that applies in certain limiting cases. The consept of preferred separation, which is important for prefractionator arrangements, is considered. From this analysis is derived information that is important for the practical operation of such columns. Finally, the proposed numerical methods are used to optimize Petlyuk arrangements for separating ternary and quaternary mixtures. 166 refs., 130 figs., 20 tabs.
Li/CFx Cells Optimized for Low-Temperature Operation
Smart, Marshall C.; Whitacre, Jay F.; Bugga, Ratnakumar V.; Prakash, G. K. Surya; Bhalla, Pooja; Smith, Kiah
2009-01-01
Some developments reported in prior NASA Tech Briefs articles on primary electrochemical power cells containing lithium anodes and fluorinated carbonaceous (CFx) cathodes have been combined to yield a product line of cells optimized for relatively-high-current operation at low temperatures at which commercial lithium-based cells become useless. These developments have involved modifications of the chemistry of commercial Li/CFx cells and batteries, which are not suitable for high-current and low-temperature applications because they are current-limited and their maximum discharge rates decrease with decreasing temperature. One of two developments that constitute the present combination is, itself, a combination of developments: (1) the use of sub-fluorinated carbonaceous (CFx wherein xLiBF4 dissolved at a concentration of 0.5 M in a mixture of four volume parts of 1,2 dimethoxyethane with one volume part of propylene carbonate. The proportion, x, of fluorine in the cathode in such a cell lies between 0.5 and 0.9. The best of such cells fabricated to date have exhibited discharge capacities as large as 0.6 A h per gram at a temperature of 50 C when discharged at a rate of C/5 (where C is the magnitude of the current, integrated for one hour, that would amount to the nominal charge capacity of a cell).
Phenology as a strategy for carbon optimality: a global model
Directory of Open Access Journals (Sweden)
S. Caldararu
2013-09-01
Full Text Available Phenology is essential to our understanding of biogeochemical cycles and the climate system. We develop a global mechanistic model of leaf phenology based on the hypothesis that phenology is a strategy for optimal carbon gain at the canopy level so that trees adjust leaf gains and losses in response to environmental factors such as light, temperature and soil moisture, to achieve maximum carbon assimilation. We fit this model to five years of satellite observations of leaf area index (LAI using a Bayesian fitting algorithm. We show that our model is able to reproduce phenological patterns for all vegetation types and use it to explore variations in growing season length and the climate factors that limit leaf growth for different biomes. Phenology in wet tropical areas is limited by leaf age physiological constraints while at higher latitude leaf seasonality is limited by low temperature and light availability. Leaf growth in grassland regions is limited by water availability but often in combination with other factors. This model will advance the current understanding of phenology for ecosystem carbon models and our ability to predict future phenological behaviour.
Strategy optimization for mask rule check in wafer fab
Yang, Chuen Huei; Lin, Shaina; Lin, Roger; Wang, Alice; Lee, Rachel; Deng, Erwin
2015-07-01
Photolithography process is getting more and more sophisticated for wafer production following Moore's law. Therefore, for wafer fab, consolidated and close cooperation with mask house is a key to achieve silicon wafer success. However, generally speaking, it is not easy to preserve such partnership because many engineering efforts and frequent communication are indispensable. The inattentive connection is obvious in mask rule check (MRC). Mask houses will do their own MRC at job deck stage, but the checking is only for identification of mask process limitation including writing, etching, inspection, metrology, etc. No further checking in terms of wafer process concerned mask data errors will be implemented after data files of whole mask are composed in mask house. There are still many potential data errors even post-OPC verification has been done for main circuits. What mentioned here are the kinds of errors which will only occur as main circuits combined with frame and dummy patterns to form whole reticle. Therefore, strategy optimization is on-going in UMC to evaluate MRC especially for wafer fab concerned errors. The prerequisite is that no impact on mask delivery cycle time even adding this extra checking. A full-mask checking based on job deck in gds or oasis format is necessary in order to secure acceptable run time. Form of the summarized error report generated by this checking is also crucial because user friendly interface will shorten engineers' judgment time to release mask for writing. This paper will survey the key factors of MRC in wafer fab.
Optimal recruitment strategies for groups of interacting walkers with leaders
Martínez-García, Ricardo; López, Cristóbal; Vazquez, Federico
2015-02-01
We introduce a model of interacting random walkers on a finite one-dimensional chain with absorbing boundaries or targets at the ends. Walkers are of two types: informed particles that move ballistically towards a given target and diffusing uninformed particles that are biased towards close informed individuals. This model mimics the dynamics of hierarchical groups of animals, where an informed individual tries to persuade and lead the movement of its conspecifics. We characterize the success of this persuasion by the first-passage probability of the uninformed particle to the target, and we interpret the speed of the informed particle as a strategic parameter that the particle can tune to maximize its success. We find that the success probability is nonmonotonic, reaching its maximum at an intermediate speed whose value increases with the diffusing rate of the uninformed particle. When two different groups of informed leaders traveling in opposite directions compete, usually the largest group is the most successful. However, the minority can reverse this situation and become the most probable winner by following two different strategies: increasing its attraction strength or adjusting its speed to an optimal value relative to the majority's speed.
Glycosylation of therapeutic proteins: an effective strategy to optimize efficacy.
Solá, Ricardo J; Griebenow, Kai
2010-02-01
During their development and administration, protein-based drugs routinely display suboptimal therapeutic efficacies due to their poor physicochemical and pharmacological properties. These innate liabilities have driven the development of molecular strategies to improve the therapeutic behavior of protein drugs. Among the currently developed approaches, glycoengineering is one of the most promising, because it has been shown to simultaneously afford improvements in most of the parameters necessary for optimization of in vivo efficacy while allowing for targeting to the desired site of action. These include increased in vitro and in vivo molecular stability (due to reduced oxidation, cross-linking, pH-, chemical-, heating-, and freezing-induced unfolding/denaturation, precipitation, kinetic inactivation, and aggregation), as well as modulated pharmacodynamic responses (due to altered potencies from diminished in vitro enzymatic activities and altered receptor binding affinities) and improved pharmacokinetic profiles (due to altered absorption and distribution behaviors, longer circulation lifetimes, and decreased clearance rates). This article provides an account of the effects that glycosylation has on the therapeutic efficacy of protein drugs and describes the current understanding of the mechanisms by which glycosylation leads to such effects.
Noninfectious uveitis: strategies to optimize treatment compliance and adherence
Directory of Open Access Journals (Sweden)
Dolz-Marco R
2015-08-01
Full Text Available Rosa Dolz-Marco,1 Roberto Gallego-Pinazo,1 Manuel Díaz-Llopis,2 Emmett T Cunningham Jr,3–6 J Fernando Arévalo7,8 1Unit of Macula, Department of Ophthalmology, University and Polytechnic Hospital La Fe, 2Faculty of Medicine, University of Valencia, Spain; 3Department of Ophthalmology, California Pacific Medical Center, San Francisco, 4Department of Ophthalmology, Stanford University School of Medicine, Stanford, 5The Francis I Proctor Foundation, University of California San Francisco Medical Center, 6West Coast Retina Medical Group, San Francisco, CA, USA; 7Vitreoretina Division, King Khaled Eye Specialist Hospital, Riyadh, Saudi Arabia; 8Retina Division, Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA Abstract: Noninfectious uveitis includes a heterogenous group of sight-threatening ocular and systemic disorders. Significant progress has been made in the treatment of noninfectious uveitis in recent years, particularly with regard to the effective use of corticosteroids and non-corticosteroid immunosuppressive drugs, including biologic agents. All of these therapeutic approaches are limited, however, by any given patient’s ability to comply with and adhere to their prescribed treatment. In fact, compliance and adherence are among the most important patient-related determinants of treatment success. We discuss strategies to optimize compliance and adherence. Keywords: noninfectious uveitis, intraocular inflammation, immunosuppressive treatment, adherence, compliance, therapeutic failure
DEFF Research Database (Denmark)
Zhang, Baohua; Hu, Weihao; Chen, Zhe
2015-01-01
As modern wind farmshave the ability to provideregulation service for the power system, wind power plant operators may be motivated to participate in the regulating market to maximize their profit.In this paper, anoptimal regulation servicestrategy for a wind farm to participate in the regulating......As modern wind farmshave the ability to provideregulation service for the power system, wind power plant operators may be motivated to participate in the regulating market to maximize their profit.In this paper, anoptimal regulation servicestrategy for a wind farm to participate...... in the stochastic optimization to deal with the uncertainty of the up regulation price and the up regulation activation of the power system.The Danish short-term electricity market and a wind farm in western Denmark are chosen to evaluate the effect of the proposed strategy. Simulation results showthe proposed...
Directory of Open Access Journals (Sweden)
Woraya Neungmatcha
2015-06-01
Full Text Available Since current agricultural production systems such as the sugarcane supply system in the sugar industry are developing towards larger and more complicated systems, there is consequently increasing use of agricultural machinery. Even though mechanization can help to increase the sugarcane yield, if the mechanical operation efficiency is low, then higher harvest costs and machinery shortages will occur. Global route planning for mechanical harvesters is one of the most important problems in the field of sugarcane harvesting and transporting operations. Improved efficiency and realistic implementation can be achieved by applying advanced planning methods for the execution of field operations, especially considering the field accessibility aspect. To address this issue, participative research was undertaken with a sugar milling company to produce and implement a mixed integer programming model that represents the mechanical harvester route plan. Particle swarm optimization was applied to find a solution to the model, leading to potential cost savings versus schedules produced manually by the mill officer. The model was also applied to explore regional planning options for a more integrated harvesting and transport system.
Directory of Open Access Journals (Sweden)
Chanda Emmanuel
2013-01-01
Full Text Available Abstract Background While consensus on malaria vector control policy and strategy has stimulated unprecedented political-will, backed by international funding organizations and donors, vector control interventions are expansively being implemented based on assumptions with unequaled successes. This manuscript reports on the strategies, achievements and challenges of the past and contemporary malaria vector control efforts in Zambia. Case description All available information and accessible archived documentary records on malaria vector control in Zambia were reviewed. Retrospective analysis of routine surveillance data from the Health Management Information System (HMIS, data from population-based household surveys and various operations research reports was conducted to assess the status in implementing policies and strategies. Discussion and evaluation Empirical evidence is critical for informing policy decisions and tailoring interventions to local settings. Thus, the World Health Organization (WHO encourages the adoption of the integrated vector management (IVM strategy which is a rational decision making process for optimal use of available resources. One of the key features of IVM is capacity building at the operational level to plan, implement, monitor and evaluate vector control and its epidemiological and entomological impact. In Zambia, great progress has been made in implementing WHO-recommended vector control policies and strategies within the context of the IVM Global Strategic framework with strong adherence to its five key attributes. Conclusions The country has solid, consistent and coordinated policies, strategies and guidelines for malaria vector control. The Zambian experience demonstrates the significance of a coordinated multi-pronged IVM approach effectively operationalized within the context of a national health system.
Multi-Agent System-Based Microgrid Operation Strategy for Demand Response
Directory of Open Access Journals (Sweden)
Hee-Jun Cha
2015-12-01
Full Text Available The microgrid and demand response (DR are important technologies for future power grids. Among the variety of microgrid operations, the multi-agent system (MAS has attracted considerable attention. In a microgrid with MAS, the agents installed on the microgrid components operate optimally by communicating with each other. This paper proposes an operation algorithm for the individual agents of a test microgrid that consists of a battery energy storage system (BESS and an intelligent load. A microgrid central controller to manage the microgrid can exchange information with each agent. The BESS agent performs scheduling for maximum benefit in response to the electricity price and BESS state of charge (SOC through a fuzzy system. The intelligent load agent assumes that the industrial load performs scheduling for maximum benefit by calculating the hourly production cost. The agent operation algorithm includes a scheduling algorithm using day-ahead pricing in the DR program and a real-time operation algorithm for emergency situations using emergency demand response (EDR. The proposed algorithm and operation strategy were implemented both by a hardware-in-the-loop simulation test using OPAL-RT and an actual hardware test by connecting a new distribution simulator.
Zhang, Zili; Gao, Chao; Liu, Yuxin; Qian, Tao
2014-09-01
Ant colony optimization (ACO) algorithms often fall into the local optimal solution and have lower search efficiency for solving the travelling salesman problem (TSP). According to these shortcomings, this paper proposes a universal optimization strategy for updating the pheromone matrix in the ACO algorithms. The new optimization strategy takes advantages of the unique feature of critical paths reserved in the process of evolving adaptive networks of the Physarum-inspired mathematical model (PMM). The optimized algorithms, denoted as PMACO algorithms, can enhance the amount of pheromone in the critical paths and promote the exploitation of the optimal solution. Experimental results in synthetic and real networks show that the PMACO algorithms are more efficient and robust than the traditional ACO algorithms, which are adaptable to solve the TSP with single or multiple objectives. Meanwhile, we further analyse the influence of parameters on the performance of the PMACO algorithms. Based on these analyses, the best values of these parameters are worked out for the TSP.
Cost related sensitivity analysis for optimal operation of a grid-parallel PEM fuel cell power plant
El-Sharkh, M. Y.; Tanrioven, M.; Rahman, A.; Alam, M. S.
Fuel cell power plants (FCPP) as a combined source of heat, power and hydrogen (CHP&H) can be considered as a potential option to supply both thermal and electrical loads. Hydrogen produced from the FCPP can be stored for future use of the FCPP or can be sold for profit. In such a system, tariff rates for purchasing or selling electricity, the fuel cost for the FCPP/thermal load, and hydrogen selling price are the main factors that affect the operational strategy. This paper presents a hybrid evolutionary programming and Hill-Climbing based approach to evaluate the impact of change of the above mentioned cost parameters on the optimal operational strategy of the FCPP. The optimal operational strategy of the FCPP for different tariffs is achieved through the estimation of the following: hourly generated power, the amount of thermal power recovered, power trade with the local grid, and the quantity of hydrogen that can be produced. Results show the importance of optimizing system cost parameters in order to minimize overall operating cost.
Operations Strategy Development in Project-based Production – a building contractor implements Lean
DEFF Research Database (Denmark)
Koch, Christian; Friis, Ole Uhrskov
2015-01-01
Purpose: To study how operations strategy innovation occurs in project-based production and organisation. Design/methodology/approach: A longitudinal case study encompassing the processes at the company headquarters and in two projects using Lean. Findings: The operations strategy development...... commences at a middle level in the organisation, is underpinned and embedded in production projects, and only after several years becomes embedded in the corporate operations strategy. The projects use Lean principles in a differentiated manner. Research limitations/implications: A qualitative case study...... operations strategy development. Originality/value: The present study contributes to the small body of studies of operations strategy development processes by providing insight into how project-based companies renew their operations strategy. Key words: Lean, Construction, Operations Strategy, Political...
Polymerase chain reaction: basic protocol plus troubleshooting and optimization strategies.
Lorenz, Todd C
2012-05-22
In the biological sciences there have been technological advances that catapult the discipline into golden ages of discovery. For example, the field of microbiology was transformed with the advent of Anton van Leeuwenhoek's microscope, which allowed scientists to visualize prokaryotes for the first time. The development of the polymerase chain reaction (PCR) is one of those innovations that changed the course of molecular science with its impact spanning countless subdisciplines in biology. The theoretical process was outlined by Keppe and coworkers in 1971; however, it was another 14 years until the complete PCR procedure was described and experimentally applied by Kary Mullis while at Cetus Corporation in 1985. Automation and refinement of this technique progressed with the introduction of a thermal stable DNA polymerase from the bacterium Thermus aquaticus, consequently the name Taq DNA polymerase. PCR is a powerful amplification technique that can generate an ample supply of a specific segment of DNA (i.e., an amplicon) from only a small amount of starting material (i.e., DNA template or target sequence). While straightforward and generally trouble-free, there are pitfalls that complicate the reaction producing spurious results. When PCR fails it can lead to many non-specific DNA products of varying sizes that appear as a ladder or smear of bands on agarose gels. Sometimes no products form at all. Another potential problem occurs when mutations are unintentionally introduced in the amplicons, resulting in a heterogeneous population of PCR products. PCR failures can become frustrating unless patience and careful troubleshooting are employed to sort out and solve the problem(s). This protocol outlines the basic principles of PCR, provides a methodology that will result in amplification of most target sequences, and presents strategies for optimizing a reaction. By following this PCR guide, students should be able to: • Set up reactions and thermal cycling
Institute of Scientific and Technical Information of China (English)
李进华; 王雪生; 邢元; 王树新; 李建民; 梁科
2016-01-01
To evaluate the operation comfortability in the master-slave robotic minimally invasive surgery (MIS), an optimal function was built with two operation comfortability decided indices, i.e., the center distance and volume contact ratio. Two verifying experiments on Phantom Desktop and MicroHand S were conducted. Experimental results show that the operation effect at the optimal relative location is better than that at the random location, which means that the optimal function constructed in this paper is effective in optimizing the operation comfortability.
Distributed optimal technology networks: a concept and strategy for potable water sustainability.
Weber, W J
2002-01-01
Viable strategies for ensuring adequate supplies of potable water are essential to long-term societal sustainability. The steadily increasing necessity for multiple reuse of water in urban societies is even now taxing our technical and financial abilities to meet ongoing needs for water suitable for human consumption. As a consequence, the current practice of treating the entire water demands of urban communities to the increasingly stringent standards required for drinking water is becoming an unsustainable practice, and thus a questionable strategy for planning and development of urban water systems. An innovative technology-based concept for implementation of a more sustainable strategy and practice for potable water is developed here. The concept is predicated on the inherent advantages of flexibility and responsiveness associated with decentralization of complex functions and operations. Specifically, it calls for strategic dispersal of flexible advanced treatment and control technologies throughout urban water transport and storage networks. This is in direct contradistinction to current strategies and practices of centralized and inflexible monolithic facilities. By integrating use-related satellite systems with critical components of existing systems and infrastructures, the concept can enable and facilitate optimal cost-effective applications of highly sophisticated advanced treatment and on-line monitoring and control technologies to in-place infrastructures in a holistic and sustainable manner.
Mentink, P.R.; Willems, F.P.T.; Kupper, F.; Eijnden, E.A.C. van den
2013-01-01
This paper presents a model-based control and calibration design method for online cost-based optimization of engine-aftertreatment operation under all operating conditions. The so-called Integrated Emission Management (IEM) strategy online minimizes the fuel and AbBlue consumption. Based on the
Mentink, P.R.; Willems, F.P.T.; Kupper, F.; Eijnden, E.A.C. van den
2013-01-01
This paper presents a model-based control and calibration design method for online cost-based optimization of engine-aftertreatment operation under all operating conditions. The so-called Integrated Emission Management (IEM) strategy online minimizes the fuel and AbBlue consumption. Based on the act
Zhu, Jun; Yan, Xuefeng; Zhao, Weixiang
2013-10-01
To solve chemical process dynamic optimization problems, a differential evolution algorithm integrated with adaptive scheduling mutation strategy (ASDE) is proposed. According to the evolution feedback information, ASDE, with adaptive control parameters, adopts the round-robin scheduling algorithm to adaptively schedule different mutation strategies. By employing an adaptive mutation strategy and control parameters, the real-time optimal control parameters and mutation strategy are obtained to improve the optimization performance. The performance of ASDE is evaluated using a suite of 14 benchmark functions. The results demonstrate that ASDE performs better than four conventional differential evolution (DE) algorithm variants with different mutation strategies, and that the whole performance of ASDE is equivalent to a self-adaptive DE algorithm variant and better than five conventional DE algorithm variants. Furthermore, ASDE was applied to solve a typical dynamic optimization problem of a chemical process. The obtained results indicate that ASDE is a feasible and competitive optimizer for this kind of problem.
The method of optimization of neuro-based concurrent operations in neurocomputers
Romanchuk, V. A.
2017-02-01
The article deals with the task of optimization of neuro-based concurrent operations to be implemented in neurocomputers. We define mathematical tools of this optimization that can employ the set-theoretic approach towards such concepts as task, operation, and microcommand. We consider segmentation and parallelization of operations as methods to use, depending on precedence relations among operations that constitute these segments. The task solution of optimization of neuro-based concurrent operations in neurocomputers can be applied to a whole class of neurocomputers, regardless of the manufacturer, the model or the product line, since we only address the general properties and principles of the neurocomputer operation. We select criteria and define methods of evaluating the effectiveness of parallelization of concurrent operations, when they are implemented in neurocomputers. We describe our empiric research in the form of a software system that automatically optimizes neuro-based concurrent operations in neurocomputers on the NP Studio platform.
Afshar, Abbas; Emami Skardi, Mohammad J.; Masoumi, Fariborz
2015-09-01
Efficient reservoir management requires the implementation of generalized optimal operating policies that manage storage volumes and releases while optimizing a single objective or multiple objectives. Reservoir operating rules stipulate the actions that should be taken under the current state of the system. This study develops a set of piecewise linear operating rule curves for water supply and hydropower reservoirs, employing an imperialist competitive algorithm in a parameterization-simulation-optimization approach. The adaptive penalty method is used for constraint handling and proved to work efficiently in the proposed scheme. Its performance is tested deriving an operation rule for the Dez reservoir in Iran. The proposed modelling scheme converged to near-optimal solutions efficiently in the case examples. It was shown that the proposed optimum piecewise linear rule may perform quite well in reservoir operation optimization as the operating period extends from very short to fairly long periods.
Dynamic Feasible Region Genetic Algorithm for Optimal Operation of a Multi-Reservoir System
Directory of Open Access Journals (Sweden)
Bin Xu
2012-08-01
Full Text Available Seeking the optimal strategy of a multi-reservoir system is an important approach to develop hydropower energy, in which the Genetic Algorithm (GA is commonly used as an effective tool. However, when the traditional GA is applied in solving the problem, the constraints of water balance equation, hydraulic continuity relationship and power system load demand might be violated by the crossover and mutation operator, which decreases the efficiency of the algorithm in searching for a feasible region or even leads to a convergence on an infeasible chromosome within the expected generations. A modified GA taking stochastic operators within the feasible region of variables is proposed. When determining the feasible region of constraints, the progressive optimal approach is applied to transform constraints imposed on reservoirs into a singular-reservoir constraint, and a joint solution with consideration of adjacent periods at crossover or mutation points is used to turn the singular-reservoir constraints into singular variable constraints. Some statistic indexes are suggested to evaluate the performances of the algorithms. The experimental results show that compared to GA adopting a penalty function or pair-wise comparison in constraint handling, the proposed modified GA improves the refinement of the quality of a solution in a more efficient and robust way.
Study of operation optimization based on data mining technique in power plants
Institute of Scientific and Technical Information of China (English)
LI Jianqiang; LIU Jizhen; GU Junjie; NIU Chenglin
2007-01-01
The determination of operation optimization value is very important for economic analysis and operation optimization in power plants.The operation optimization value determined by traditional methods usually cannot reflect the actual running states correctly in power plants with the increase in running time.Based on a large amount of history data stored in power plants,a way of operation optimization by applying data mining technique is proposed.The structure of operation optimi-zation based on data mining is established and the fuzzy association rule mining algorithm is introduced to find the operation optimization target value to guide the operation in power plants.Based on the actual local data in a 300 MW unit,the operation optimization value in typical load ranges is found out by data mining to provide better adjustment guidance in industry process.Experimental results show that the determination of operation optimization value based on data mining can improve the efficiency and decrease the emission of pollutants.
Directory of Open Access Journals (Sweden)
Hao Bai
2015-03-01
Full Text Available A virtual power plant takes advantage of interactive communication and energy management systems to optimize and coordinate the dispatch of distributed generation, interruptible loads, energy storage systems and battery switch stations, so as to integrate them as an entity to exchange energy with the power market. This paper studies the optimal dispatch strategy of a virtual power plant, based on a unified electricity market combining day-ahead trading with real-time trading. The operation models of interruptible loads, energy storage systems and battery switch stations are specifically described in the paper. The virtual power plant applies an optimal dispatch strategy to earn the maximal expected profit under some fluctuating parameters, including market price, retail price and load demand. The presented model is a nonlinear mixed-integer programming with inter-temporal constraints and is solved by the fruit fly algorithm.
Supply Chain Optimized Strategies in the Mode of External Financing
Institute of Scientific and Technical Information of China (English)
Wenyi; DU; Xingzheng; AI; Xiaowo; TANG
2015-01-01
In the circumstance that market demand is uncertain,it studies the decision-making problem of supply chain financial system consisting of the single supplier,a capital constraint retailer and a bank. Considering the mode of external financing,we obtain the optimal order decision of the capital constraint retailer,the optimal financing rate and the optimal wholesale price of the supplier and analyze the effects of owned capitals of retailer on the optimized decision-making of supply chain financial system. At last,it demonstrates the effectiveness of conclusion by numerical examples.
Optimizing Multiple QoS for Workflow Applications using PSO and Min-Max Strategy
Umar Ambursa, Faruku; Latip, Rohaya; Abdullah, Azizol; Subramaniam, Shamala
2017-08-01
Workflow scheduling under multiple QoS constraints is a complicated optimization problem. Metaheuristic techniques are excellent approaches used in dealing with such problem. Many metaheuristic based algorithms have been proposed, that considers various economic and trustworthy QoS dimensions. However, most of these approaches lead to high violation of user-defined QoS requirements in tight situation. Recently, a new Particle Swarm Optimization (PSO)-based QoS-aware workflow scheduling strategy (LAPSO) is proposed to improve performance in such situations. LAPSO algorithm is designed based on synergy between a violation handling method and a hybrid of PSO and min-max heuristic. Simulation results showed a great potential of LAPSO algorithm to handling user requirements even in tight situations. In this paper, the performance of the algorithm is anlysed further. Specifically, the impact of the min-max strategy on the performance of the algorithm is revealed. This is achieved by removing the violation handling from the operation of the algorithm. The results show that LAPSO based on only the min-max method still outperforms the benchmark, even though the LAPSO with the violation handling performs more significantly better.
Optimal waste-to-energy strategy assisted by GIS For sustainable solid waste management
Tan, S. T.; Hashim, H.
2014-02-01
Municipal solid waste (MSW) management has become more complex and costly with the rapid socio-economic development and increased volume of waste. Planning a sustainable regional waste management strategy is a critical step for the decision maker. There is a great potential for MSW to be used for the generation of renewable energy through waste incineration or landfilling with gas capture system. However, due to high processing cost and cost of resource transportation and distribution throughout the waste collection station and power plant, MSW is mostly disposed in the landfill. This paper presents an optimization model incorporated with GIS data inputs for MSW management. The model can design the multi-period waste-to-energy (WTE) strategy to illustrate the economic potential and tradeoffs for MSW management under different scenarios. The model is capable of predicting the optimal generation, capacity, type of WTE conversion technology and location for the operation and construction of new WTE power plants to satisfy the increased energy demand by 2025 in the most profitable way. Iskandar Malaysia region was chosen as the model city for this study.
A typology for strategic supply-chain management : bridging the gap between operations and strategy
Connolly, Kate Phillips
2007-01-01
Over the last decade, supply-chain management (SCM), a field that emerged from the operational areas of purchasing and logistics, has become a focal area in business studies. However, efforts to move SCM from an operational to a more strategic perspective typically stop at the design, or operations strategy level, and it has proven difficult to move SCM to a strategic perspective. Led by operations and operations strategy researchers and practitioners, tremendous efforts have been made to dev...
Refrigerator Optimal Scheduling to Minimise the Cost of Operation
Directory of Open Access Journals (Sweden)
Bálint Roland
2016-12-01
Full Text Available The cost optimal scheduling of a household refrigerator is presented in this work. The fundamental approach is the model predictive control methodology applied to the piecewise affine model of the refrigerator.
Offshore Wind Farm Layout Design Considering Optimized Power Dispatch Strategy
DEFF Research Database (Denmark)
Hou, Peng; Hu, Weihao; N. Soltani, Mohsen
2017-01-01
leading to energy losses. It is expected that the optimized placement of wind turbines (WT) over a large sea area can lead to the best tradeoff between energy yields and capital investment. This paper proposes a novel way to position offshore WTs for a regular shaped wind farm. In addition to optimizing...
Educational Tool for Optimal Controller Tuning Using Evolutionary Strategies
Carmona Morales, D.; Jimenez-Hornero, J. E.; Vazquez, F.; Morilla, F.
2012-01-01
In this paper, an optimal tuning tool is presented for control structures based on multivariable proportional-integral-derivative (PID) control, using genetic algorithms as an alternative to traditional optimization algorithms. From an educational point of view, this tool provides students with the necessary means to consolidate their knowledge on…
A trust-region strategy for manifold-mapping optimization
Hemker, P.W.; Echeverria, D.
2007-01-01
Studying the space-mapping technique by Bandler et al. [J. Bandler, R. Biernacki, S. Chen, P. Grobelny, R.H. Hemmers, Space mapping technique for electromagnetic optimization, IEEE Trans. Microwave Theory Tech. 42 (1994) 2536–2544] for the solution of optimization problems, we observe the possible d
A trust-region strategy for manifold mapping optimization.
Hemker, P.W.; Echeverria, D.
2006-01-01
As a starting point we take the space-mapping iteration technique by Bandler et al. for the efficient solution of optimization problems. This technique achieves acceleration of accurate design processes with the help of simpler, easier to optimize models. We observe the difference between the soluti
Global Optimization strategies for two-mode clustering
J.M. van Rosmalen (Joost); P.J.F. Groenen (Patrick); J. Trejos (Javier); W. Castilli
2005-01-01
textabstractTwo-mode clustering is a relatively new form of clustering that clusters both rows and columns of a data matrix. To do so, a criterion similar to k-means is optimized. However, it is still unclear which optimization method should be used to perform two-mode clustering, as various meth
Directory of Open Access Journals (Sweden)
Kui-Ting CHEN
2015-12-01
Full Text Available Capacitated vehicle routing problem with pickups and deliveries (CVRPPD is one of the most challenging combinatorial optimization problems which include goods delivery/pickup optimization, vehicle number optimization, routing path optimization and transportation cost minimization. The conventional particle swarm optimization (PSO is difficult to find an optimal solution of the CVRPPD due to its simple search strategy. A PSO with adaptive multi-swarm strategy (AMSPSO is proposed to solve the CVRPPD in this paper. The proposed AMSPSO employs multiple PSO algorithms and an adaptive algorithm with punishment mechanism to search the optimal solution, which can deal with large-scale optimization problems. The simulation results prove that the proposed AMSPSO can solve the CVRPPD with the least number of vehicles and less transportation cost, simultaneously.
Optimal Strategy for Inspection and Repair of Structural Systems
DEFF Research Database (Denmark)
Thoft-Christensen, Palle; Sørensen, John Dalsgaard
1987-01-01
A new strategy for inspection and repair of structural elements and systems is presented. The total cost of inspection and repair is minimized with the constraints that the reliability of elements and/or of the structural system are acceptable. The design variables are the time intervals between...... inspections and the quality of the inspections. Numerical examples are presented to illustrate the performance of the strategy. The strategy can be used for any engineering system where inspection and repair are required....
Nested algorithms for optimal reservoir operation and their embedding in a decision support platform
Delipetrev, B.
2016-01-01
Reservoir operation is a multi-objective optimization problem traditionally solved with dynamic programming (DP) and stochastic dynamic programming (SDP) algorithms. The thesis presents novel algorithms for optimal reservoir operation named nested DP (nDP), nested SDP (nSDP), nested reinforcement le
Average optimization of the approximate solution of operator equations and its application
Institute of Scientific and Technical Information of China (English)
WANG; xinghua(王兴华); MA; Wan(马万)
2002-01-01
In this paper, a definition of the optimization of operator equations in the average case setting is given. And the general result (Theorem 1) about the relevant optimization problem is obtained. This result is applied to the optimization of approximate solution of some classes of integral equations.