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RFID technology investment evaluation model for the stochastic joint replenishment and delivery problem

EXPERT SYSTEMS WITH APPLICATIONS 2014年第4期41卷 1792-1805页

作者： Cui, Ligang Wang, Lin Deng, Jie Huazhong Univ Sci & Technol Sch Management Wuhan 430074 Peoples R China City Univ Hong Kong Dept Management Sci Kowloon Tong Hong Kong Peoples R China

Radio Frequency Identification (RFID) can help to share information in real time, detect and trace multi-item simultaneously, with which the joint replenishment can be efficiently realized, and proper RFID adoptions can also improve the delivery efficiencies. To investigate the effects of RFID investment, we firstly propose an RFID-based investment evaluation model for the joint replenishment and delivery problem (JRD) under stochastic demand. Unlike existing study on the JRD, we also adopt an effective multi-stage delivery policy in replenishment cycles which can result in delivery cost savings. Secondly, a differential evolution algorithm (DE) is adopted to solve the proposed JRD, which can find the best cycle time of each item, the best basic cycle time and the best and longest delivery route simultaneously, and can dynamically generate the service routes under different number of visiting supplier(s). Thirdly, the effectiveness and efficiency of the proposed JRD model and DE-based solution were verified by a classic case and sensitivity analyses on RFID investment related parameters were performed. At last, the proposed model and solution were further tested by a larger scale case. Results and implications from the experiments show great benefits can be obtained if the RFID investment scale is controlled in a proper range. Crown Copyright (C) 2013 Published by Elsevier Ltd. All rights reserved.

关键词： RFID investment Joint replenishment and delivery differential evolution algorithm

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Induction motor parameter estimation using metaheuristic methods

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TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2014年第5期22卷 1177-1192页

作者： Canakoglu, All Ihsan Yetgin, Asim Gokhan Temurtas, Hasan Turan, Mustafa Dumlupinar Univ Fac Engn Dept Elect & Elect Engn Kutahya Turkey Dumlupinar Univ Fac Engn Dept Comp Engn Kutahya Turkey Sakarya Univ Fac Engn Dept Elect & Elect Engn Sakarya Turkey

The steady-state equivalent circuit parameters of an induction motor can be estimated using the operation characteristics that are provided by manufacturers. The characteristics of the motor used in estimation methods are the starting, maximum, and nominal torque values;the power factor;and efficiency. The operation characteristics of a motor given in data sheets are generally based on design parameters and are not suitable with real values. For this reason, in this paper, the data used in the parameter estimation for induction motors are taken from the literature. Using an optimization method for parameter estimation is useful for comparing the manufacturer values and values at the end of estimation, as well as minimizing the error in between. There are many methods in the literature for the parameter estimation of induction motors. In this study, the estimation is made using the charged system search (CSS), differential evolution algorithm (DEA), particle swarm optimization, and genetic algorithm optimization techniques. The CSS algorithm is first applied for estimation of the parameters of an induction motor. The results obtained from all of the methods show that the CSS algorithm is suitable with the DEA. From the obtained results, it is understood that an exact approach can be made to equivalent circuit parameters in case the values given by the manufacturer model the motor properly.

关键词： Induction motor exact equivalent circuit parameters torque values charged system search differential evolution algorithm particle swarm optimization genetic algorithm

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On-line coordination of directional overcurrent relays: Performance evaluation among optimization algorithms

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ELECTRIC POWER SYSTEMS RESEARCH 2014年第0期110卷 122-132页

作者： Yen Shih, Meng Conde Enriquez, Arturo Torres Trevino, Luis Martin Univ Autonoma Nuevo Leon UANL FIME San Nicolas De Los Garza 66451 NL Mexico

The coordination of directional overcurrent relays is most commonly studied based on a fixed network topology in a mesh electrical system. However, in real life, the network topology and the operation of elements of sub-transmission and distribution systems are constantly changing. In addition, modern electrical systems tend to operate near boundary conditions to satisfy the clients. As a result, the directional overcurrent relays (DOCRs) lose speed and sensitivity. Therefore, the principal objective of this paper is to perform on-line coordination of the directional overcurrent relays in order to enhance speed and sensitivity. The secondary objective is to formulate the differential evolution algorithm and compare it with the genetic algorithm and ant colony algorithm. The objectives were accomplished by developing an on-line algorithm that worked with the optimization algorithms. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Ant colony algorithm differential evolution algorithm Dynamic network topologies Genetic algorithm On-line Overcurrent relay coordination

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Open vehicle routing problem with demand uncertainty and its robust strategies

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EXPERT SYSTEMS WITH APPLICATIONS 2014年第7期41卷 3569-3575页

作者： Cao Erbao Lai Mingyong Yang Hongming Hunan Univ Dept Econ & Trade Changsha 410079 Hunan Peoples R China Hunan Prov Lab Logist Informat & Simulat Technol Changsha 410079 Hunan Peoples R China Changsha Univ Sci & Technol Coll Elect & Informat Engn Changsha 410004 Hunan Peoples R China

We investigate the open vehicle routing problem with uncertain demands, where the vehicles do not necessarily return to their original locations after delivering goods to customers. We firstly describe the customer's demand as specific bounded uncertainty sets with expected demand value and nominal value, and propose the robust optimization model that aim at minimizing transportation costs and unsatisfied demands in the specific bounded uncertainty sets. We propose four robust strategies to cope with the uncertain demand and an improved differential evolution algorithm (IDE) to solve the robust optimization model. Then we analyze the performance of four different robust strategies by considering the extra costs and unmet demand. Finally, the computational experiments indicate that the robust optimization greatly avoid unmet demand while incurring a small extra cost and the optimal return strategy is the best strategy by balancing the trade-off the cost and unmet demand among different robust strategies. Crown Copyright (C) 2013 Published by Elsevier Ltd. All rights reserved.

关键词： Distribution strategy Open vehicle routing problem Uncertainty Robust optimization differential evolution algorithm

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A study on the characteristics, predictions and policies of China's eight main power grids

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ENERGY CONVERSION AND MANAGEMENT 2014年 86卷 818-830页

作者： Wang, Jianzhou Dong, Yao Jiang, He Dongbei Univ Finance & Econ Sch Stat Dalian 116025 Peoples R China Lanzhou Univ Sch Math & Stat Lanzhou 730000 Peoples R China Florida State Univ Dept Stat Tallahassee FL 32306 USA

Electricity is an indispensable energy source for modern social and economic development. However, large-scale blackouts can cause incalculable loss to society. In 2012, three major Indian power grids collapsed, resulting in the interruption of the electricity supply to over 600 million people. To avoid an event like that, China needs to forecast the power generation and consumption of eight power grids effectively. This paper first analyzes the characteristics of eight power grids and then proposes a combined model based on three improved grey models optimized by a differential evolution algorithm to predict electricity production and consumption of each power grid. The optimized combined forecasting model provides a better prediction than other models, and it is also the most workable and satisfactory model. Experiment results show electricity production and consumption would increase. In consideration of the real situation and existing problems, some suggestions are proposed. The government could decrease thermal power and exploit renewable energy power, like hydroelectric power, wind power and solar power, to ensure the safe and reliable operation of China's major power grids and protect environment. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： China's power grids Electricity production and consumption Indian blackout Combined forecasting model differential evolution algorithm

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Real Time Optimization of a Natural Gas Lift System with a differential Evaluation Method

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ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS 2014年第3期36卷 309-322页

作者： Frooqnia, A. Pishvaie, M. R. Aminshahidy, B. Sharif Univ Technol Chem Engn & Petr Dept Tehran Iran Univ Tehran Inst Petr Engn Tehran Iran

This article presents a method for optimizing and controlling an oil production system using a natural gas lift concept. Ever increasing development of Smart Well technology and various applications of down-hole monitoring and controlling instruments along with new methods of data acquisition/transmission make it possible for the natural gas lift system to be controlled and optimized more effectively and faster than before. With this technology it is possible to monitor the down-hole conditions of gas and oil zones and to control the inflow valves in gas and oil zones. In this work, a proportional integral differential feedback controller has been used to smartly control the entrance of gas from the gas zone to the oil well. The optimizer determines the optimal values of gas injection setpoint for the controller to manipulate the inflow of gas to the oil reservoir. The problem will be more complex when the available gas in the gas zone is limited. The optimization of this process has been done by a differential evolution method.

关键词： differential evolution algorithm natural gas lift proportional integral differential feedback controller real time optimization smart wells

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Multi Stage Promotional Resource Allocation for Segment Specific and Spectrum Effect of Promotion for a Product Incorporating Repeat Purchase Behavior

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INTERNATIONAL GAME THEORY REVIEW 2015年第2期17卷 1540021-1540021页

作者： Manik, Prerna Gupta, Anshu Jha, P. C. Univ Delhi Fac Math Sci Dept Operat Res Delhi 110007 India Dr BR Ambedkar Univ Sch Business Publ Policy & Social Entrepreneurshi Sect 9 Delhi 110077 India

Promotion plays an important role in determining fate of a product. It voices product qualities and persuades potential customers to make purchases. In todays diversified markets every customer has individual needs and preferences. This calls for market segmentation which facilitates companies to adopt customer driven marketing. Product is also promoted using mass promotion to influence larger markets and segments with a spectrum effect. Existing literature in promotion resource allocation optimization evades distinction in two types of promotion strategies while allocating resources and primarily focuses on either of them statically. In this paper, we formulate an optimization model which dynamically allocates differentiated and mass promotional resources in segments to maximize sales under budgetary and minimum market share aspiration constraint on each segment as well as on total market share including repeat purchase behavior. Planning horizon is divided into multi-periods, adoption pattern is studied in each period and then resources are allocated attuned to current market behavior. Dynamic allocation provides a way to track the market potential expansion due to promotion and plan the allocation for the uncaptured potential. The proposed optimization model is NP hard and very challenging to solve. Solution methodology is presented with practical application based on real-time data using differential evolution algorithm.

关键词： Market segmentation differentiated market promotion mass market promotion spectrum effect dynamic promotional effort allocation repeat purchase NP-hard differential evolution algorithm durable technology product innovation diffusion models

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Substation Planning Based on Geographic Information and differential evolution algorithm

Substation Planning Based on Geographic Information and Diff...

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International Conference on Sustainable Power Generation and Supply

作者： Wang Zhiqiang Zhang Xin Liu Wenxia Liu Boliang N China Elect Power Univ Dept Elect & Elect Engn Sch Elect & Elect Engn Beijing 102206 Peoples R China Southeat Univ Sch Elect & Elect Engn Nanjing Peoples R China

ISBN: (纸本)9781424449347

In this paper the differential evolution (DE) algorithm is used to solve the substation location optimization problem for a distribution network. To improve the capability of the DE algorithm, the dynamic parameter adjustment strategy is used to guarantee the multiplicity of colony in the initial computation period and enhance the optimization speed of the algorithm in the later period. Using the knowledge of the Geographic Information System, the graph of possible area of substation location is encoded and stored in data form, the suitable location area is selected on the comparison of network topologies of optional location areas and geographic information. Through the simulation and analysis of a practical example the idea of combining the DE algorithm with graphical display based on GIS database has been successfully employed in distribution network planning

关键词： differential evolution algorithm Substation locating and sizing geography information system

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Three-dimensional WSN Node Localization Method Based on LSSVR Optimized by DE algorithm

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RECENT ADVANCES IN ELECTRICAL & ELECTRONIC ENGINEERING 2014年第2期7卷 123-129页

作者： Zhang, Lieping Ji, Wenjun Chen, Ming Guilin Univ Technol Guang Xi Key Lab New Energy & Bldg Energy Saving Guilin 541004 Peoples R China Guilin Univ Technol Coll Mech & Control Engn Guilin 541004 Peoples R China

Aiming at the problem that the three-dimensional (3D) node localization precision is affected by the model parameters of least squares support vector regression (LSSVR) node localization method for wireless sensor network, a localization method based on LSSVR optimized by differential evolution (DE) algorithm is proposed in this paper. Firstly, the 3D node localization model is built through LSSVR and the kernel function parameter and the regularization parameter are optimized by DE algorithm. Then, the fitness function of DE algorithm is constructed according to the mean square error of a number of virtual nodes from the predicted position and their actual position, and the global optimal parameters of LSSVR are acquired through limited modeling parameters iterative searching method. Finally, the LSSVR optimized by DE algorithm is used to realize the node localization. The simulation results show that the localization accuracy of the proposed method is superior to that of least square (LS) and LSSVR method.

关键词： differential evolution algorithm least square support vector regression three-dimensional node localization wireless sensor network

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Developing a likely climate scenario from multiple regional climate model simulations with an optimal weighting factor

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CLIMATE DYNAMICS 2014年第1-2期43卷 11-35页

作者： Eum, Hyung-Il Gachon, Philippe Laprise, Rene Environm Canada W CIRC STN CSC Victoria BC V8W 3R4 Canada Univ Quebec Montreal PQ H2X 3Y7 Canada Environm Canada Div Climate Res Canadian Ctr Climate Modelling Montreal PQ H5A 1L9 Canada Environm Canada Div Climate Res Anal Sect Montreal PQ H5A 1L9 Canada

This study presents a performance-based comprehensive weighting factor that accounts for the skill of different regional climate models (RCMs), including the effect of the driving lateral boundary condition coming from either atmosphere-ocean global climate models (AOGCMs) or reanalyses. A differential evolution algorithm is employed to identify the optimal relative importance of five performance metrics, and corresponding weighting factors, that include the relative absolute mean error (RAME), annual cycle, spatial pattern, extremes and multi-decadal trend. Based on cumulative density functions built by weighting factors of various RCMs/AOGCMs ensemble simulations, current and future climate projections were then generated to identify the level of uncertainty in the climate scenarios. This study selected the areas of southern Ontario and Qu,bec in Canada as a case study. The main conclusions are as follows: (1) Three performance metrics were found essential, having the greater relative importance: the RAME, annual variability and multi-decadal trend. (2) The choice of driving conditions from the AOGCM had impacts on the comprehensive weighting factor, particularly for the winter season. (3) Combining climate projections based on the weighting factors significantly increased the consistency and reduced the spread among models in the future climate changes. These results imply that the weighting factors play a more important role in reducing the effects of outliers on plausible future climate conditions in regions where there is a higher level of variability in RCM/AOGCM simulations. As a result of weighting, substantial increases in the projected warming were found in the southern part of the study area during summer, and the whole region during winter, compared to the simple equal weighting scheme from RCM runs. This study is an initial step toward developing a likelihood procedure for climate scenarios on a regional scale using equal or different probabilities for

关键词： Ensemble simulations Regional climate models Probabilistic climate change scenarios Comprehensive weighting factor differential evolution algorithm Uncertainties analysis

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