基于直觉模糊数的电动汽车集中充电中心选址决策研究
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摘要
为有效促进电动汽车市场化,本文提出基于改进前景理论的直觉模糊多准则决策分析方法,并将其应用于电动汽车电池集中充电中心的选址决策。构建电池集中充电中心选址的评价指标体系,建立直觉模糊评价矩阵,并定义新的记分函数,据此将直觉模糊评价矩阵转化为实数评价矩阵;考虑到决策者的非理性行为,引入改进的前景理论,构建改进的前景决策矩阵;建立综合考虑主、客观因素的优化定权模型;结合改进的前景决策矩阵及准则权重提出基于改进前景理论的直觉模糊多准则决策方法;基于该方法研究电池集中充电中心的选址问题,为此类问题提供一种有效的分析方法,并通过算例对此类问题进行优化决策。
In order to effectively promote the marketization of electric vehicles,this paper provides an intuitionistic fuzzy multi-criteria decision-making analysis method based on the improved prospect theory,and applies it to the site selection decision of battery centralized charging centers for electric vehicles. Firstly,we establish an evaluation index system for battery centralized charging center location,an intuitionistic fuzzy evaluation matrix and define a new score function. Based on this,the intuitionistic fuzzy evaluation matrix is converted into a real number evaluation matrix. Secondly,considering the irrational behavior of decision makers,the improved outlook theory is introduced to construct an improved outlook decision matrix. Third,establish an optimization and weighting model that comprehensively considers the main and objective factors. Then,an intuitionistic fuzzy multi-criteria decision-making method based on improved prospect theory is proposed in combination with improved foreground decision matrix and criterion weights. Based on this method,the problem of location selection of battery centralized charging centers is studied,and an effective analysis method for such problems is provided. Through optimization examples,such problems are optimized and determined.
In order to effectively promote the marketization of electric vehicles,this paper provides an intuitionistic fuzzy multi-criteria decision-making analysis method based on the improved prospect theory,and applies it to the site selection decision of battery centralized charging centers for electric vehicles. Firstly,we establish an evaluation index system for battery centralized charging center location,an intuitionistic fuzzy evaluation matrix and define a new score function. Based on this,the intuitionistic fuzzy evaluation matrix is converted into a real number evaluation matrix. Secondly,considering the irrational behavior of decision makers,the improved outlook theory is introduced to construct an improved outlook decision matrix. Third,establish an optimization and weighting model that comprehensively considers the main and objective factors. Then,an intuitionistic fuzzy multi-criteria decision-making method based on improved prospect theory is proposed in combination with improved foreground decision matrix and criterion weights. Based on this method,the problem of location selection of battery centralized charging centers is studied,and an effective analysis method for such problems is provided. Through optimization examples,such problems are optimized and determined.
引文
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[14]王坚强,李婧婧.基于记分函数的直觉随机多准则决策方法[J].控制与决策,2010,25(9):1297~1306.
[15] Kahneman D,Tversky A. Prospect Theory:An Analysis of Decision Under Risk[J]. Econometrica,1979,47(2):263~291.
[16]马健,孙秀霞.基于效用曲线改进的前景理论价值函数[J].信息与控制,2011,40(4):501~506
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[18] Wang Y M,Luo Y,Liu X W. Two New Models for Determining OWA Operator Weights[J]. Computers&Industrial Engineering,2007,52:203~209.
[19] Chen T,Li C. Determining Objective Weights with Intuitionistic Fuzzy Entropy Measures:A Comparative Analysis[J]. Information Sciences,2010,180(21):4207~4222.
[20] Wang Y,Luo Y. Integration of Correlations with Standard Deviations for Determining Attribute Weights in Multiple Attribute Decision Making[J]. Mathematical and Computer Modelling,2010,51(1):1~12.
[21] Wei G W. Maximizing Deviation Method for Multiple Attribute Decision Making in Intuitionistic Fuzzy Setting[J]. KnowledgeBased Systems,2008,21(8):833~836.
[2]唐现刚,刘俊勇,刘友波,等.基于计算几何方法的电动汽车充电站规划[J].电力系统自动化,2012,36(8):24~30.
[3]杨珺,冯鹏祥,孙昊,等.电动汽车物流配送系统的换电站选址与路径优化问题研究[J].中国管理科学,2015,55:217~232.
[4]王辉,王贵斌,赵俊华,等.考虑交通网络流量的电动汽车充电站规划[J].电力系统自动化,2013,37(13):63~69.
[5]贾斯佳,袁竞峰.电动汽车基础设施选址定容研究——以南京市河西新城为例[J].科技管理研究,2018,1:223~232.
[6]葛少云,李荣,韩俊,等.考虑电动出租车随机概率行为特性的充电站规划[J].电力系统自动化,2016,40(4):50~58.
[7]冯超,周步祥,林楠,等. Delphi和GAHP集成的综合评价方法在电动汽车充电站选址最优决策中的应用[J].电力自动化设备,2012,32(9):25~29.
[8]王萌,刘凯,牛利勇,等.电动汽车充电站选址决策与评价研究[J].物流技术,2015,34(9):117~121.
[9] Guo Sen,Zhao Huiru. Optimal Site Selection of Electric Vehicle Charging Station by Using Fuzzy TOPSIS Based on Sustainability Perspective[J]. Applied Energy,2015,158:390~402.
[10] Atanassov K. lntuitionistic Fuzzy Sets[J]. Fuzzy Sets and Systems,1986,20(1):87~96.
[11] Chen S M,Tan J M. Handling Multi-criteria Fuzzy Decisionmaking Problems Based on Vague Set Theory[J]. Fuzzy Sets and Systems,1994,67(2):163~172.
[12] Hong D H,Choi C H. Multi-criteria Fuzzy Decision-making Problems Based on Vague Set Theory[J]. Fuzzy Sets and Systems,2000,114(1):103~113
[13] Ye J. Improved Method of Multi-criteria Fuzzy Decision-making Based on Vague Sets[J]. Computer-Aided Design,2007,39:164~169.
[14]王坚强,李婧婧.基于记分函数的直觉随机多准则决策方法[J].控制与决策,2010,25(9):1297~1306.
[15] Kahneman D,Tversky A. Prospect Theory:An Analysis of Decision Under Risk[J]. Econometrica,1979,47(2):263~291.
[16]马健,孙秀霞.基于效用曲线改进的前景理论价值函数[J].信息与控制,2011,40(4):501~506
[17] Bernoulli D. Exposition of a New Theory on the Measurement of Risk[J]. Econometrica,1954,22(1):22~36.
[18] Wang Y M,Luo Y,Liu X W. Two New Models for Determining OWA Operator Weights[J]. Computers&Industrial Engineering,2007,52:203~209.
[19] Chen T,Li C. Determining Objective Weights with Intuitionistic Fuzzy Entropy Measures:A Comparative Analysis[J]. Information Sciences,2010,180(21):4207~4222.
[20] Wang Y,Luo Y. Integration of Correlations with Standard Deviations for Determining Attribute Weights in Multiple Attribute Decision Making[J]. Mathematical and Computer Modelling,2010,51(1):1~12.
[21] Wei G W. Maximizing Deviation Method for Multiple Attribute Decision Making in Intuitionistic Fuzzy Setting[J]. KnowledgeBased Systems,2008,21(8):833~836.