| A Class of Optimization Method for Bilevel Multi-objective Decision Making Problem with the Help of Satisfactoriness |
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| 作者姓名： | LITong TENGChun－xian 等 |
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| 作者单位： | LI Tong 1，2，TENG Chun-xian 3，LI Hao-bai 3 1.Tianjin University，Tianjin 300072，China 2.Dalian University，Dalian 116622，China 3.Harbin University of Science and Technology，Harbin 150080，China |
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| 基金项目： | This project is supported by National Natural Science Foundation of China( 6 9874 0 0 9) and theNatural Science Foundation of Heilongjiang Province( A0 0 0 4 ) |
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| 摘 要： | 1 IntroductionWe discuss the following bilevel multi-objective decision making problemmaxx F( x,y) ( 1 a)s.t. G( x,y)≤ 0 ( 1 b)maxyifi( x,yi) , i =1 ,… ,p ( 1 c)s.t. gi( x,gi)≤ 0 , i =1 ,… ,p ( 1 d)where F( x,y) =( F1 ( x,y) ,… ,FM( x,y) ) ,M≥ 2 .x=( x1 ,x2 ,… ,x N) Tand yi=( yi1 ,… ,yin) Tstand for the decision variable of the upper-level decision maker and the decision variable ofthe lower-level i-th decision making unit;y=( y T1 ,… ,y Tp) T;letn =∑pi=1ni;F∶ Rn N → RM…
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| 关 键 词： | 系统最优化分类 多客体决策 模拟退火算法 |
A Class of Optimization Method for Bilevel Multi-objective Decision Making Problem with the Help of Satisfactoriness |
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| LI Tong,TENG Chun-xian,LI Hao-bai.A Class of Optimization Method for Bilevel Multi-objective Decision Making Problem with the Help of Satisfactoriness[J].Journal of Systems Science and Systems Engineering,2002,11(1):6-12. |
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| Authors: | LI Tong TENG Chun-xian LI Hao-bai |
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| Institution: | 1. Tianjin University, Tianjin 300072, China;Dalian University, Dalian 116622, China
2. Harbin University of Science and Technology, Harbin 150080, China |
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| Abstract: | In the paper, it is discussed that the method on how to transform the multi-person bilevel multi-objective decision making problem into the equivalent generalized multi-objective decision making problem by using Kuhn-Tucker sufficient and necessary condition. In order to embody the decision maker's hope and transform it into single-objective decision making problem with the help of e-constraint method.Then we can obtain the global optimal solution by means of simulated annealing algorithm. |
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| Keywords: | bilevel multi-objective decision making satisfactoriness non-inferior solution simulated annealing algorithm |
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