A Bi-level Multiobjective PSO Algorithm

被引:7
作者
Carrasqueira, Pedro [1 ]
Alves, Maria Joao [2 ]
Antunes, Carlos Henggeler [3 ]
机构
[1] INESC Coimbra, Coimbra, Portugal
[2] Univ Coimbra, Fac Econ, INESC Coimbra, Coimbra, Portugal
[3] Univ Coimbra, Dept Elect Engn & Comp, INESC Coimbra, Coimbra, Portugal
来源
EVOLUTIONARY MULTI-CRITERION OPTIMIZATION, PT I | 2015年 / 9018卷
关键词
PARTICLE SWARM OPTIMIZATION;
D O I
10.1007/978-3-319-15934-8_18
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Bi-level optimization represents a class of optimization problems with two decision levels: the upper level (leader) and the lower level (follower). Bi-level problems have been extensively studied for single objective problems, but there is few research in case of multiobjective problems in both levels. This case is herein studied using a multiobjective particle swarm optimization (MOPSO) based algorithm. To solve the bi-level multiobjective problem the algorithm searches for upper level Pareto optimal solutions. In every upper level search, the algorithm solves a lower level multiobjective problem in order to find a representative set of lower level Pareto optimal solutions for a fixed upper level vector of decision variables. The search in both levels is performed using the operators of a MOPSO algorithm. The proposed algorithm is able to solve bi-level multiobjective problems achieving solutions in the true Pareto optimal front or close to it.
引用
收藏
页码:263 / 276
页数:14
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