Paper Info
Title
Uniform Design Based Hybrid Genetic Algorithm for Multiobjective Bilevel Convex Programming
Abstract
Multiobjective bilevel linear programming is a decentralized decision problem, it consists of many objectives at the upper level and the lower level, respectively. It has a wide field of applications and has been proven to be NP-hard. In this paper, a kind of multiobjective bilevel convex programming(MBCP) is studied, in which the lower level is first transformed into an equivalent single objective bilevel convex programming problem by weighted aggregation method. Then, for the equivalent problem, we use uniform design scheme to generate some representative weight vectors. Thereafter, a crossover operator and mutation operator are designed. Based on all these, a uniform design based hybrid genetic algorithm is proposed for MBCP. Finally, the performance of the proposed algorithm is illustrated by two numerical experiments. The results (including the compared results) show that the proposed algorithm is effective.
Year
DOI
Venue
2011
10.1109/CIS.2011.43
CIS
Keywords
Field
DocType
multiobjective bilevel convex programming,equivalent problem,upper level,decentralized decision problem,hybrid genetic algorithm,proposed algorithm,multiobjective bilevel linear programming,convex programming problem,lower level,equivalent single objective bilevel,uniform design,vectors,genetic algorithm,genetic algorithms,pareto optimization,decision problem,linear programming,algorithm design,algorithm design and analysis,linear program,convex programming,programming,computational complexity
Computer science,Multi-objective optimization,Artificial intelligence,Linear programming,Genetic algorithm,Mathematical optimization,Decision problem,Algorithm design,Crossover,Algorithm,Convex optimization,Machine learning,Computational complexity theory
Conference
Citations 
PageRank 
References 
2
0.38
6
Authors
3
Name
Order
Citations
PageRank
Li-Ping Jia1547.81
Yuping Wang2106091.93
Lei Fan3485.70