期刊
SWARM AND EVOLUTIONARY COMPUTATION
卷 15, 期 -, 页码 66-79出版社
ELSEVIER
DOI: 10.1016/j.swevo.2013.12.002
关键词
Genetic algorithm; Optimal sequence method; Multi-objective optimization; Constraint handling technique
A new constraint handling technique for multi-objective genetic algorithm is proposed in this paper. There are two important issues in multi-objective genetic algorithm, closeness of the obtained solutions to the real Pareto frontier and diversity of the obtained solutions. If considering a constrained multi-objective programming problem, one needs to take account of feasibility of solutions. Thus, in this new constraint handling technique, we systematically take closeness, diversity and feasibility as three objectives in a multi-objective subproblem. And solutions in each iteration are sorted by optimal sequence method based on those three objectives. Then, the solutions inherited to the next generation are selected based on its optimal order. Numerical tests show that the solutions obtained by this method are not only feasible, but also close to the real Pareto front and have good diversity. (C) 2013 Elsevier B.V. All rights reserved.
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