Genetic Algorithm to Solve Optimization Problem with Equality Constrains

Abstract

Abstract: Aiming at difficultly solving optimization with equality constraint in genetic algorithm, based on independence analysis of design variables, a descending dimension method was used to deal with equality constraint. In this way, not only equality constraints can be strictly satisfied during optimization, but also there are only inequality constrains in optimization. Furthermore, referring to the multiobjective idea, individuals was ranked through violation degree and violation times simultaneously, which is more in accord with practice. Finally, three numerical examples were used to examine the proposed method, satisfying results were achieved, which indicates the method is valid and feasible.

Key words: genetic algorithm, equality constraint, descending dimension, rank, optimization

CLC Number:

TP18

HU Kuan-1, 2 , CHANG Xin-Long-1, SONG Bi-Feng-2, ZHANG Lin-3, LONG Bing-1, YU Yan-Feng-1. Genetic Algorithm to Solve Optimization Problem with Equality Constrains[J]. Journal of Shanghai Jiaotong University, 2011, 45(07): 966-969.

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