Abstract：As Genetic Algorithms handles the constraint optimization problem,the difficulty is how to solve the constraints.According to this problem,a new improved Genetic Algorithms (CIFGA) is proposed.The key strategy in CIFGA is that the whole infeasible individuals,appeared after each generation,will be transformed into feasible ones.Go through generation after generation,the optimum solution of optimization problem can be founded.The CIFGA,with either binary coding or real coding,is proved to converge to global optimum solution.The experimental results show that CIFGA has great advantage of convergence property over the GAs based on Penalty Function(PFGA),and has good ability of solving constrained optimization in general purpose.
高玉根;程峰;王灿;王国彪. 基于违约解转化法的遗传算法及其性能分析[J]. 电子学报, 2006, 34(4): 638-641.
GAO Yu-gen;CHENG Feng;WANG Can;WANG Guo-biao. A New Improved Genetic Algorithms Based on Converting Infeasible Individuals into Feasible Ones and Its Property Analysis. Chinese Journal of Electronics, 2006, 34(4): 638-641.
2006, Vol. 34 
