有约束优化中遗传算法的应用

以列车操纵优化中为每个行车子区间分配时间片段这一实际问题为背景, 详细介绍了用遗传算法(GA ) 利用引进惩罚项解决这一类有约束优化问题。同时给出了GA 对于有约束问题的几点改进方法: 用交叉基始位加快进化进程、用变异环境串来激励出更优秀的个体。 

Application of Genetic Algorithm to Constrained Optimization

With a practical problem of distributing moments by each regions in train optimum operations being taken as a background, the solution to the constrained optimization by applying genetic algorithm (GA) is described in detail. Some improved GA methods used in the constrained optimization is presented, i.e., the cross base bit is employed to accelerate the optimizing process, and the mutation environment string is used to simulate and produce much better individuals.