求解Flow Shop问题的改进遗传算法

Improvements of the Genetic Algorism for Solution of Flow Shop Scheduling Problems

在对FSP问题进行描述的基础上,提出了一种新的改进遗传算法。该算法针对遗传算法的弱点进行了一系列的改进:设计一个新的选择策略和一个新的多交叉算子策略来避免早熟并引入了兄弟竞争的策略来加快收敛速度和全局搜索能力。仿真计算表明了该算法的良好收敛性和有效性。

This paper brings forward a new enhanced Genetic Algorithm on the basis of depicting FSP problem. A lot of the improvements have been done aimed at the defect of the Genetic Algorithm. The improvements include a new design of selection strategy and multi-crossover strategy to avoid prematurity and a competition between brothers for the better ability of convergence＇s speed and the whole search. Simulation experiment shows the good convergence and effectiveness of this algorithm.