基于改进遗传算法的FlowShop调度算法研究

Research on Flow Shop Scheduling Problem Based on Improved Genetic Algorithm

给出了Flow Shop调度问题的数学模型,介绍了三种用于求解该问题的启发式算法,根据普通遗传算法与启发式算法的互补特性,提出了结合两者各自优势的改进遗传算法.通过两个不同规模的经典算例对算法的优化性能进行了对比分析,结果表明,采用了保优策略的改进遗传算法的搜索能力优于启发式算法及普通遗传算法,并具有较强的鲁棒性.

This paper introduces a mathematical model of Flow Shop Problem（FSP）, and then gives three heuristic algorithms to solve it. The new improved Genetic Algorithm（GA） is presented by combining the advantages of standard GA and heuristic algorithm. With two benchmark FSPs, the simulation results show that the new method of GA by using elitist selection strategy has better performance than standard GA and heuristic algorithm, and has strong robustness.