基于混合遗传算法的工艺路线优化配置

Process Route Optimization of FMS Based on Hybrid Genetic Algorithm

针对 FMS工艺路线优化配置问题提出一种混合遗传算法。该算法在遗传算法中引入了具有启发式规则的余量随机分配算子 ,可以将超过约束条件的余量随机分配到个体中去 ,通过按照一定规则的调整而将不可行个体引入可行域。一方面实现了利用遗传算法求解工艺路线的约束优化问题 ,保持了遗传算法的全局寻优特点 ,另一方面加强了遗传算法的局部搜索能力 ,提高了运行效率。算例证明该算法的求解效果好于目前该领域常用的启发式算法。

A hybrid genetic algorithm (HGA) was proposed for process route optimization of FMS(Flexible Manufacturing System) based on closed queueing networks. This algorithm imbeds an operator called as Operator for Distributing Remainder Randomly in GA to resolve the constraint optimal problem. The operator distributes equation constraints over individuals randomly and guides the individuals into feasible region from infeasible region by heuristic rules, thus making the HGA capable of solving the constraint optimal problem and enhancing its ability of local search. Accordingly, the HGA not only inherits GA's global optimization feature, but is more efficient. Calculations show that HGA is better than heuristic methods.