求解置换流水线调度问题的改进萤火虫优化算法

针对最小化最大完成时间的置换流水线调度问题,提出了一种改进的离散萤火虫优化算法。在传统萤火虫优化算法的基础上,采用基于升序排序的随机键编码方式对萤火虫种群进行离散化处理,使用NEH算法对萤火虫种群进行初始化处理,结合遗传算法的交叉变异思想改进位置更新策略,采用个体变异方式解决孤立个体问题,提高算法的寻优能力。最后通过典型算例对改进算法进行仿真测试,实验结果表明该算法求解置换流水线调度问题时具备很强的寻优能力和鲁棒性,明显优于传统萤火虫优化算法和遗传算法,是解决置换流水线调度问题的一种有效算法。

Improved GSO Algorithm for Solving PFSP

An improved discrete glowworm swarm optimization (DGSO) was proposed for solving the permutation flow shop scheduling problem (PFSP) with the objective of minimizing makespan.On the basis of the traditional glowworm swarm optimization algorithm,this paper used a random key coding method based on the ascending order to discretize the glowworm swarm populations.Then it used the NEH algorithm to initialize the glowworm swarm populations,the idea of crossover and mutation thought in genetic algorithm was used to improve the location updating strategy,and individual mutation was used to resolve individual problems in isolation,improving the capability of algorithm optimization.Finally,the simulation test of the improved algorithm was carried out through typical examples.Simulation results show its efficiency and superiority for solving the PFSP.It is obviously better than the traditional glowworm swarm optimization and genetic algorithm,and it is an effective algorithm for solving flow shop scheduling problem.