基于遗传算法的带时间窗的多目标flow-shop调度

Multi-objective Flow-shop Scheduling with Time Window Based on Genetic Algorithm

结合实际生产,引入机器的空闲时间建立了一个带有时间窗的flow-shop优化调度模型。通过非支配排序来进行群体虚拟适应度值的分配,引入精英解策略来保证算法的收敛性和解的多样性,运用小生境技术来避免局部收敛和早熟,维持种群多样性。通过仿真实验得到模型具有实际意义,算法具有可行性。

Combined with practical production, the spare time of the machines was introduced to build a flow-shop scheduling model with time window. The community hypothesized sufficiency value was carried on through non-control sorting the assignment. The elitist solutions to guar- antee the convergence of the algorithm and the multiplicity of the solutions were introduced. The niche technology was used to prevent local convergence and premature, maintain population diversity. Through the simulation experiment, it was obtained that the model have practical significance and the algorithm has the feasibility.