研究了多机多任务的车间天车调度问题,提出了一种结合免疫遗传算法的仿真模型解决方案.该方案建立了能反映天车实际工作环境运行特征的仿真模型,根据天车作业跨的工位与天车位置关系进行模型空间抽象,用可变的天车任务优先级来解决天车运行过程中空间约束导致的多机多任务冲突;仿真模型用于评估各种调度方案,免疫遗传算法则使调度方案在不断的迭代中持续优化.以某钢厂一主作业跨的天车调运任务问题制定天车调度方案进行模型检验,对求解的可行天车任务分配方案,进行比较分析,说明了模型方法的有效性与工程应用的可行性.
A simulation model combining immune and genetic algorithm is proposed to solve multi-machine multi-task crane scheduling in job shop. Simulation model represents the crane characteristics of natural working environments where spatial abstraction is based on the locations between work stations and cranes in the same span. During scheduling process, multi-machine multi-task confliction is settled considering spatial constraints with available crane task priorities. Crane scheduling is evaluated by simulation model, while optimization is iterated with immune and genetic algorithm. Crane scheduling in a major span of a steelmaking factory is made to validate the simulation model, and compare between feasible schemes is given. The result shows efficiency and feasibility in industry.