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Integrated Process Planning and Scheduling - Multi-Agent System with Ant Algorithm

机译:具有Ant算法的集成流程规划和调度 - 多智能体系

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In this paper, an ant colony optimization (ACO) algorithm is implemented in a multi-agent system (MAS) to accomplish integrated process planning and scheduling (IPPS) in the job shop type of flexible manufacturing environments. Traditionally, process planning and scheduling functions are performed sequentially and the actual status of the production facilities is not considered in either process planning or scheduling. IIPPS is to combine both the process planning and scheduling problems in the consideration, that is, the actual process plan and the schedule are determined dynamically in accordance with the order details and the status of the manufacturing system. The ACO algorithm will be able to support dynamic process planning, scheduling and rescheduling. Performance of the combined approach of ACO algorithm and MAS will be evaluated according to different criteria including make-span, tardiness, and machine utilization.
机译:在本文中,蚁群优化(ACO)算法在多代理系统(MAS)中实现,以在柔性制造环境的作业商店类型中实现集成的过程规划和调度(IPPS)。传统上,顺序执行流程规划和调度功能,并且在处理规划或调度中不考虑生产设施的实际状态。 IIPPS将在考虑中组合过程规划和调度问题,即实际的过程计划和计划按照订单详细信息和制造系统的状态动态确定。 ACO算法将能够支持动态过程规划,调度和重新安排。 ACO算法和MAS的组合方法的性能将根据不同的标准进行评估,包括制作跨度,迟到和机器利用率。

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