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Integration of Process Planning and Production Scheduling Based on A Hybrid PSO and SA Algorithm

机译:基于混合PSO和SA算法的工艺计划与生产调度集成。

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Process planning and production scheduling play important roles in manufacturing systems. In this paper, a fuzzy inference system(FIS) in choosing alternative machines for integrated process planning and scheduling of a job shop manufacturing system are proposed. Machines will be chosen based on the machine's reliability characteristics. This will ensure the capability of the machine in fulfilling the production demand. In addition, based on the capability information, the load for each machine is balanced by using the Particle Swarm Optimization (PSO). Simulation study shows some promising results in integrating production capability and load balancing during scheduling activity. There are few objectives could be optimized individually or simultaneously. This will give a choice to the scheduler in determining which objective is the most important.
机译:流程计划和生产计划在制造系统中起着重要作用。本文提出了一种模糊推理系统(FIS),该系统在选择备选机器进行车间加工制造系统的集成过程计划和调度时。将根据机器的可靠性特征选择机器。这将确保机器满足生产需求的能力。此外,基于功能信息,可以使用粒子群优化(PSO)平衡每台计算机的负载。仿真研究显示了在调度活动期间集成生产能力和负载平衡的一些有希望的结果。可以单独或同时优化的目标很少。这将使调度程序可以选择哪个目标最重要。

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