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Solving Flexible Job-Shop Scheduling Problem Using Gravitational Search Algorithm and Colored Petri Net

机译:利用引力搜索算法和彩色Petri网解决柔性车间作业调度问题

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Scheduled production system leads to avoiding stock accumulations, losses reduction, decreasing or even eliminating idol machines, and effort to better benefitting from machines for on time responding customer orders and supplying requested materials in suitable time. In flexible job-shop scheduling production systems, we could reduce time and costs by transferring and delivering operations on existing machines, that is, among NP-hard problems. The scheduling objective minimizes the maximal completion time of all the operations, which is denoted by Makespan. Different methods and algorithms have been presented for solving this problem. Having a reasonable scheduled production system has significant influence on improving effectiveness and attaining to organization goals. In this paper, new algorithm were proposed for flexible job-shop scheduling problem systems (FJSSP-GSPN) that is based on gravitational search algorithm (GSA). In the proposed method, the flexible job-shop scheduling problem systems was modeled by color Petri net and CPN tool and then a scheduled job was programmed by GSA algorithm. The experimental results showed that the proposed method has reasonable performance in comparison with other algorithms.
机译:预定的生产系统可以避免库存累积,减少损失,减少甚至消除偶像机器,并努力更好地从机器中受益,以便及时响应客户订单并在适当的时间提供所需的材料。在灵活的车间调度生产系统中,我们可以通过转移和交付现有机器上的操作(即NP难题)来减少时间和成本。调度目标使所有操作的最大完成时间最小化,这由Makespan表示。已经提出了解决该问题的不同方法和算法。拥有合理的计划生产系统对提高效率和实现组织目标具有重大影响。本文提出了一种基于引力搜索算法(GSA)的柔性作业车间调度问题系统(FJSSP-GSPN)的新算法。该方法利用彩色Petri网和CPN工具对柔性作业车间调度问题系统进行建模,然后利用GSA算法对作业进行调度。实验结果表明,与其他算法相比,该方法具有合理的性能。

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