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Resource-constrained unrelated parallel machine scheduling problem with sequence dependent setup times, precedence constraints and machine eligibility restrictions

机译:资源受限的无关并行机器调度问题,其依赖序列的设置时间,优先级限制和机器资格限制

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摘要

This study addresses an unrelated parallel machine scheduling problem with resource constrains, sequence-dependent setup times, different release dates, machine eligibility and precedence constraints. This problem has been inspired from the block erection scheduling problem in a shipyard. Majority of the traditional scheduling problems in parallel machine environment deal with machine as the only resource. However, other resources such as labors, tools, jigs, fixtures, pallets, dies and industrial robots are not only required for processing jobs but also are often restricted. To formulate this complicated problem, a new pure integer mathematical modeling is proposed and makespan is employed as the objective function. Since the problem is strongly NP-hard, exact approaches are intractable for large size problems. Thus, two new meta-heuristic algorithms including genetic algorithm (GA) and artificial immune system (AIS) are developed to find optimal or near optimal solutions. In addition, the parameters of these algorithms are calibrated by using Taguchi method. The performances of the proposed meta-heuristics are evaluated by a number of numerical examples. The computational results demonstrated that in small scale problems both algorithms are effective and efficient, but in large scale problems the suggested AIS statistically outperformed the proposed GA.
机译:这项研究解决了一个不相关的并行机器调度问题,该问题具有资源约束,与序列有关的设置时间,不同的发布日期,机器资格和优先级约束。这个问题是由造船厂的区块安装计划问题引起的。并行机器环境中的大多数传统调度问题都将机器视为唯一资源。但是,其他资源(例如人工,工具,夹具,固定装置,托盘,模具和工业机器人)不仅需要处理工作,而且经常受到限制。为了解决这个复杂的问题,提出了一种新的纯整数数学建模方法,并将makepan作为目标函数。由于该问题对NP来说非常困难,因此对于大尺寸问题很难采用精确的方法。因此,开发了两种新的元启发式算法,包括遗传算法(GA)和人工免疫系统(AIS),以找到最优或接近最优的解决方案。另外,这些算法的参数是通过Taguchi方法校准的。所提出的元启发式方法的性能通过许多数值示例进行了评估。计算结果表明,在小规模问题中,两种算法都是有效且高效的,但在大规模问题中,建议的AIS在统计上优于拟议的遗传算法。

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