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The robust (minmax regret) single machine scheduling with interval processing times and total weighted completion time objective

机译:具有间隔处理时间和总加权完成时间目标的强大的(最小后悔)单机调度

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Single machine scheduling is a classical optimization problem that depicts multiple real life systems in which a single resource (the machine) represents the whole system or the bottleneck operation of the system. In this paper we consider the problem under a weighted completion time performance metric in which the processing time of the tasks to perform (the jobs) are uncertain, but can only take values from closed intervals. The objective is then to find a solution that minimizes the maximum absolute regret for any possible realization of the processing times. We present an exact branch-and-bound method to solve the problem, and conduct a computational experiment to ascertain the possibilities and limitations of the proposed method. The results show that the algorithm is able to optimally solve instances of moderate size (25-40 jobs depending on the characteristics of the instance). (c) 2015 Elsevier Ltd. All rights reserved.
机译:单机调度是一个经典的优化问题,它描述了多个现实生活中的系统,其中单个资源(机器)代表整个系统或系统的瓶颈操作。在本文中,我们考虑了加权完成时间性能指标下的问题,在该指标中,要执行的任务(作业)的处理时间不确定,但只能从封闭间隔中获取值。然后,目的是找到一种解决方案,以最大程度地减少处理时间的任何可能的最大绝对遗憾。我们提出一种精确的分支定界方法来解决该问题,并进行计算实验以确定该方法的可能性和局限性。结果表明,该算法能够最优地求解中等大小的实例(根据实例的特征,需要执行25至40个工作)。 (c)2015 Elsevier Ltd.保留所有权利。

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