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首页> 外文期刊>European Journal of Operational Research >Optimal allocation and processing time decisions on non-identical parallel CNC machines: epsilon-constraint approach
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Optimal allocation and processing time decisions on non-identical parallel CNC machines: epsilon-constraint approach

机译:不同的并行CNC机器上的最佳分配和处理时间决策:ε约束方法

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摘要

When the processing times of jobs are controllable, selected processing times affect both the manufacturing cost and the scheduling performance. A well known example for such a case that this paper specifically deals with is the turning operation on a CNC machine. Manufacturing cost of a turning operation is a nonlinear convex function of its processing time. In this paper, we deal with making optimal machine-job assignments and processing time decisions so as to minimize total manufacturing cost while the makespan being upper bounded by a known value, denoted as E-constraint approach for a bicriteria problem. We then give optimality properties for the resulting single criterion problem. We provide alternative methods to compute cost lower bounds for partial schedules, which are used in developing an exact (branch and bound) algorithm. For the cases where the exact algorithm is not efficient in terms of computation time, we present a recovering beam search algorithm equipped with an improvement search procedure. In order to find improving search directions, the improvement search algorithm uses the proposed cost bounding properties. Computational results show that our lower bounding methods in branch and bound algorithm achieve a significant reduction in the search tree size that we need to traverse. Also, our recovering beam search and improvement search heuristics achieve solutions within 1% of the optimum on the average while they spent much less computational effort than the exact algorithm. (c) 2006 Elsevier B.V. All rights reserved.
机译:当作业的处理时间是可控制的时,选择的处理时间会影响制造成本和调度性能。本文专门处理的这种情况的一个众所周知的例子是在CNC机床上进行车削操作。车削工序的制造成本是其加工时间的非线性凸函数。在本文中,我们处理最佳的机器作业分配和处理时间决策,以使总制造成本最小化,同时使制造期上限受已知值的限制,这被称为双标准问题的E约束方法。然后,我们为所得的单准则问题提供最优性。我们提供了替代方法来计算部分计划的成本下限,这些方法用于开发精确的(分支定界)算法。对于精确算法在计算时间上效率不高的情况,我们提出了一种配备改进搜索程序的恢复束搜索算法。为了找到改进的搜索方向,改进搜索算法使用了建议的成本限制属性。计算结果表明,在分支定界算法中,我们的下界方法大大减少了我们需要遍历的搜索树大小。同样,我们的恢复波束搜索和改进搜索启发式算法可平均获得最佳解决方案的1%以内的解决方案,同时它们比精确算法花费的计算量要少得多。 (c)2006 Elsevier B.V.保留所有权利。

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