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THE INTEGRATED CUTTING AND PACKING HETEROGENEOUS PRECAST BEAMS MULTIPERIOD PRODUCTION PLANNING PROBLEM

机译:综合切割和包装异质预制光束多体生产计划问题

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摘要

We introduce a novel variant of cutting production planning problems named Integrated Cutting and Packing Heterogeneous Precast Beams Multiperiod Production Planning (ICP-HPBMPP). We propose an integer linear programming model for the ICP-HPBMPP, as well as a lower bound for its optimal objective function value, which is empirically shown to be closer to the optimal solution value than the bound obtained from the linear relaxation of the model. We also propose a genetic algorithm approach for the ICP-HPBMPP as an alternative solution method. We discuss computational experiments and propose a parameterization for the genetic algorithm using D-optimal experimental design. We observe good performance of the exact approach when solving small-sized instances, although there are difficulties in finding optimal solutions for medium and large-sized problems, or even in finding feasible solutions for large instances. On the other hand, the genetic algorithm is shown to typically find good-quality solutions for large-sized instances within short computing times.
机译:我们介绍了一个名为综合切割和包装异质预制光束多体生产计划(ICP-HPBMPP)的新型切割生产计划问题。我们为ICP-HPBMPP提出了一个整数线性编程模型,以及其最佳目标函数值的下限,其经验显示比从模型的线性松弛所获得的绑定更接近最佳解决方案值。我们还提出了ICP-HPBMPP作为替代解决方法的遗传算法方法。我们讨论计算实验,并提出使用D-Optal实验设计的遗传算法参数化。我们在解决小型实例时遵守确切方法的良好表现,尽管在寻找用于中型和大型问题的最佳解决方案方面存在困难,甚至在寻找大型实例的可行解决方案方面存在困难。另一方面,遗传算法显示为在短期计算时间内为大型实例找到高质量的解决方案。

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