p-鲁棒随机设施定位问题的研究

Fan Ke-wei
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引用次数: 1

摘要

Snyder和Daskin在两个经典的设施选址模型PMP (P-median problem)和UFLP (uncapacitated facility location problem)的基础上提出了p-鲁棒模型。我们可以施加一个约束,规定在任何情况下的相对后悔必须不大于p,其中p>0是一个外部参数。换句话说,每个场景下的成本必须在该场景的最优成本的100(1+p)%之内。对于较小的p,对于给定的问题可能没有p鲁棒解。因此,p-稳健性增加了大多数其他稳健性措施中不存在的可行性问题。本文利用p-SPMP (p-鲁棒随机p中值问题)、p-SUFLP (p-鲁棒随机无容量设施选址问题)、p-SCPMP (p-鲁棒随机无容量设施选址问题)、p-SCFLP (p-鲁棒随机有容量设施选址问题)、p-SCPMPX (p-鲁棒随机有容量设施选址问题,x是连续的)和p-SCFLPX (p-鲁棒随机有容量设施选址问题),X为连续)来分析随机设施选址问题
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on p-Robust Stochastic Facility Location Problem
Snyder and Daskin presented p-robust models based on two classical facility location models, the PMP (P-median problem) and UFLP (uncapacitated facility location problem). We can impose a constraint dictating that the relative regret in any scenario must be no greater than p, where p>0 is an external parameter. In other words, the cost under each scenario must be within 100(1+p)% of the optimal cost for that scenario. For small p, there may be no p-robust solutions for a given problem. Thus, p-robustness adds a feasibility issue not present in most other robustness measures. In this paper, we use the following p-SPMP (p-robust stochastic P-median problem), p-SUFLP (p-robust stochastic uncapacitated facility location problem), p-SCPMP (p-robust stochastic capacitated P-median problem), p-SCFLP (p-robust stochastic capacitated facility location problem), p-SCPMPX (p-robust stochastic capacitated P-median problem, x is continuous) and p-SCFLPX (p-robust stochastic capacitated facility location problem, x is continuous) to analysis the stochastic facility location problems
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