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Robust quadratic assignment problem with budgeted uncertain flows

机译:预算不确定流量的鲁棒二次分配问题

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We consider a generalization of the classical quadratic assignment problem, where material flows between facilities are uncertain, and belong to a budgeted uncertainty set. The objective is to find a robust solution under all possible scenarios in the given uncertainty set. We present an exact quadratic formulation as a robust counterpart and develop an equivalent mixed integer programming model for it. To solve the proposed model for large-scale instances, we also develop two different heuristics based on 2-Opt local search and tabu search algorithms. We discuss performance of these methods and the quality of robust solutions through extensive computational experiments. Highlights ? A robust approach for quadratic assignment problem (RQAP) with budgeted uncertainty. ? An exact and two heuristic methods to solve RQAP. ? Extensive experiments to show performance of methods and quality of solutions. ? RQAP can be solved significantly faster than minmax regret QAP. ? RQAP has adjustable conservativeness while minmax regret QAP has not.
机译:我们考虑经典的二次分配问题的一般化,其中设施之间的物料流动是不确定的,并且属于预算不确定性集合。目的是在给定的不确定性集中找到所有可能情况下的可靠解决方案。我们提出了一个精确的二次公式作为健壮的对等物,并为其开发了等效的混合整数规划模型。为了解决大型实例的建议模型,我们还基于2-Opt本地搜索和禁忌搜索算法开发了两种不同的启发式算法。我们将通过大量的计算实验来讨论这些方法的性能以及健壮解决方案的质量。强调 ?具有预算不确定性的二次分配问题(RQAP)的可靠方法。 ?求解RQAP的一种精确方法和两种启发式方法。 ?广泛的实验表明方法的性能和解决方案的质量。 ? RQAP的解决速度远快于minmax后悔的QAP。 ? RQAP具有可调整的保守性,而minmax遗憾的是QAP没有。

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