参数化局部预算不确定性组合问题的多参数鲁棒解
Multiparametric robust solutions for combinatorial problems with parameterized locally budgeted uncertainty
摘要：
本文研究了具有参数化局部预算不确定性的组合问题。我们正在寻找一个解决方案集，使得对于任何参数向量，都存在一个鲁棒性接近最优的解决方案。该算法包括应用多参数算法，以获得一个接近最优的多参数解决方案相对于目标函数的组合问题，定义为找到一个强大的解决方案，参数固定。据我们所知，这是第一个提出来做这项任务的算法。最短路径和$p$ -中位数问题的计算经验
英文摘要：
In this paper we studied combinatorial problems with parameterized locally budgeted uncertainty. We are looking for a solutions set such that for any parameters vector there exists a solution in the set with robustness near optimal. The algorithm consists of applying a multiparametric algorithm to obtain a near optimal multiparametric solution relative to the objective function for a combinatorial problem defined to find a robust solution for parameters fixed. As far as we know this is the first algorithm presented to do that task. Computational experience is presented to shortest path and $p$-medians problems
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