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A Combinatorial Branch and Bound for the Min-Max Regret Spanning Tree Problem

机译:一个组合分支并绑定了Min-Max后悔的跨越树问题

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摘要

Uncertainty in optimization can be modeled with the concept of scenarios, each of which corresponds to possible values for each parameter of the problem. The min-max regret criterion aims at obtaining a solution minimizing the maximum deviation, over all possible scenarios, from the optimal value of each scenario. Well-known problems, such as the shortest path problem and the minimum spanning tree, become NP-hard under a min-max regret criterion. This work reports the development of a branch and bound approach to solve the Minimum Spanning Tree problem under a min-max regret criterion in the discrete scenario case. The approach is tested in a wide range of test instances and compared with a generic pseudo-polynomial algorithm.
机译:优化中的不确定性可以用方案的概念建模,每个概念对应于问题的每个参数的可能值。 MIN-MAX遗憾标准旨在获得最小化所有可能场景的最大偏差的解决方案,从每个场景的最佳值中获得最大偏差。众所周知的问题,例如最短的路径问题和最小的生成树,在min-max后悔标准下变得很硬。这项工作报告了分支机构和绑定方法的开发,以解决离散场景案例中的MIN-MAX后悔标准下的最小生成树问题。该方法在广泛的测试实例中测试并与通用伪多项式算法进行比较。

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