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Connectedness of Efficient Solutions in Multiple Objective Combinatorial Optimization

机译:多目标组合优化中有效解的连通性

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Connectedness of efficient solutions is a powerful property in multiple objective combinatorial optimization since it allows the construction of the complete efficient set using neighborhood search techniques. However, we show that many classical multiple objective combinatorial optimization problems do not possess the connectedness property in general, including, among others, knapsack problems (and even several special cases) and linear assignment problems. We also extend known non-connectedness results for several optimization problems on graphs like shortest path, spanning tree and minimum cost flow problems. Different concepts of connectedness are discussed in a formal setting, and numerical tests are performed for two variants of the knapsack problem to analyze the likelihood with which non-connected adjacency graphs occur in randomly generated instances.
机译:有效解决方案的连通性是多目标组合优化中的强大功能,因为它允许使用邻域搜索技术构建完整的有效集。但是,我们表明,许多经典的多目标组合优化问题通常不具备连通性,其中包括背包问题(甚至几种特殊情况)和线性分配问题。我们还针对图中最短路径,生成树和最小成本流问题之类的几个优化问题扩展了已知的非连接性结果。在正式的场合中讨论了不同的连通性概念,并对背包问题的两个变体进行了数值测试,以分析在随机生成的实例中非连通邻接图出现的可能性。

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