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A new measure of solution quality for combinatorial task assignment problems

机译:组合任务分配问题的解决方案质量的新措施

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This paper details a new method for measuring the quality of solutions to combinatorial optimization problems in a task assignment and vehicle routing framework. The authors demonstrate that these task assignment problems exhibit an underlying stochastic structure. This structure allows for useful statistical analysis of the problem domain. We are able to numerically recognize problem domains characterized by non-Gaussian distributions and compute a mapping from this non-Gaussian distribution to a Gaussian one. This allows any fractile from the non-Gaussian distribution to be mapped to a Gaussian distribution. Gaussian statistical analysis tools are then used to rate solution quality.
机译:本文详述了一种测量任务分配和车辆路由框架中的组合优化问题的解决方案质量的新方法。作者表明,这些任务分配问题表现出潜在的随机结构。该结构允许对问题域的有用统计分析。我们能够在数值上识别以非高斯分布的特征的问题域,并计算从该非高斯分发到高斯人的映射。这允许从非高斯分布中映射到高斯分布的任何骨折。然后使用高斯统计分析工具来评估解决方案质量。

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