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Investigation of selection strategies in branch and bound algorithm with simplicial partitions and combination of Lipschitz bounds

机译:具有简单划分和Lipschitz界组合的分支定界算法的选择策略研究。

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摘要

Speed and memory requirements of branch and bound algorithms depend on the selection strategy of which candidate node to process next. The goal of this paper is to experimentally investigate this influence to the performance of sequential and parallel branch and bound algorithms. The experiments have been performed solving a number of multidimensional test problems for global optimization. Branch and bound algorithm using simplicial partitions and combination of Lipschitz bounds has been investigated. Similar results may be expected for other branch and boundalgorithms.
机译:分支定界算法的速度和内存要求取决于下一个要处理的候选节点的选择策略。本文的目的是通过实验研究这种影响对顺序和并行分支定界算法性能的影响。已经进行了实验,解决了用于全局优化的许多多维测试问题。研究了使用简单划分和Lipschitz边界组合的分支定界算法。对于其他分支和边界算法,可能会期望得到类似的结果。

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