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Improved Tabu search heuristics for the dynamic space allocation problem

机译:改进的禁忌搜索启发式算法,用于动态空间分配问题

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The dynamic space allocation problem (DSAP) presented in this paper considers the task of assigning items (resources) to locations during a multi-period planning horizon such that the cost of rearranging the items is minimized. Three tabu search heuristics are presented for this problem. The first heuristic is a simple basic tabu search heuristic. The second heuristic adds diversification and intensification strategies to the first, and the third heuristic is a probabilistic tabu search heuristic. To test the performances of the heuristics, a set of test problems from the literature is used in the analysis. The results show that the tabu search heuristics are efficient techniques for solving the DSAP. More importantly, the proposed tabu search heuristic with diversification/intensification strategies found new best solutions using less computation time for one-half of all the test problems.
机译:本文提出的动态空间分配问题(DSAP)考虑了在多期间计划期间将项目(资源)分配到位置的任务,以使重新安排项目的成本最小化。针对此问题,提出了三种禁忌搜索试探法。第一种启发式方法是简单的基本禁忌搜索启发式方法。第二种启发式方法在第一种启发式方法的基础上增加了多元化和集约化策略,而第三种启发式方法则是一种概率性禁忌搜索启发式方法。为了测试启发式方法的性能,分析中使用了一系列来自文献的测试问题。结果表明,禁忌搜索启发式算法是解决DSAP的有效技术。更重要的是,所提出的具有多样化/强化策略的禁忌搜索试探法找到了针对所有测试问题一半的计算时间更少的新最佳解决方案。

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