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首页> 外文期刊>International journal of production economics >An empirical comparison of Tabu Search, Simulated Annealing, and Genetic Algorithms for facilities location problems
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An empirical comparison of Tabu Search, Simulated Annealing, and Genetic Algorithms for facilities location problems

机译：禁忌搜索，模拟退火和遗传算法对设施选址问题的经验比较

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摘要

Algorithms to solve Facility Location Problems (FLP) optimally suffer from combinatorial explosion and resources required to solve such problems repeatedly as required in practical applications become prohibitive. In these cases heuristic methods are the only viable alternative. We compare the relative performance of Tabu Search (TS), Simulated Annealing (SA) and Genetic Algorithms (GA) on various types of FLP under time-limited, solution-limited, and unrestricted conditions. The results indicate that TS shows very good performance in most cases. The performance of SA and GA are more partial to problem type and the criterion used. Thus, in general we may conclude that TS should be tried first to the extent that it always yields as good or better results and is easy to develop and implement.
机译：解决设施位置问题（FLP）的算法最容易遭受组合爆炸的影响，而实际应用中需要反复解决这些问题的资源变得令人望而却步。在这些情况下，启发式方法是唯一可行的选择。我们比较了禁忌搜索（TS），模拟退火（SA）和遗传算法（GA）在时间限制，解限制和无限制条件下在各种类型的FLP上的相对性能。结果表明，TS在大多数情况下显示出非常好的性能。 SA和GA的性能更多地取决于问题类型和所使用的标准。因此，总的来说，我们可以得出结论，应该首先尝试TS，直到它总是产生相同或更好的结果并且易于开发和实施。

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