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Local Search Heuristics for the One Dimensional Bin Packing Problems

机译:一维装箱问题的本地搜索启发式

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This resaerch implements three basic local search heuristics; hill climbing (i.e., random descent), simulated annealing and multi-start simulated annealing. The aim is to investigate the performance of these heuristics compared to the state of art literatures. To achieve this, researchers use a common software interface (the HyFlex framework) that are designed to enable the development, testing and comparison of iterative general-purpose heuristic search algorithms. To evaluate the performance of these heuristics researchers test on one dimensional bin packing instances using simple move operator. The results demonstrated that hill climbing heuristic outperforms other approaches in all tested instances. This indicates that simple local search is more effective in solving one dimensional bin packing problems when the searcher is allowed to run in a short time.
机译:此搜索实施三种基本的本地搜索试探法;爬坡(即随机下降),模拟退火和多起点模拟退火。目的是研究与现有文献相比这些启发式方法的性能。为了实现这一目标,研究人员使用了一个通用软件界面(HyFlex框架),该界面旨在实现迭代通用启发式搜索算法的开发,测试和比较。为了评估这些启发式方法的性能,研究人员使用简单的move运算符在一维装箱实例上进行了测试。结果表明,在所有测试实例中,爬山试探法均优于其他方法。这表明,当允许搜索器在短时间内运行时,简单的本地搜索在解决一维装箱问题方面会更有效。

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