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On the Adequacy of Tabu Search for Global Robot Path Planning Problem in Grid Environments

机译:禁忌搜索在网格环境中全局机器人路径规划问题的充分性

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This paper investigates the capabilities of tabu search for solving the global path planning problem in grid maps. Accordingly, a tabu search system model is designed and a tabu search planner algorithm for solving the path planning problem is proposed. A comprehensive simulation study is conducted using the proposed model and algorithm, in terms of solution quality and execution time. A comparison between our results with those of A* and genetic algorithms (GA) is presented for small, medium and large-scale grid maps. Simulation results show that the tabu search planner is able to find the optimal solution for small scale environments. However, for large scale maps, it provides near-optimal solutions with small gap while ensuring shorter execution times as compared to the A* Algorithm. A discussion about the advantages and limitations of TS for solving a path planning problem is also presented.
机译:本文研究禁忌搜索解决网格地图全局路径规划问题的能力。据此,设计了禁忌搜索系统模型,提出了一种用于解决路径规划问题的禁忌搜索计划器算法。在解决方案质量和执行时间方面,使用提出的模型和算法进行了全面的仿真研究。针对小型,中型和大型网格图,将我们的结果与A *和遗传算法(GA)的结果进行了比较。仿真结果表明,禁忌搜索计划器能够为小规模环境找到最佳解决方案。但是,对于大型地图,与A *算法相比,它提供了较小间隙的近乎最优的解决方案,同时确保了较短的执行时间。还讨论了TS在解决路径规划问题方面的优势和局限性。

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