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A hybridisation of Improved Harmony Search and Bacterial Foraging for multi-robot motion planning

机译:改进的和谐搜索和细菌搜寻的混合,用于多机器人运动计划

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摘要

This paper provides a new approach to include the chemotactic behavior of Bacterial Foraging Algorithm (BFOA) in the existing Improved Harmony Search (IHS) algorithm. Extensive computer simulations with CEC-2005 benchmark functions reveal that the proposed algorithm outperforms the existing one with respect to accuracy in determining the optima. The proposed algorithm has successfully been implemented for multi-robot motion planning application. Performance has been studied using the proposed IHS-BFO algorithm and compared with existing IHS and Particle Swarm Optimization (PSO) algorithm.
机译:本文提供了一种新方法,可将细菌觅食算法(BFOA)的趋化行为包含在现有的改进和谐搜索(IHS)算法中。使用CEC-2005基准函数进行的大量计算机仿真表明,在确定最佳值的准确性方面,所提出的算法优于现有算法。该算法已经成功地应用于多机器人运动规划应用中。使用提出的IHS-BFO算法研究了性能,并与现有的IHS和粒子群优化(PSO)算法进行了比较。

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