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Multi-swarm Optimization Algorithm Based on Firefly and Particle Swarm Optimization Techniques

机译:基于萤火虫和粒子群算法的多群优化算法

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In this paper, the two hybrid swarm-based metaheuristic algorithms are tested and compared. The first hybrid is already existing Firefly Particle Swarm Optimization (FFPSO), which is based, as the name suggests, on Firefly Algorithm (FA) and Particle Swarm Optimization (PSO). The secondly proposed hybrid is an algorithm using the multi-swarm method to merge FA and PSO. The performance of our developed algorithm is tested and compared with the FFPSO and canonical FA. Comparisons have been conducted on five selected benchmark functions, and the results have been evaluated for statistical significance using Friedman rank test.
机译:本文对两种基于混合群的元启发式算法进行了测试和比较。第一个混合动力是已经存在的Firefly粒子群优化算法(FFPSO),顾名思义,它基于Firefly算法(FA)和粒子群优化(PSO)。第二种提出的混合算法是使用多群方法将FA和PSO合并的算法。我们开发的算法的性能经过测试,并与FFPSO和规范FA进行了比较。已对五个选定的基准函数进行了比较,并使用弗里德曼等级检验对结果进行了统计显着性评估。

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