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Chaos-Enhanced Firefly Algorithm with Automatic Parameter Tuning

机译:具有自动参数调整功能的混沌增强萤火虫算法

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摘要

Many metaheuristic algorithms are nature-inspired, and most are population-based. Particle swarm optimization is a good example as an efficient metaheuristic algorithm. Inspired by PSO, many new algorithms have been developed in recent years. For example, firefly algorithm was inspired by the flashing behaviour of fireflies. In this paper, the author extends the standard firefly algorithm further to introduce chaos-enhanced firefly algorithm with automatic parameter tuning, which results in two more variants of FA. The author first compares the performance of these algorithms, and then uses them to solve a benchmark design problem in engineering. Results obtained by other methods will be compared and analyzed.
机译:许多元启发式算法是自然启发的,并且大多数是基于人群的。粒子群优化是一种有效的元启发式算法的很好的例子。受PSO启发,近年来开发了许多新算法。例如,萤火虫算法受萤火虫闪烁行为的启发。在本文中,作者进一步扩展了标准萤火虫算法,以引入具有自动参数调整功能的混沌增强萤火虫算法,这导致了FA的两个变体。作者首先比较了这些算法的性能,然后使用它们来解决工程中的基准设计问题。通过其他方法获得的结果将进行比较和分析。

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