仿生萤火虫算法:一种系统的调查-群体智能算法

C. Kalpana, B. Booba
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引用次数: 0

摘要

在群体智能领域,萤火虫算法是应用于大多数优化领域的最重要的算法。FA和变体很容易理解和实现。FA能够解决不同领域的问题。为了解决各种工程问题,需要改进FA或混合FA算法,但可能有额外的改进范围。近年来,基于群体智能的智能优化算法已被用于研究目的。遗传算法是一种重要的智能群算法,可以应用于全局优化问题。遗传算法能够在复杂问题中获得最佳结果。本文讨论了脂肪酸的不同特性,并对脂肪酸的研究进展作了简要的综述。与其他元元算法一起讨论了多目标算法、混合算法等算法的不同变体。给出了萤火虫算法的应用。本文的目的是为未来FA的研究指明方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bio-Inspired Firefly Algorithm A Methodical Survey – Swarm Intelligence Algorithm
In the Swarm Intelligence domain, the firefly algorithm(s) is the most significant algorithm applied in most all optimization areas. FA and variants are easily understood and implemented. FA is capable of solving different domain problems. For solving diverse range of engineering problems requires modified FA or Hybrid FA algorithms, but it is possible additional scope of improvement. In recent times swarm intelligence based intelligent optimization algorithms have been used for Research purposes. FA is one of most important intelligence Swarm algorithm that can be applied for the problems of Global optimization. FA algorithm is capable of achieving best results for complicated issues. In this research study we have discussed and different characteristics of FA and presented brief Review of FA. Along with other metahauristic algorithm we have discussed FA algorithm’s different variant like multi objective, and hybrid. The applications of firefly algorithm are bestowed. The aim of the paper is to give future direction for research in FA.
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