批判性分析：基于Bat算法的若干领域研究与应用
Critical Analysis: Bat Algorithm based Investigation and Application on Several Domains
摘要：
近年来出现了几种群优化算法，如杨新社于2010年提出的蝙蝠算法（BA）。算法的思想来自蝙蝠的回声定位能力。目的：本研究的目的是为读者提供蝙蝠算法的全面研究，包括其局限性，该算法已被应用的领域，在不同领域的通用优化问题，以及所有的研究，评估其性能对其他元启发式算法。方法：从背景、特点、局限性等方面对Bat算法进行了深入的介绍，并展示了与BA算法相结合的算法（K-Medoids，Back-propagation神经网络，Harmony Search Algorithm，Differential Evaluation Strategies，Enhanced Particle Swarm Optimization，Cuckoo Search Algorithm）及其理论结果，以及已经对算法进行的修改（改进的蝙蝠算法（MBA），增强的蝙蝠算法（EBA），变异蝙蝠算法（BAM），无人战斗机-蝙蝠变异算法（UCAV-BAM），非线性优化）。调查结果：光的优点和缺点，这个算法通过所有的研究，处理该算法的领域和应用，它已经解决，希望它能帮助科学家了解和发展it. Originality/值：至于研究界的知识，有没有全面的调查研究进行了这个算法，涵盖了它的各个方面。关键词：群体智能;自然启发式算法;元启发式算法;优化算法;蝙蝠算法。
英文摘要：
In recent years several swarm optimization algorithms, such as Bat Algorithm (BA) have emerged, which was proposed by Xin-She Yang in 2010. The idea of the algorithm was taken from the echolocation ability of bats. Purpose: The purpose of this study is to provide the reader with a full study of the Bat Algorithm, including its limitations, the fields that the algorithm has been applied, versatile optimization problems in different domains, and all the studies that assess its performance against other meta-heuristic algorithms. Approach: Bat Algorithm is given in-depth in terms of backgrounds, characteristics, limitations, it has also displayed the algorithms that hybridized with BA (K-Medoids, Back-propagation neural network, Harmony Search Algorithm, Differential Evaluation Strategies, Enhanced Particle Swarm Optimization, and Cuckoo Search Algorithm) and their theoretical results, as well as to the modifications that have been performed of the algorithm (Modified Bat Algorithm (MBA), Enhanced Bat Algorithm (EBA), Bat Algorithm with Mutation (BAM), Uninhabited Combat Aerial Vehicle-Bat algorithm with Mutation (UCAV-BAM), Nonlinear Optimization)... Findings: Shed light on the advantages and disadvantages of this algorithm through all the researches that dealt with the algorithm in addition to the fields and applications it has addressed in the hope that it will help scientists understand and develop it. Originality/value: As far as the research community knowledge, there is no comprehensive survey study conducted on this algorithm coverıng all its aspects. Keywords: Swarm Intelligence; Nature-Inspired Algorithms; Metaheuristic Algorithms; Optimization Algorithms; Bat Algorithm.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
