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Bat algorithm (BA): review, applications and modifications

机译：BAT算法（BA）：审查，应用程序和修改

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Generally, Metaheuristic algorithms such as ant colony optimization, Elephant herding algorithm, particle swarm optimization, bat algorithms becomes a powerful methods for solving optimization problems. This paper provides a timely review of the bat algorithm and its new variants. Bat algorithm (BA) is a Swarm based metaheuristic algorithm developed in 2010 by Xin-She Yang, BA has been inspired by the foraging behavior of micro bats, algorithm carries out the search process using arti?cial bats as search agents mimicking the natural pulse loudness and emission rate of real bats. It has become a powerful swarm intelligence method for solving optimization prob-lems over continuous and discrete spaces. Nowadays, it has been successfully applied to solve problems in almost all areas of opti-mization, and it found to be very efficient. As a result, the literature has expanded significantly, a wide range of diverse applications and case studies has been made base on the bat algorithm.
机译：通常，诸如蚁群优化，大象放牧算法，粒子群优化，BAT算法的抗殖民地算法成为一种解决优化问题的强大方法。本文提供了对BAT算法及其新变种的及时审查。 BAT算法（BA）是一种基于群体的成群质算法2010年，由新佘阳开发，BA已经受到微蝙蝠的觅食行为的启发，算法使用ARTI？CIAL BATS作为模仿自然脉冲的搜索器真正的蝙蝠的响度和排放率。它已成为一种强大的群体智能方法，用于解决连续和离散空间的优化概率。如今，已经成功地应用于解决几乎所有优化领域的问题，并且发现它非常有效。结果，文献已经显着扩展，在BAT算法上基于各种不同的应用和案例研究。

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