Bat algorithm
Encyclopedia
Bat-inspired algorithm is a metaheuristic
Metaheuristic
In computer science, metaheuristic designates a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. Metaheuristics make few or no assumptions about the problem being optimized and can search very large spaces...

 search optimization
Optimization
Optimization or optimality may refer to:* Mathematical optimization, the theory and computation of extrema or stationary points of functionsEconomics and business* Optimality, in economics; see utility and economic efficiency...

 developed by Xin-She Yang in 2010. This bat algorithm is based on the echolocation behaviour of microbats with varying pulse rates of emission and loudness.

Algorithm Description

The idealization of echolocation
Echolocation
Echolocation may refer to:* Acoustic location, the general use of sound to locate objects* Animal echolocation, non-human animals emitting sound waves and listening to the echo in order to locate objects or navigate...

 can be summarized as follows: Each virtual bat flies randomly with a velocity at position (solution) with a varying frequency or wavelength and loudness . As it searches and finds
its prey, it changes frequency, loudness and pulse emission rate . Search is intensified by a local random walk
Random walk
A random walk, sometimes denoted RW, is a mathematical formalisation of a trajectory that consists of taking successive random steps. For example, the path traced by a molecule as it travels in a liquid or a gas, the search path of a foraging animal, the price of a fluctuating stock and the...

. Selection of the best continues until certain stop criteria are met.

A detailed introduction of metaheuristic algorithms including the bat algorithm is given by Yang where a demo program in Matlab/Octave is available, while a comprehensive review is carried out by Parpinelli and Lopes.

Multi-objective Bat Algorithm (MOBA)

Using a simple weighted sum with random weights, a very effective but yet simple multiobjective bat algorithm (MOBA) has been developed to solve multiobjective engineering design tasks.

Applications

A fuzzy bat clustering method has been developed to solve ergonomic workplace problems
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