Title: An optimisation algorithm based on the behaviour of locust swarms

Authors: Erik Cuevas; Adrián González; Daniel Zaldívar; Marco Pérez-Cisneros

Addresses: Departamento de Electrónica, Universidad de Guadalajara, CUCEI, Av. Revolución 1500, Guadalajara, Jal, México ' Departamento de Electrónica, Universidad de Guadalajara, CUCEI, Av. Revolución 1500, Guadalajara, Jal, México ' Departamento de Electrónica, Universidad de Guadalajara, CUCEI, Av. Revolución 1500, Guadalajara, Jal, México ' Departamento de Electrónica, Universidad de Guadalajara, CUCEI, Av. Revolución 1500, Guadalajara, Jal, México

Abstract: In this paper, a novel swarm algorithm called locust search (LS) is proposed for solving optimisation tasks. The LS algorithm is based on the simulation of the behaviour presented in swarms of locusts. In the proposed algorithm, individuals emulate a group of locusts which interact to each other based on the biological laws of the cooperative swarm. Experimental results demonstrate a high performance of the proposed method for searching a global optimum in comparison with other well-known evolutionary methods.

Keywords: swarm intelligence; global optimisation; bio-inspired computation; locust swarms; locust search.

DOI: 10.1504/IJBIC.2015.073178

International Journal of Bio-Inspired Computation, 2015 Vol.7 No.6, pp.402 - 407

Received: 13 Jan 2015
Accepted: 09 Apr 2015

Published online: 26 Nov 2015 *

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