Title: An innovative artificial immune optimisation algorithm for solving complex optimisation problems

Authors: Alireza Askarzadeh

Addresses: Department of Energy Management and Optimisation, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, Iran

Abstract: The main contribution of this paper is to develop an innovative artificial immune optimisation algorithm, called AIO, for solving complex optimisation problems. The proposed population-based algorithm has the ability of escaping from local optima and approaching to the optimum solution by providing a good balance between exploration and exploitation. In order to evaluate the optimisation power of the proposed algorithm, AIO is applied to solve five well-known benchmark functions that are extremely used for testing optimisation algorithms. The acquired results indicate that the proposed algorithm not only finds optimal or close-to-optimal solutions but also gives both better and more robust results in comparison with the other studied algorithms.

Keywords: local optima; population-based algorithm; artificial immune optimisation.

DOI: 10.1504/IJBIC.2014.066972

International Journal of Bio-Inspired Computation, 2014 Vol.6 No.6, pp.409 - 415

Received: 18 Sep 2013
Accepted: 08 Oct 2014
Published online: 24 Jan 2015 *

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