An innovative artificial immune optimisation algorithm for solving complex optimisation problems
by Alireza Askarzadeh
International Journal of Bio-Inspired Computation (IJBIC), Vol. 6, No. 6, 2014

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.

Online publication date: Sat, 24-Jan-2015

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