Open Access

ARTICLE

Random Controlled Pool Base Differential Evolution Algorithm (RCPDE)

Qamar Abbas^a, Jamil Ahmad^b, Hajira Jabeen^a

^a Computer Department, Iqra University, Islamabad, Pakistan;
^b Computer Department, Abasyn University, Islamabad, Pakistan

* Corresponding Author: Qamar Abbas,

Intelligent Automation & Soft Computing 2018, 24(2), 377-390. https://doi.org/10.1080/10798587.2017.1295678

Abstract

This paper presents a novel random controlled pool base differential evolution algorithm (RCPDE) where powerful mutation strategy and control parameter pools have been used. The mutation strategy pool contains mutations strategies having diverse parameter values, whereas the control parameter pool contains varying nature pairs of control parameter values. It has also been observed that with the addition of rarely used control parameter values in these pools are highly beneficial to enhance the performance of the DE algorithm. The proposed mutation strategy and control parameter pools improve the solution quality and the convergence speed of DE algorithm. The simulation results of the proposed RCPDE algorithm shows significant performance as compared to other algorithms when tested over a set of multi-dimensional benchmark functions.

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Keywords

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