Title: An enhanced differential evolution algorithm for solving large scale optimisation problems on graphics hardware
Authors: Jing Wang
Addresses: School of Software and Communication Engineering, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, 330013, China
Abstract: This paper presents an enhanced differential evolution (DE) algorithm on graphics hardware. It has shown a good performance on solving large scale optimisation problems. In this algorithm, generalised opposition-based learning (GOBL) strategy and orientation neighbourhood search (ONS) are embedded into DE algorithm. These strategies are helpful to balance the global and local search ability of the algorithm, moreover, the GPU hardware can accelerate the convergence rate. Experimental results show that the enhanced algorithm on graphics hardware achieves good accuracy and high speedup.
Keywords: differential evolution; graphics hardware; opposition-based learning; OBL; orientation neighbourhood search; ONS; large scale optimisation.
International Journal of Computer Applications in Technology, 2013 Vol.46 No.3, pp.259 - 266
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 23 Mar 2013 *