An enhanced differential evolution algorithm for solving large scale optimisation problems on graphics hardware

  • Authors:
  • Jing Wang

  • Affiliations:
  • School of Software and Communication Engineering, Jiangxi University of Finance and Economics, Nanchang, Jiangxi, 330013, China

  • Venue:
  • International Journal of Computer Applications in Technology
  • Year:
  • 2013

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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.