International Journal of Advanced and Applied Sciences

Int. j. adv. appl. sci.

EISSN: 2313-3724

Print ISSN: 2313-626X

Volume 4, Issue 7  (July 2017), Pages:  50-58

Title:  OPSODE: Opposition based particle swarm optimization instilled with differential evolution

Author(s):  Qamar Abbas 1, *, Jamil Ahmad 2, Hajira Jabeen 1


1Computer Department, Iqra University, Islamabad,44000, Pakistan
2Computer Department, Abasyn University, Islamabad,44000, Pakistan

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Particle Swarm Optimization (PSO) is a very powerful global optimization technique. Differential Evolution (DE) is another fast and emerging algorithm of evolutionary computing. PSODE is hybrid of PSO and DE that incorporates diversity in the PSO algorithm. In this research a new opposition based version of PSODE (OPSODE) is proposed that incorporates some more diversity by employing the opposition based learning in the PSODE algorithm. Some standard benchmark functions are used to access the performance of the OPOSDE algorithm. The proposed version is then compared with the PSO, OPSO, and PSODE algorithm. The research result shows that the new version OPSODE has significance performance. 

© 2017 The Authors. Published by IASE.

This is an open access article under the CC BY-NC-ND license (

Keywords: Opposition, Particle swarm optimization, Differential evolution, Initialization

Article History: Received 21 October 2016, Received in revised form 17 April 2017, Accepted 18 May 2017

Digital Object Identifier:


Abbas Q, Ahmad J, and Jabeen H (2017). OPSODE: Opposition based particle swarm optimization instilled with differential evolution. International Journal of Advanced and Applied Sciences, 4(7): 50-58


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