A shrinking hypersphere PSO for engineering optimisation problems. Issue 1 (3rd March 2016)

• Record Type: Journal Article
• Authors: Yadav, Anupam; Deep, Kusum
• Is Part Of: Journal of experimental & theoretical artificial intelligence. Volume 28:Issue 1/2(2016)
• Page Start: 1
• Page End: 33
• Publication Date: 2016-03-03
• Subjects: particle swarm optimisation -- hypersphere -- constrained optimisation -- engineering design; Artificial intelligence -- Periodicals; 006.3
• DOI: 10.1080/0952813X.2014.924589
• Languages: English
• ISSNs: 0952-813X

Abstract

Abstract : Many real-world and engineering design problems can be formulated as constrained optimisation problems (COPs). Swarm intelligence techniques are a good approach to solve COPs. In this paper an efficient shrinking hypersphere-based particle swarm optimisation (SHPSO) algorithm is proposed for constrained optimisation. The proposed SHPSO is designed in such a way that the movement of the particle is set to move under the influence of shrinking hyperspheres. A parameter-free approach is used to handle the constraints. The performance of the SHPSO is compared against the state-of-the-art algorithms for a set of 24 benchmark problems. An exhaustive comparison of the results is provided statistically as well as graphically. Moreover three engineering design problems namely welded beam design, compressed string design and pressure vessel design problems are solved using SHPSO and the results are compared with the state-of-the-art algorithms.