An improved design optimisation algorithm based on swarm intelligence. (1st January 2014)

• Record Type: Journal Article
• Authors: Wu, Qinghua; Liu, Hanmin; Yan, Xuesong
• Is Part Of: International journal of computing science and mathematics. Volume 5:Number 1(2014)
• Page Start: 27
• Page End: 36
• Publication Date: 2014-01-01
• Subjects: design optimisation -- particle swarm optimisation -- PSO -- particle -- genetic algorithms; Mathematics -- Periodicals; Computer science -- Periodicals; Mathematics -- Data processing -- Periodicals; 510.285
• Languages: English
• ISSNs: 1752-5055

Abstract

In design optimisation field, there are many non-linear optimisation problems and the traditional algorithms cannot deal with these problems well. In this paper, we improve the standard particle swarm optimisation (PSO) and propose a new algorithm to solve the overcome of standard PSO algorithm like being trapped easily into a local optimum. The new algorithm keeps not only the fast convergence speed characteristic of PSO, but effectively improves the capability of global searching as well. Compared with standard PSO on the benchmark functions, the results show that the new algorithm is efficient. We also used the new algorithm to solve design optimisation problems and the experiment results show the new algorithm is effective for these problems.