Parameter selection of a Particle Swarm Optimisation dynamics by closed loop stability analysis
International Journal of Computing Science and Mathematics
Interpolated differential evolution for global optimisation problems
International Journal of Computing Science and Mathematics
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Diversity enhanced particle swarm optimization with neighborhood search
Information Sciences: an International Journal
An improved particle swarm optimisation for solving generalised travelling salesman problem
International Journal of Computing Science and Mathematics
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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.