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- Title
An Improved Multi-State Particle Swarm Optimization for Discrete Combinatorial Optimization Problems.
- Authors
Ibrahim, Ismail; Ibrahim, Zuwairie; Ahmad, Hamzah; Yusof, Zulkifli Md.
- Abstract
Particle swarm optimization (PSO) has been successfully applied to solve various optimization problems. Recently, a state-based algorithm called multi-state particle swarm optimization (MSPSO) has been proposed to solve discrete combinatorial optimization problems. The algorithm operates based on a simplified mechanism of transition between two states. However, the MSPSO algorithm has to deal with the production of infeasible solutions and hence, additional step to convert the infeasible solution to feasible solution is required. In this paper, the MSPSO is improved by introducing a strategy that directly produces feasible solutions. The performance of the improved multi-state particle swarm optimization (IMSPSO) is empirically evaluated based on a set of travelling salesman problems (TSPs). The experimental results are statistically analyzed and show that the IMSPSO is promising and consistently outperformed the binary PSO algorithm.
- Subjects
PARTICLE swarm optimization; COMBINATORIAL optimization; TRAVELING sales personnel
- Publication
International Journal of Simulation: Systems, Science & Technology, 2015, Vol 16, Issue 6, p14.1
- ISSN
1473-8031
- Publication type
Article
- DOI
10.5013/IJSSST.a.16.06.14