Particle swarm optimization-based algorithms for TSP and generalized TSP
Information Processing Letters
A hybrid discrete particle swarm optimization for the traveling salesman problem
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
A Cooperative approach to particle swarm optimization
IEEE Transactions on Evolutionary Computation
Improved intelligent water drops algorithm using adaptive schema
International Journal of Bio-Inspired Computation
A discrete shuffled frog optimization algorithm
Artificial Intelligence Review
Journal of Intelligent Manufacturing
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The discrete particle swarm optimization (DPSO) is a kind of particle swarm optimization (PSO) algorithm to find optimal solutions for discrete problems. This paper proposes an improved DPSO based on cooperative swarms, which partition the search space into lower dimensional subspaces. The $k$-means split scheme and regular split scheme are applied to split the solution vector into swarms. Then the swarms optimize the different components of the solution vector cooperatively. Some strategies are further used to improve the accuracy and convergence. Application of the proposed cooperative swarms based DPSO (CDPSO) on the traveling salesman problem (TSP) shows a significant improvement over conventional DPSOs.