A New Dynamic Particle Swarm Optimizer
This paper presents a new optimization model— Dynamic Particle Swarm Optimizer (DPSO). A new acceptance rule that based on the principle of minimal free energy from the statistical mechanics is introduced to the standard particle swarm optimizer. A definition of the entropy of the particle system is given. Then the law of entropy increment is applied to control the algorithm. Simulations have been done to illustrate the significant and effective impact of this new rule on the particle swarm optimizer.
KeywordsParticle Swarm Optimization Particle Swarm Local Extremum Minimal Free Energy Standard Particle Swarm Optimizer
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- 1.Kennedy, J., Eberhart, R.C.: Particle Swarm Optimization. In: IEEE International Conference on Neural Networks, pp. 1942–1948 (1995)Google Scholar
- 3.Van den Bergh, F.: An Analysis of Particle Swam Optimizers. PhD thesis, University of Pretoria (2000)Google Scholar
- 5.Hu, T., Li, Y., Ding, W.: A new dynamical evolutionary algorithm based on the principle of minimal free energy. In: Kang, L. (ed.) International Symposium on Intelligent Computation and its Application, ISICA 2005, Wuhan, China, pp. 749–754 (2005)Google Scholar