Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
Hybridization of PSO and a Discrete Position Update Scheme Techniques for Manufacturing Cell Design
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Collaborative particle swarm optimization with a data mining technique for manufacturing cell design
Expert Systems with Applications: An International Journal
Binary particle swarm optimization for black-scholes option pricing
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
Optimization of modular structures using Particle Swarm Optimization
Expert Systems with Applications: An International Journal
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Particle swarm optimization (PSO), inspired by social psychology principles and evolutionary computations, has been successfully applied to a wide range of continuous optimization problems. However, research on discrete problems has been done not much even though discrete binary version of PSO (BPSO) was introduced by Kennedy and Eberhart in 1997. In this paper, we propose a modified BPSO algorithm, which escapes from a local optimum by employing a bit change mutation. The proposed algorithm was tested on De jong's suite and its results show that BPSO with the proposed mutation outperforms the original BPSO.