Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Swarm intelligence
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
A review of particle swarm optimization. Part I: background and development
Natural Computing: an international journal
A hybrid genetic algorithm and particle swarm optimization for multimodal functions
Applied Soft Computing
Introducing dynamic diversity into a discrete particle swarm optimization
Computers and Operations Research
Comparison among five evolutionary-based optimization algorithms
Advanced Engineering Informatics
An Improved Self-Adaptive Particle Swarm Optimization Algorithm with Simulated Annealing
IITA '09 Proceedings of the 2009 Third International Symposium on Intelligent Information Technology Application - Volume 03
Computers and Operations Research
Simulated annealing algorithm with adaptive neighborhood
Applied Soft Computing
Cellular particle swarm optimization
Information Sciences: an International Journal
Enhancing particle swarm optimization using generalized opposition-based learning
Information Sciences: an International Journal
Self-adaptive learning based particle swarm optimization
Information Sciences: an International Journal
Example-based learning particle swarm optimization for continuous optimization
Information Sciences: an International Journal
Evolutionary programming made faster
IEEE Transactions on Evolutionary Computation
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
The fully informed particle swarm: simpler, maybe better
IEEE Transactions on Evolutionary Computation
A Cooperative approach to particle swarm optimization
IEEE Transactions on Evolutionary Computation
Comprehensive learning particle swarm optimizer for global optimization of multimodal functions
IEEE Transactions on Evolutionary Computation
Particle Swarm Optimization With Recombination and Dynamic Linkage Discovery
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Over the last two decades, the newly developed optimization technique - Particle Swarm Optimization (PSO) has attracted great attention. Two common criticisms exist. First, most existing PSOs are designed for a specific search space thus an algorithm performing well on a diverse set of problems is lacking. Secondly, PSO suffers premature convergence. To address the first issue, we propose to augment PSO via the fusion of multiple search methods. An intelligent selection mechanism is developed based on an effectiveness index to trigger appropriate search methods. In this research, two search techniques are studied: a non-uniform mutation-based method and an adaptive sub-gradient method. We further improve the proposed PSO using adaptive Cauchy mutation to prevent premature convergence. As a result, an augmented PSO with multiple adaptive methods (PSO-MAM) is proposed. The performance of PSO-MAM is tested on 43 functions (uni-modal, multi-modal, non-separable, shifted, rotated, noisy and mis-scaled functions). The results are compared in terms of solution quality and convergence speed with 10 published PSO methods. The experimental results demonstrate PSO-MAM outperforms the comparison algorithms on 36 out of 43 functions. We conclude, while promising, there is still room for improving PSO-MAM on complex multi-modal functions (e.g., rotated multi-modal functions).