Constraint handling in multiobjective evolutionary optimization
IEEE Transactions on Evolutionary Computation
Dynamic multiple swarms in multiobjective particle swarm optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
An adaptive penalty formulation for constrained evolutionary optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Barebones particle swarm for multi-objective optimisation problems
International Journal of Innovative Computing and Applications
Vaccine-enhanced artificial immune system for multimodal function optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Hierarchical cluster-based multispecies particle-swarm optimization for fuzzy-system optimization
IEEE Transactions on Fuzzy Systems
Particle swarm optimisation aided minimum bit error rate multiuser transmission
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Clustering methods for agent distribution optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Particle swarm optimization aided orthogonal forward regression for unified data modeling
IEEE Transactions on Evolutionary Computation
Particle swarm optimization for determining fuzzy measures from data
Information Sciences: an International Journal
A new multi-swarm multi-objective particle swarm optimization based on pareto front set
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Expert Systems with Applications: An International Journal
Adaptive population tuning scheme for differential evolution
Information Sciences: an International Journal
Modified particle swarm optimization structure approach to direction of arrival estimation
Applied Soft Computing
A Multiobjective Particle Swarm Optimizer for Constrained Optimization
International Journal of Swarm Intelligence Research
A new multi-swarm multi-objective optimization method for structural design
Advances in Engineering Software
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Recently, various multiobjective particle swarm optimization (MOPSO) algorithms have been developed to efficiently and effectively solve multiobjective optimization problems. How ever, the existing MOPSO designs generally adopt a notion to "estimate" a fixed population size sufficiently to explore the search space without incurring excessive computational complexity. To address the issue, this paper proposes the integration of a dynamic population strategy within the multiple-swarm MOPSO. The proposed algorithm is named dynamic population multiple-swarm MOPSO. An additional feature, adaptive local archives, is designed to improve the diversity within each swarm. Performance metrics and benchmark test functions are used to examine the performance of the proposed algorithm compared with that of five selected MOPSOs and two selected multiobjective evolutionary algorithms. In addition, the computational cost of the proposed algorithm is quantified and compared with that of the selected MOPSOs. The proposed algorithm shows competitive results with improved diversity and convergence and demands less computational cost.