Computational intelligence PC tools
Computational intelligence PC tools
System design by constraint adaptation and differential evolution
IEEE Transactions on Evolutionary Computation
Stochastic ranking for constrained evolutionary optimization
IEEE Transactions on Evolutionary Computation
The fully informed particle swarm: simpler, maybe better
IEEE Transactions on Evolutionary Computation
Information Sciences: an International Journal
Solving constrained optimization via a modified genetic particle swarm optimization
Proceedings of the 1st international conference on Forensic applications and techniques in telecommunications, information, and multimedia and workshop
Performance based unit loading optimization using particle swarm optimization approach
CIMMACS'06 Proceedings of the 5th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Self-adaptive velocity particle swarm optimization for solving constrained optimization problems
Journal of Global Optimization
Artificial Bee Colony (ABC) Optimization Algorithm for Solving Constrained Optimization Problems
IFSA '07 Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing
ICCSA '08 Proceedings of the international conference on Computational Science and Its Applications, Part II
IEA/AIE '09 Proceedings of the 22nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: Next-Generation Applied Intelligence
Properties of Quantum Particles in Multi-Swarms for Dynamic Optimization
Fundamenta Informaticae
Differential genetic particle swarm optimization for continuous function optimization
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
A modified Artificial Bee Colony (ABC) algorithm for constrained optimization problems
Applied Soft Computing
Enhanced artificial bee colony algorithm performance
ICCOMP'10 Proceedings of the 14th WSEAS international conference on Computers: part of the 14th WSEAS CSCC multiconference - Volume II
Modified cuckoo search algorithm for unconstrained optimization problems
ECC'11 Proceedings of the 5th European conference on European computing conference
A note on teaching-learning-based optimization algorithm
Information Sciences: an International Journal
Properties of Quantum Particles in Multi-Swarms for Dynamic Optimization
Fundamenta Informaticae
Comments on "A note on teaching-learning-based optimization algorithm"
Information Sciences: an International Journal
Modified onlooker phase in artificial bee colony algorithm
SEMCCO'12 Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing
Constrained optimisation and robust function optimisation with EIWO
International Journal of Bio-Inspired Computation
An upgraded artificial bee colony (ABC) algorithm for constrained optimization problems
Journal of Intelligent Manufacturing
International Journal of Metaheuristics
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We introduce the PESO (Particle Evolutionary Swarm Optimization) algorithm for solving single objective constrained optimization problems. PESO algorithm proposes two new perturbation operators: "c-perturbation" and "m-perturbation". The goal of these operators is to fight premature convergence and poor diversity issues observed in Particle Swarm Optimization (PSO) implementations. Constraint handling is based on simple feasibility rules. PESO is compared with respect to a highly competitive technique representative of the state-of-the-art in the area using a well-known benchmark for evolutionary constrained optimization. PESO matches most results and outperforms other PSO algorithms.