A modeling language for mathematical programming
Management Science
An Electromagnetism-like Mechanism for Global Optimization
Journal of Global Optimization
On the Convergence of a Population-Based Global Optimization Algorithm
Journal of Global Optimization
Constrained optimization via particle evolutionary swarm optimization algorithm (PESO)
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Differential evolution algorithms using hybrid mutation
Computational Optimization and Applications
A filled function method for constrained global optimization
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
Unified particle swarm optimization for solving constrained engineering optimization problems
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
Stochastic ranking for constrained evolutionary optimization
IEEE Transactions on Evolutionary Computation
An electromagnetism-like method for nonlinearly constrained global optimization
Computers & Mathematics with Applications
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This paper presents the use of a constraint-handling technique, known as feasibility and dominance rules, in a electromagnetism-like (ELM) mechanism for solving constrained global optimization problems. Since the original ELM algorithm is specifically designed for solving bound constrained problems, only the inequality and equality constraints violation together with the objective function value are used to select points and to progress towards feasibility and optimality. Numerical experiments are presented, including a comparison with other methods recently reported in the literature.