Constraint handling in multiobjective evolutionary optimization
IEEE Transactions on Evolutionary Computation
Parameter control in differential evolution for constrained optimization
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Differential evolution in constrained numerical optimization: An empirical study
Information Sciences: an International Journal
Ensemble of constraint handling techniques
IEEE Transactions on Evolutionary Computation
A new self-adaption differential evolution algorithm based component model
ISICA'10 Proceedings of the 5th international conference on Advances in computation and intelligence
A three-strategy based differential evolution algorithm for constrained optimization
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I
Blended biogeography-based optimization for constrained optimization
Engineering Applications of Artificial Intelligence
Multi-operator based evolutionary algorithms for solving constrained optimization problems
Computers and Operations Research
On an evolutionary approach for constrained optimization problem solving
Applied Soft Computing
An improved (µ+λ)-constrained differential evolution for constrained optimization
Information Sciences: an International Journal
International Journal of Computing Science and Mathematics
Constraint Handling in Particle Swarm Optimization
International Journal of Swarm Intelligence Research
A Multiobjective Particle Swarm Optimizer for Constrained Optimization
International Journal of Swarm Intelligence Research
Self-adaptive differential evolution incorporating a heuristic mixing of operators
Computational Optimization and Applications
Particle swarm optimization for solving engineering problems: A new constraint-handling mechanism
Engineering Applications of Artificial Intelligence
A novel selection evolutionary strategy for constrained optimization
Information Sciences: an International Journal
A rough penalty genetic algorithm for constrained optimization
Information Sciences: an International Journal
International Journal of Bio-Inspired Computation
Differential evolution with multi-constraint consensus methods for constrained optimization
Journal of Global Optimization
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In this paper, an adaptive tradeoff model (ATM) is proposed for constrained evolutionary optimization. In this model, three main issues are considered: (1) the evaluation of infeasible solutions when the population contains only infeasible individuals; (2) balancing feasible and infeasible solutions when the population consists of a combination of feasible and infeasible individuals; and (3) the selection of feasible solutions when the population is composed of feasible individuals only. These issues are addressed in this paper by designing different tradeoff schemes during different stages of a search process to obtain an appropriate tradeoff between objective function and constraint violations. In addition, a simple evolutionary strategy (ES) is used as the search engine. By integrating ATM with ES, a generic constrained optimization evolutionary algorithm (ATMES) is derived. The new method is tested on 13 well-known benchmark test functions, and the empirical results suggest that it outperforms or performs similarly to other state-of-the-art techniques referred to in this paper in terms of the quality of the resulting solutions.