An adaptive penalty formulation for constrained evolutionary optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Markovian search games in heterogeneous spaces
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
HCS: a new local search strategy for memetic multiobjective evolutionary algorithms
IEEE Transactions 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
Solving multiobjective optimization problem by constraint optimization
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Modified genetic algorithms for manufacturing process planning in multiple parts manufacturing lines
Expert Systems with Applications: An International Journal
Constrained optimization based on modified differential evolution algorithm
Information Sciences: an International Journal
An improved (µ+λ)-constrained differential evolution for constrained optimization
Information Sciences: an International Journal
ICARIS'12 Proceedings of the 11th international conference on Artificial Immune Systems
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
A rough penalty genetic algorithm for constrained optimization
Information Sciences: an International Journal
International Journal of Bio-Inspired Computation
Comprehensive Survey of the Hybrid Evolutionary Algorithms
International Journal of Applied Evolutionary Computation
Engineering Applications of Artificial Intelligence
An evolutionary-based fuzzy resource assignment strategy for elastic traffic
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
An innovation approach for achieving cost optimization in supply chain management
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Hi-index | 0.00 |
This paper presents a novel evolutionary algorithm (EA) for constrained optimization problems, i.e., the hybrid constrained optimization EA (HCOEA). This algorithm effectively combines multiobjective optimization with global and local search models. In performing the global search, a niching genetic algorithm based on tournament selection is proposed. Also, HCOEA has adopted a parallel local search operator that implements a clustering partition of the population and multiparent crossover to generate the offspring population. Then, nondominated individuals in the offspring population are used to replace the dominated individuals in the parent population. Meanwhile, the best infeasible individual replacement scheme is devised for the purpose of rapidly guiding the population toward the feasible region of the search space. During the evolutionary process, the global search model effectively promotes high population diversity, and the local search model remarkably accelerates the convergence speed. HCOEA is tested on 13 well-known benchmark functions, and the experimental results suggest that it is more robust and efficient than other state-of-the-art algorithms from the literature in terms of the selected performance metrics, such as the best, median, mean, and worst objective function values and the standard deviations