Use of a self-adaptive penalty approach for engineering optimization problems
Computers in Industry
Journal of Global Optimization
An effective co-evolutionary particle swarm optimization for constrained engineering design problems
Engineering Applications of Artificial Intelligence
A multiview approach for intelligent data analysis based on data operators
Information Sciences: an International Journal
Evolutionary algorithms for constrained parameter optimization problems
Evolutionary Computation
Differential evolution with dynamic stochastic selection for constrained optimization
Information Sciences: an International Journal
Easy Efficiency-Enhancement Technique for the ECGA
SBRN '08 Proceedings of the 2008 10th Brazilian Symposium on Neural Networks
Easy Efficiency-Enhancement Technique for the ECGA
SBRN '08 Proceedings of the 2008 10th Brazilian Symposium on Neural Networks
Learning from Multiple Sources
The Journal of Machine Learning Research
Advances in Differential Evolution
Advances in Differential Evolution
Expert Systems with Applications: An International Journal
Differential evolution algorithm with strategy adaptation for global numerical optimization
IEEE Transactions on Evolutionary Computation
Fundamenta Informaticae - Swarm Intelligence
ISDA '09 Proceedings of the 2009 Ninth International Conference on Intelligent Systems Design and Applications
JADE: adaptive differential evolution with optional external archive
IEEE Transactions on Evolutionary Computation
Information Sciences: an International Journal
Information Sciences: an International Journal
Disturbed Exploitation compact Differential Evolution for limited memory optimization problems
Information Sciences: an International Journal
Society and civilization: An optimization algorithm based on the simulation of social behavior
IEEE Transactions on Evolutionary Computation
Accelerating Differential Evolution Using an Adaptive Local Search
IEEE Transactions on Evolutionary Computation
Differential Evolution: A Survey of the State-of-the-Art
IEEE Transactions on Evolutionary Computation
Differential Evolution With Composite Trial Vector Generation Strategies and Control Parameters
IEEE Transactions on Evolutionary Computation
Hi-index | 12.05 |
Several constrained and unconstrained optimization problems have been adequately solved over the years thanks to advances in the metaheuristics area. In the last decades, different metaheuristics have been proposed employing new ideas, and hybrid algorithms that improve the original metaheuristics have been developed. One of the most successfully employed metaheuristics is the Differential Evolution. In this paper it is proposed a Multi-View Differential Evolution algorithm (MVDE) in which several mutation strategies are applied to the current population to generate different views at each iteration. The views are then merged according to the winner-takes-all paradigm, resulting in automatic exploration/exploitation balance. MVDE was tested to solve a set of well-known constrained engineering design problems and the obtained results were compared to those from many state-of-the-art metaheuristics. Results show that MVDE was very competitive in the considered problems, largely outperforming several of the compared algorithms.