Journal of Global Optimization
Differential Evolution Training Algorithm for Feed-Forward Neural Networks
Neural Processing Letters
A Trigonometric Mutation Operation to Differential Evolution
Journal of Global Optimization
Population set-based global optimization algorithms: some modifications and numerical studies
Computers and Operations Research
DE/EDA: a new evolutionary algorithm for global optimization
Information Sciences—Informatics and Computer Science: An International Journal
Two improved differential evolution schemes for faster global search
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
A Fuzzy Adaptive Differential Evolution Algorithm
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
Exploring dynamic self-adaptive populations in differential evolution
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Large scale evolutionary optimization using cooperative coevolution
Information Sciences: an International Journal
Automatic image pixel clustering with an improved differential evolution
Applied Soft Computing
Differential evolution algorithm with strategy adaptation for global numerical optimization
IEEE Transactions on Evolutionary Computation
Differential evolution using a neighborhood-based mutation operator
IEEE Transactions on Evolutionary Computation
JADE: adaptive differential evolution with optional external archive
IEEE Transactions on Evolutionary Computation
Differential evolution algorithm with ensemble of parameters and mutation strategies
Applied Soft Computing
A study on scale factor in distributed differential evolution
Information Sciences: an International Journal
Disturbed Exploitation compact Differential Evolution for limited memory optimization problems
Information Sciences: an International Journal
An effective memetic differential evolution algorithm based on chaotic local search
Information Sciences: an International Journal
System design by constraint adaptation and differential evolution
IEEE Transactions on Evolutionary Computation
An orthogonal genetic algorithm for multimedia multicast routing
IEEE Transactions on Evolutionary Computation
An orthogonal genetic algorithm with quantization for globalnumerical optimization
IEEE Transactions on Evolutionary Computation
Hybrid Taguchi-genetic algorithm for global numerical optimization
IEEE Transactions on Evolutionary Computation
Intelligent evolutionary algorithms for large parameter optimization problems
IEEE Transactions on Evolutionary Computation
Comprehensive learning particle swarm optimizer for global optimization of multimodal functions
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
An Evolutionary Algorithm for Global Optimization Based on Level-Set Evolution and Latin Squares
IEEE Transactions on Evolutionary Computation
Opposition-Based Differential Evolution
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
Enhanced Differential Evolution With Adaptive Strategies for Numerical Optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A note on teaching-learning-based optimization algorithm
Information Sciences: an International Journal
Optimized bi-dimensional data projection for clustering visualization
Information Sciences: an International Journal
Differential evolution with local information for neuro-fuzzy systems optimisation
Knowledge-Based Systems
Exploration and exploitation in evolutionary algorithms: A survey
ACM Computing Surveys (CSUR)
Adaptive Memetic Differential Evolution with Global and Local neighborhood-based mutation operators
Information Sciences: an International Journal
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Differential evolution (DE) is a class of simple yet powerful evolutionary algorithms for global numerical optimization. Binomial crossover and exponential crossover are two commonly used crossover operators in current popular DE. It is noteworthy that these two operators can only generate a vertex of a hyper-rectangle defined by the mutant and target vectors. Therefore, the search ability of DE may be limited. Orthogonal crossover (OX) operators, which are based on orthogonal design, can make a systematic and rational search in a region defined by the parent solutions. In this paper, we have suggested a framework for using an OX in DE variants and proposed OXDE, a combination of DE/rand/1/bin and OX. Extensive experiments have been carried out to study OXDE and to demonstrate that our framework can also be used for improving the performance of other DE variants.