Global optimization
Global optimization of composite laminates using improving hit and run
Recent advances in global optimization
A deterministic algorithm for global optimization
Mathematical Programming: Series A and B
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Testing Unconstrained Optimization Software
ACM Transactions on Mathematical Software (TOMS)
Journal of Global Optimization
A Note on the Griewank Test Function
Journal of Global Optimization
A Trigonometric Mutation Operation to Differential Evolution
Journal of Global Optimization
Robust Estimation of Camera Rotation, Translation and Focal Length at High Outlier Rates
CRV '04 Proceedings of the 1st Canadian Conference on Computer and Robot Vision
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
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Two improved differential evolution schemes for faster global search
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Journal of Global Optimization
A Fuzzy Adaptive Differential Evolution Algorithm
Soft Computing - A Fusion of Foundations, Methodologies and Applications
A Note on the Extended Rosenbrock Function
Evolutionary Computation
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Exploring dynamic self-adaptive populations in differential evolution
Soft Computing - A Fusion of Foundations, Methodologies and Applications
On the significance of the permutation problem in neuroevolution
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
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
Cooperative co-evolutionary differential evolution for function optimization
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Self-Adaptive chaos differential evolution
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Scale invariant robust registration of 3d-point data and a triangle mesh by global optimization
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
Self-adaptive differential evolution
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Opposition-Based Differential Evolution
IEEE Transactions on Evolutionary Computation
Adaptive Memetic Differential Evolution with Global and Local neighborhood-based mutation operators
Information Sciences: an International Journal
Moving object detection using Markov Random Field and Distributed Differential Evolution
Applied Soft Computing
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Differential Evolution (DE) is a widely used successful evolutionary algorithm (EA) based on a population of individuals, which is especially well suited to solve problems that have non-linear, multimodal cost functions. However, for a given population, the set of possible new populations is finite and a true subset of the cost function domain. Furthermore, the update formula of DE does not use any information about the fitness of the population. This paper presents a novel extension of DE called Randomized and Rank-based Differential Evolution (R2DE) and its self-adaptive version SAR2DE to improve robustness and global convergence speed on multimodal problems by introducing two multiplicative terms in the DE update formula. The first term is based on a random variate of a Cauchy distribution, which leads to a randomization. The second term is based on ranking of individuals, so that R2DE exploits additional information provided by the population fitness. In extensive experiments conducted with a wide range of complexity settings, we show that the proposed heuristics lead to an overall improvement in robustness and speed of convergence compared to several global optimization techniques, including DE, Opposition based Differential Evolution (ODE), DE with Random Scale Factor (DERSF) and the self-adaptive Cauchy distribution based DE (NSDE).