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Robot Base Disturbance Optimization with Compact Differential Evolution Light
(Springer Berlin Heidelberg, 2012-04)
Despite the constant growth of the computational power in consumer electronics, very simple hardware is still used in space applications. In order to obtain the highest possible reliability, in space systems limited-power ...
Three variants of three Stage Optimal Memetic Exploration for handling non-separable fitness landscapes
(IEEE, 2012-09)
Three Stage Optimal Memetic Exploration (3SOME) is a recently proposed algorithmic framework which sequentially perturbs a single solution by means of three operators. Although 3SOME proved to be extremely successful at ...
Meta-Lamarckian learning in three stage optimal memetic exploration
(IEEE Xplore, 2012-09)
Three Stage Optimal Memetic Exploration (3SOME) is a single-solution optimization algorithm where the coordinated action of three distinct operators progressively perturb the solution in order to progress towards the ...
Continuous Parameter Pools in Ensemble Differential Evolution
(IEEE, 2015-12)
Ensemble of parameters and mutation strategies differential evolution (EPSDE) is an elegant promising optimization framework based on the idea that a pool of mutation and crossover strategies along, with associated pools ...
Compact differential evolution light: high performance despite limited memory requirement and modest computational overhead
(Springer US, 2012-09-01)
Compact algorithms are Estimation of Distribution Algorithms which mimic the behavior of population-based algorithms by means of a probabilistic representation of the population of candidate solutions. These algorithms ...
The Importance of Being Structured: a Comparative Study on Multi Stage Memetic Approaches
(IEEE, 2012-09)
Memetic Computing (MC) is a discipline which studies optimization algorithms and sees them as structures of operators, the memes. Although the choice of memes is crucial for an effective algorithmic design, special attention ...
A Differential Evolution Framework with Ensemble of Parameters and Strategies and Pool of Local Search Algorithms
(Springer Berlin Heidelberg, 2014-11)
The ensemble structure is a computational intelligence supervised strategy consisting of a pool of multiple operators that compete among each other for being selected, and an adaptation mechanism that tends to reward the ...
Multicriteria adaptive differential evolution for global numerical optimization
(IOS Press, 2015-02-01)
Differential evolution (DE) has become a prevalent tool for global optimization problems since it was proposed in 1995. As usual, when applying DE to a specific problem, determining the most proper strategy and its associated ...