— In this paper, the performance of a sequential Differential Evolution (DE) enhanced by neighborhood search (SDENS) is reported on the set of benchmark functions provided for th...
Abstract— Over the last years, interest in hybrid metaheuristics has risen considerably in the field of optimization. Combinations of methods such as evolutionary algorithms and...
— Many evolutionary algorithms have been proposed for large scale optimization. Parameter interaction in nonseparable problems is a major source of performance loss specially on ...
— The scaling properties of multimodal optimization methods have seldom been studied, and existing studies often concentrated on the idea that all local optima of a multimodal fu...
Abstract— In Evolutionary Robotics (ER), explicitly rewarding for behavioral diversity recently revealed to generate efficient results without recourse to complex fitness funct...
— In this paper, we illustrate the use of a reference point based many-objective particle swarm optimization algorithm to optimize low-speed airfoil aerodynamic designs. Our fram...
Upali K. Wickramasinghe, Robert Carrese, Xiaodong ...
Abstract— Locality - how well neighbouring genotypes correspond to neighbouring phenotypes - has been described as a key element in Evolutionary Computation. Grammatical Evolutio...
Jonathan Byrne, James McDermott, Edgar Galvá...
— This paper presents new upper bounds for binary covering arrays of variable strength constructed by using a new Simulated Annealing (SA) algorithm. This algorithm incorporates ...
Abstract—A key parameter affecting the operation of differential evolution (DE) is the crossover rate Cr ∈ [0, 1]. While very low values are recommended for and used with separ...
— Genetic programming is the usage of the paradigm of survival of the fittest in scientific computing. It is applied to evolve solutions to problems where dependencies between ...