2002 · 41 citations · 15 references
EngineeringScatter SearchEvolutionary AlgorithmsOperations ResearchPermutation ProblemsMemetic AlgorithmGenetic AlgorithmCombinatorial OptimizationComputational GeometryEvolution-based MethodSearch-based Software EngineeringGa ImplementationIntelligent OptimizationComputer EngineeringComputer ScienceVariable Neighborhood SearchEvolutionary ProgrammingGenetic AlgorithmsExperimental Evaluation
The purpose of this work is to compare the performance of a scatter search (SS) implementation and an implementation of a genetic algorithm (GA) in the context of searching for optimal solutions to permutation problems. Scatter search and genetic algorithms are members of the evolutionary computation family. That is, they are both based on maintaining a population of solutions for the purpose of generating new trial solutions. We perform computational experiments with four well-known permutation problems to study and compare the performance of a SS and a GA implementation.
15