2002 · 21 citations · 9 references
Artificial IntelligenceEngineeringIndustrial EngineeringNon-generational Genetic AlgorithmGenetic AlgorithmSystems EngineeringHybrid Optimization TechniqueEvolutionary AlgorithmsMultiobjective OptimizationDomination CountCombinatorial OptimizationNeighborhood Density MeasureEvolution-based MethodEvolutionary Multimodal OptimizationEvolutionary ProgrammingOperations Research
In this paper a non-generational genetic algorithm for multiobjective optimization problems is proposed. For each element in the population a domination count is defined together with a neighborhood density measure based on a sharing function. Those two measures are then nonlinearly combined in order to define the individual's fitness. Numerical experiments with four test-problems taken from the evolutionary multiobjective literature are performed and the results are compared with those obtained by other evolutionary techniques.
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