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2004
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Dominance Based Crossover Operator for Evolutionary Multi-objective Algorithms

9 years 22 days ago
Dominance Based Crossover Operator for Evolutionary Multi-objective Algorithms
In spite of the recent quick growth of the Evolutionary Multi-objective Optimization (EMO) research field, there has been few trials to adapt the general variation operators to the particular context of the quest for the Pareto-optimal set. The only exceptions are some mating restrictions that take in account the distance between the potential mates – but contradictory conclusions have been reported. This paper introduces a particular mating restriction for Evolutionary Multi-objective Algorithms, based on the Pareto dominance relation: the partner of a non-dominated individual will be preferably chosen among the individuals of the population that it dominates. Coupled with the BLX crossover operator, two different ways of generating offspring are proposed. This recombination scheme is validated within the well-known NSGA-II framework on three bi-objective benchmark problems and one real-world bi-objective constrained optimization problem. An acceleration of the progress of the p...
Olga Rudenko, Marc Schoenauer
Added 02 Jul 2010
Updated 02 Jul 2010
Type Conference
Year 2004
Where PPSN
Authors Olga Rudenko, Marc Schoenauer
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