LCGA: Local Cultivation Genetic Algorithm for multi-objective optimization problems
S Watanabe, T Hiroyasu, M Miki - … of the 4th Annual Conference on …, 2002 - dl.acm.org
S Watanabe, T Hiroyasu, M Miki
Proceedings of the 4th Annual Conference on Genetic and Evolutionary Computation, 2002•dl.acm.orgIn this paper, a new genetic algorithm for multi-objective optimization problems is
introduced. That is called" Local Cultivation GA (LCGA)". LCGA has a neighborhood
crossover mechanism in addition to the mechanism of GAs that had proposed in the past
researches. As compared with SPEA2, NSGA-II, and MOGA, LCGA is the robust algorithm
which should find the Pareto optimum solution. Since LCGA is easy to implement to parallel
computer as a master-slave model, the reduction of calculation cost can be expected.
introduced. That is called" Local Cultivation GA (LCGA)". LCGA has a neighborhood
crossover mechanism in addition to the mechanism of GAs that had proposed in the past
researches. As compared with SPEA2, NSGA-II, and MOGA, LCGA is the robust algorithm
which should find the Pareto optimum solution. Since LCGA is easy to implement to parallel
computer as a master-slave model, the reduction of calculation cost can be expected.
In this paper, a new genetic algorithm for multi-objective optimization problems is introduced. That is called "Local Cultivation GA (LCGA)". LCGA has a neighborhood crossover mechanism in addition to the mechanism of GAs that had proposed in the past researches. As compared with SPEA2, NSGA-II, and MOGA, LCGA is the robust algorithm which should find the Pareto optimum solution. Since LCGA is easy to implement to parallel computer as a master-slave model, the reduction of calculation cost can be expected.
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