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PSFGA: A Parallel Genetic Algorithm for Multiobjective Optimization
Canary Islands, Spain January 09-January 11
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/PDP.2002.1000210th Euromicro Workshop on Parallel, ...
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This paper presents the Parallel Single Front Genetic Algorithm (PSFGA), a parallel Pareto-based algorithm for multiobjective optimization problems based on an evolutionary procedure. In this procedure, a population of solutions is sorted with respect to the values of the objective functions and partitioned into subpopulations which are distributed among the processors. Each processor applies a sequential multiobjective genetic algorithm that we have devised (called Single Front Genetic Algorithm, SFGA) to its subpopulation. Experimental results are provided comparing PSFGA with previously proposed multiobjective evolutionary algorithms.
Citation:
"PSFGA: A Parallel Genetic Algorithm for Multiobjective Optimization," pdp, pp.0384, 10th Euromicro Workshop on Parallel, Distributed and Network-based Processing (EUROMICRO-PDP 2002), 2002
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