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A Parallel evolutionary approach to multi-objective optimization
2007
2007 IEEE Congress on Evolutionary Computation
Evolutionary algorithms have been used since the mid-eighties to solve complex single and multi-objective optimization problems. More recently the swarm intelligent approaches such as particle swarm optimization and ant colony optimization have been successfully used for multiobjective optimization. This paper proposes a new approach based on the generic generalized particle model (GE-GPM) for computing in parallel approximate efficient solutions for the distribution problem with multiple
doi:10.1109/cec.2007.4424606
dblp:conf/cec/FengL07
fatcat:4zqp5k3ckjccpfncl4fwsza3sm