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Self-adaptation is an efficient way to control the strategy parameters of an Evolutionary Algorithm automatically during optimization. It is based on implicit evolutionary search in the space of strategy parameters, and has been proven to work well as on-line parameter control method for a variety of strategy parameters, from local to global ones. Our proposed Self-Adaptive Multi-Objective Evolutionary...
We propose a hybrid approach for multi-objective assignment problem which combines genetic algorithm and mathematical programming techniques. This method is based on the dominance cost variant of the multi-objective genetic algorithm hybridized with exact method. The initial population is generated by solving a series of mono-objective assignment problems obtained by a suitable choice of a set of...
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