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In recent decades, multi-objective evolutionary algorithms (MOEAs) are developed as powerful tools to solve multi-objective optimization problems. While the diversity of Pareto front (PF) plays an important role in the performance evaluation of MOEAs, various diversity preservation strategies (DPS) have been developed. In this paper, a novel approach that inspired from the crowding distance technique...
Some important issues on the determination of weights in multi-objective decision making (MODM) and multiple learning machines system (MLMS) are discussed: it is presented that determining weights is an important evaluation process; some drawbacks of several current methods of determining weights with the help of optimization are analyzed. Meanwhile, it is pointed out that it's not overall and unreliable...
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