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Multi-objective evolutionary algorithms which use non-dominated sorting and sharing have been mainly criticized for their (i) ¥ is the number of objectives and § is the population size), (ii) non-elitism approach, and (iii) the need for specifying a sharing parameter. In this paper, we suggest a non-dominated sorting based multi-objective evolutionary(More)
—Multiobjective evolutionary algorithms (EAs) that use nondominated sorting and sharing have been criticized mainly for their: 1) (3) computational complexity (where is the number of objectives and is the population size); 2) nonelitism approach; and 3) the need for specifying a sharing parameter. In this paper, we suggest a nondominated sorting-based(More)
Multi-objective evolutionary algorithms which use non-dominated sorting and sharing have been mainly criticized for their (i) Ç´ÑAE ¿ µ computational complexity (where Ñ is the number of objectives and AE is the population size), (ii) non-elitism approach, and (iii) the need for specifying a sharing parameter. In this paper, we suggest a non-dominated(More)
Vehicle driving consumes time and energy (fuel, electricity etc.). Usually both have to be minimized. Minimizing the consumption of one of them leads to increasing the consumption of the other. To find driving strategies that take into consideration both objectives, we have implemented a multiobjective genetic algorithm that constructs driving strategies as(More)
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