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Multi-objective optimization problems with interval (MOPs-I) uncertainties parameters are common in practice. Evolutionary multi-objective (EMO) algorithms are popularly employed to solve these problems due to their powerful explorations. The comparison strategies among interval objectives of MOPs-I are crucially important for obtaining a superior Pareto front when applying EMOs. By effectively combining...
In this paper we give a survey of multi-objective scheduling that have appeared in the literature or are to appear. Firstly, some basic concepts about multi-objective optimization and prevalent approaches for multi-objective optimization are given. Then, several multi-objective scheduling models are introduced and the comprehensive review of recent study on them is summarized. Finally, the trend of...
A novel approach to construct accurate and interpretable fuzzy classification system based on hybrid co-evolution algorithm is proposed in this paper. First, the necessary conditions of interpretability are analyzed. Second, the search ability of Michigan-style and Pittsburgh-style genetic algorithm is examined respectively for designing fuzzy classification system. It is clearly demonstrated that...
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