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Multidimensional decision-making today involves balancing multiple objectives, such as economic, environmental, social, and technical factors. This complexity necessitates multiobjective optimization, which extends traditional single-objective approaches. In this context, objectives can conflict, leading to the concept of Pareto optimality, where no objective can be improved without worsening another. The challenge lies in selecting a preferred solution from the Pareto set, focusing on how to derive a compromise that reflects the decision maker's subjective judgments.
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Fuzzy Sets and Interactive Multiobjective Optimization, Masatoshi Sakawa
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- 2013
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