Preference Incorporation in Multi-objective Evolutionary Algorithms: A Survey
作者： L. Rachmawati , D. Srinivasan
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摘要: This paper presents a review of preference incorporation in Multi-Objective Evolutionary Algorithms (MOEA). The Multi-objective Optimization (EMO) promotes better decision-making. Introducing MOEAs increases the specificity selection, leading to solutions which are higher relevance Decision Maker(s). When many objectives involved, MOEA based on pure Pareto-optimality criterion may not achieve meaningful search. addresses this concern. is difficult because uncertainties arising from lack prior problem knowledge and fuzziness human preference. Further, decision making complex ill-defined process at times could be mathematically characterized. These concerns must addressed
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