What Should We Learn? Uncertain Multicriteria Decision Making Using Evolutionary Algorithms

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What Should We Learn? Uncertain Multicriteria Decision Making Using Evolutionary Algorithms

Yang Li

Uncertain multicriteria decision making is to select or rank objects based on the evaluation done by the decisionmaker on several criteria under uncertainty. Uncertain multicriteria decision making has been proved as a useful means in diverse fields such as management, finance, economics, education, environmental protection, medicine, engineering, and so on. Due to numerous successful applications, it becomes more and more prevailing.

It becomes quite a challenging task, as far as the solution methodologies of uncertain multicriteria decision making is concerned. The complexity becomes more and more significant in terms of problem size (e.g., number of criteria, size of the search space). Moreover, the solution time has to be reasonable for most of the problems encountered in practice. Hence, the development of advanced multicriteria evolutionary algorithms has been widely investigated.

The purpose of the special issue Uncertain Multicriteria Decision Making Using Evolutionary Algorithms published in IEEE Transactions on Fuzzy Systems in May 2019 is to gather together high quality papers which significantly contribute to new theories, applications, and algorithms about uncertain multicriteria decision making. It not only reports recent significant developments but also highlights potential, growing research directions, and future trends, which will benefit researchers in studying theories, applications, and algorithms about uncertain multicriteria/multiobjective/multiattribute decision making.

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