Abstract
Evolutionary multi-objective optimization aims to provide a representative subset of the Pareto front to decision makers. In practice, however, decision makers are usually interested in only a particular part of the Pareto front of the multi-objective optimization problem. This is particularly true when the number of objectives becomes large. Over the past decade, preference-based multi-objective optimization has attracted increasing attention from both academia and industry due to its significance in both theory and practice. Significant progress has been made in evolutionary multi-objective optimization and multi-criteria decision communities, although many open issues still remain to be addressed. This paper provides a concise review on preference-based multi-objective optimization, including various preference modeling methods and existing preference-based optimization methods, as well as a brief discussion of the main future challenges.
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CITATION STYLE
Wang, H., Olhofer, M., & Jin, Y. (2017). A mini-review on preference modeling and articulation in multi-objective optimization: current status and challenges. Complex & Intelligent Systems, 3(4), 233–245. https://doi.org/10.1007/s40747-017-0053-9
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