期刊
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
卷 159, 期 -, 页码 -出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ijar.2023.108941
关键词
Robust optimization; Hurwicz criterion; Belief function; Possibility theory
This paper investigates an optimization problem with uncertain objective function coefficients. The uncertainty is described by a discrete scenario set. The concept of belief function is used to define admissible probability distributions over the scenario set. The generalized Hurwicz criterion is applied to compute a solution. The complexity of the problem is explored and exact and approximation methods are proposed.
In this paper, an optimization problem with uncertain objective function coefficients is considered. The uncertainty is specified by providing a discrete scenario set containing possible realizations of the objective function coefficients. The concept of belief function in the traditional and possibilistic setting is applied to define a set of admissible probability distributions over the scenario set. The generalized Hurwicz criterion is then used to compute a solution. In this paper, the complexity of the resulting problem is explored. Some exact and approximation methods of solving it are proposed. & COPY; 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons .org /licenses /by /4 .0/).
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