Robust Optimization with Scenarios Using Belief Functions

Romain Guillaume (), Adam Kasperski () and Paweł Zieliński ()
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Romain Guillaume: Université de Toulouse-IRIT
Adam Kasperski: Wrocław University of Science and Technology
Paweł Zieliński: Wrocław University of Science and Technology

A chapter in Operations Research Proceedings 2021, 2022, pp 114-119 from Springer

Abstract: Abstract In this paper a class of optimization problems with uncertain objective function coefficients is considered. The uncertainty is specified by providing a scenario set containing a finite number of parameter realizations, called scenarios. Additional knowledge about scenarios is modeled by specifying a mass function, which defines a belief function in scenario set. The generalized Hurwicz criterion is then used to compute a solution. Various computational properties of the resulting optimization problem are presented.

Keywords: Robust optimization; Belief function; Hurwicz criterion (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-3-031-08623-6_18

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DOI: 10.1007/978-3-031-08623-6_18

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