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Decision Uncertainty in Multiobjective Optimization by Gabriele Eichfelder; Corinna Krüger; Anita Schöbel is a Computer Science article available to read on EtoBox.

What is Decision Uncertainty in Multiobjective Optimization about?

In many real-world optimization problems, a solution cannot be realized in practice exactly as computed, e.g., it may be impossible to produce a board of exactly 3.546 mm width. Whenever computed solutions are not realized exactly but in a perturbed way, we speak of decision uncertainty. We study decision uncertainty in multiobjective optimization problems and we propose the concept of decision robust efficiency for evaluating the robustness of a solution in this case. This solution concept is defined by using the framework of set-valued maps. We prove that convexity and continuity are preserved by the resulting set-valued maps. Moreover, we obtain specific results for particular classes of objective functions that are relevant for solving the set-valued problem. We furthermore prove that decision robust efficient solutions can be found by solving a deterministic problem in case of linear objective functions. We also investigate the relationship of the proposed concept to other concepts in the literature.

Who reads Decision Uncertainty in Multiobjective Optimization?

Author

Gabriele Eichfelder; Corinna Krüger; Anita Schöbel

Publisher

Springer Science and Business Media LLC

Published

2017

Language

EN

Field

Computer Science (Physical Sciences)