The minmax regret inverse maximum weight problem

Kien Trung Nguyen and Nguyen Thanh Hung

Applied Mathematics and Computation, 2021, vol. 407, issue C

Abstract: Let a ground set E and a prespecified element be given. We address the problem of modifying the weight of each element in E at minimum cost so that the weight of the prespecified element become the maximum one in the perturbed set. Moreover, as modifying costs are usually uncertain in many real life situations, we measure the robustness by taking into account the minmax regret inverse maximum weight problem on E. In order to solve the problem, we first prove that there are exactly two scenarios that lead to the maximum regret of the cost function. Based on the convexity of the objective function, we develop a combinatorial algorithm that solves the corresponding problem in linear time.

Keywords: Minmax regret; Robustness; Inverse optimization; Uncertainty; Convexity (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300321004173
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:407:y:2021:i:c:s0096300321004173

DOI: 10.1016/j.amc.2021.126328

Access Statistics for this article

Applied Mathematics and Computation is currently edited by Theodore Simos

More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().