Capacity Inverse Minimum Cost Flow Problem

  • Given a directed graph G = (N,A) with arc capacities u and a minimum cost flow problem defined on G, the capacity inverse minimum cost flow problem is to find a new capacity vector u' for the arc set A such that a given feasible flow x' is optimal with respect to the modified capacities. Among all capacity vectors u' satisfying this condition, we would like to find one with minimum ||u' - u|| value. We consider two distance measures for ||u' - u||, rectilinear and Chebyshev distances. By reduction from the feedback arc set problem we show that the capacity inverse minimum cost flow problem is NP-hard in the rectilinear case. On the other hand, it is polynomially solvable by a greedy algorithm for the Chebyshev norm. In the latter case we propose a heuristic for the bicriteria problem, where we minimize among all optimal solutions the number of affected arcs. We also present computational results for this heuristic.

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Metadaten
Author:Cigdem Güler, Horst Hamacher
URN (permanent link):urn:nbn:de:hbz:386-kluedo-15097
Serie (Series number):Report in Wirtschaftsmathematik (WIMA Report) (111)
Document Type:Preprint
Language of publication:English
Year of Completion:2007
Year of Publication:2007
Publishing Institute:Technische Universität Kaiserslautern
Tag:inverse problems ; minimum cost flows; network flows
Faculties / Organisational entities:Fachbereich Mathematik
DDC-Cassification:510 Mathematik

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