Ranking Approach to Max-Ordering Combinatorial Optimization and Network Flows
- Max ordering (MO) optimization is introduced as tool for modelling production planning with unknown lot sizes and in scenario modelling. In MO optimization a feasible solution set \(X\) and, for each \(x\in X, Q\) individual objective functions \(f_1(x),\dots,f_Q(x)\) are given. The max ordering objective \(g(x):=max\) {\(f_1(x),\dots,f_Q(x)\)} is then minimized over all \(x\in X\). The paper discusses complexity results and describes exact and approximative algorithms for the case where \(X\) is the solution set of combinatorial optimization problems and network flow problems, respectively.
Author: | Claus Hüsselmann, Horst W. Hamacher |
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URN: | urn:nbn:de:hbz:386-kluedo-50441 |
Series (Serial Number): | Preprints (rote Reihe) des Fachbereich Mathematik (246) |
Document Type: | Report |
Language of publication: | English |
Date of Publication (online): | 2017/11/07 |
Year of first Publication: | 1993 |
Publishing Institution: | Technische Universität Kaiserslautern |
Date of the Publication (Server): | 2017/11/07 |
Page Number: | 22 |
Faculties / Organisational entities: | Kaiserslautern - Fachbereich Mathematik |
DDC-Cassification: | 5 Naturwissenschaften und Mathematik / 510 Mathematik |
Licence (German): | Creative Commons 4.0 - Namensnennung, nicht kommerziell, keine Bearbeitung (CC BY-NC-ND 4.0) |