0–1 Multiband Robust Optimization

Christina Büsing (), Fabio D’Andreagiovanni () and Annie Raymond ()
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Christina Büsing: RWTH Aachen University
Fabio D’Andreagiovanni: Technical University Berlin
Annie Raymond: Zuse-Institut Berlin (ZIB)

A chapter in Operations Research Proceedings 2013, 2014, pp 89-95 from Springer

Abstract: Abstract We provide an overview of new theoretical results that we obtained while further investigating multiband robust optimization, a new model for robust optimization that we recently proposed to tackle uncertainty in mixed-integer linear programming. This new model extends and refines the classical $$\varGamma $$ Γ -robustness model of Bertsimas and Sim and is particularly useful in the common case of arbitrary asymmetric distributions of the uncertainty. Here, we focus on uncertain 0–1 programs and we analyze their robust counterparts when the uncertainty is represented through a multiband set. Our investigations were inspired by the needs of our industrial partners in the research project ROBUKOM [2].

Keywords: Robust Optimization; Valid Inequality; Cost Coefficient; Robust Counterpart; Minimum Span Tree Problem (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-319-07001-8_13

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DOI: 10.1007/978-3-319-07001-8_13

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