Approximating Combinatorial Optimization Problems with Uncertain Costs and the OWA Criterion

Adam Kasperski and Paweł Zieliński ()
Additional contact information
Paweł Zieliński: Wrocław University of Technology

A chapter in Operations Research Proceedings 2012, 2014, pp 141-146 from Springer

Abstract: Abstract In this paper a class combinatorial optimization problems with uncertain costs is discussed. This uncertainty is modeled by specifying a scenario set containing K distinct cost vectors. In order to choose a solution the Ordered Weighted Averaging aggregation operator (OWA) is used. For most classical problems, for example network problems, minimizing OWA is NP-hard even for two scenarios. In this paper some positive and negative approximation results for the problem are shown.

Keywords: Uncertain Costs; Class Combinatorial Optimization Problems; Cost Vector; Network Problems; Fully Polynomial Time Approximation Scheme (FPTAS) (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:spr:oprchp:978-3-319-00795-3_21

Ordering information: This item can be ordered from
http://www.springer.com/9783319007953

DOI: 10.1007/978-3-319-00795-3_21

Access Statistics for this chapter

More chapters in Operations Research Proceedings from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().