Stochastic integer programming by dynamic programming

B.J. Lageweg, J.K. Lenstra, A.H.G. Rinnooy Kan, L. Stougie

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

3 Downloads (Pure)

Abstract

Stochastic integer programming is a suitable tool for modeling hierarchical decision situations with combinatorial features. In continuation of our work on the design and analysis of heuristics for such problems, we now try to find optimal solutions. Dynamic programming techniques can be used to exploit the structure of two-stage scheduling, bin packing and multiknapsack problems. Numerical results for small instances of these problems are presented.
Original languageEnglish
Title of host publicationNumerical techniques for stochastic optimization
EditorsYu. Ermoliev, R.J.B. Wets
Place of PublicationNew York
PublisherSpringer
Pages403-412
ISBN (Print)0-387-18677-8
Publication statusPublished - 1988

Publication series

NameSpringer Series in Computational Mathematics
Volume10
ISSN (Print)0179-3632

Fingerprint

Dive into the research topics of 'Stochastic integer programming by dynamic programming'. Together they form a unique fingerprint.

Cite this