Dynamic-programming approximations for stochastic time-staged integer multicommodity-flow problems

Huseyin Topaloglu, Warren Buckler Powell

Research output: Contribution to journalArticle

103 Scopus citations

Abstract

In this paper, we consider a stochastic and time-dependent version of the min-cost integer multicommodity-flow problem that arises in the dynamic resource allocation context. In this problem class, tasks arriving over time have to be covered by a set of indivisible and reusable resources of different types. The assignment of a resource to a task removes the task from the system, modifies the resource, and generates a profit. When serving a task, resources of different types can serve as substitutes of each other, possibly yielding different revenues. We propose an iterative, adaptive dynamic-programming-based methodology that makes use of linear or nonlinear approximations of the value function. Our numerical work shows that the proposed method provides high-quality solutions and is computationally attractive for large problems.

Original languageEnglish (US)
Pages (from-to)31-42
Number of pages12
JournalINFORMS Journal on Computing
Volume18
Issue number1
DOIs
StatePublished - Dec 1 2006

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems
  • Computer Science Applications
  • Management Science and Operations Research

Keywords

  • Dynamic programming
  • Multicommodity
  • Networks-graphs
  • Transportation

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