Sensitivity analysis of a dynamic fleet management model using approximate dynamic programming

Huseyin Topaloglu, Warren Buckler Powell

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

We present tractable algorithms to assess the sensitivity of a stochastic dynamic fleet management model to fleet size and load availability. In particular, we show how to compute the change in the objective function value in response to an additional vehicle or an additional load introduced into the system. The novel aspect of our approach is that it does not require multiple simulations with different values of the model parameters, and in this respect it differs from trial-anderror-based "what-if" analyses. Numerical experiments show that the proposed methods are accurate and computationally attractive.

Original languageEnglish (US)
Pages (from-to)319-331
Number of pages13
JournalOperations Research
Volume55
Issue number2
DOIs
StatePublished - Mar 2007

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Management Science and Operations Research

Keywords

  • Dynamic programming/optimal control: applications
  • Network
  • Transportation: models

Fingerprint

Dive into the research topics of 'Sensitivity analysis of a dynamic fleet management model using approximate dynamic programming'. Together they form a unique fingerprint.

Cite this