Mean-Standard Deviation Model For Minimum Cost Flow Problem

The authors study the mean-standard deviation minimum cost flow (MSMCF) problem — where the objective is minimizing a linear combination of the mean and standard deviation of flow costs. The emerging optimization problem is both non-linear and non-additive in the objective, therefore not amenable to known methods for solving linear bi-criteria minimum cost flow problems. The authors prove that the efficient solution set of the MSMCF problem is a subset of the efficient solution set of the mean-variance minimum cost flow (MVMCF). Leveraging this result, the authors propose an algorithm that solves the MSMCF problem, by solving a series of simpler MVMCF problems. The authors further extend the results to more general bi-criteria non-additive minimum cost flow problems where the non-additive criteria is convex and differentiable. To demonstrate the performance of their method, the authors provide computational experiments on various sizes of randomly generated networks.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ADB30 Standing Committee on Transportation Network Modeling.
  • Corporate Authors:

    Transportation Research Board

    ,    
  • Authors:
    • Gokalp, Can
    • Boyles, Stephen D
  • Conference:
  • Date: 2019

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: References; Tables;
  • Pagination: 25p

Subject/Index Terms

Filing Info

  • Accession Number: 01698263
  • Record Type: Publication
  • Report/Paper Numbers: 19-04781
  • Files: TRIS, TRB, ATRI
  • Created Date: Mar 1 2019 3:51PM