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.
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Supplemental Notes:
- This paper was sponsored by TRB committee ADB30 Standing Committee on Transportation Network Modeling.
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Corporate Authors:
Transportation Research Board
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Authors:
- Gokalp, Can
- Boyles, Stephen D
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Conference:
- Transportation Research Board 98th Annual Meeting
- Location: Washington DC, United States
- Date: 2019-1-13 to 2019-1-17
- Date: 2019
Language
- English
Media Info
- Media Type: Digital/other
- Features: References; Tables;
- Pagination: 25p
Subject/Index Terms
- TRT Terms: Costs; Mathematical models; Networks; Optimization; Public transit; Standard deviation
- Subject Areas: Finance; Planning and Forecasting; Public Transportation;
Filing Info
- Accession Number: 01698263
- Record Type: Publication
- Report/Paper Numbers: 19-04781
- Files: TRIS, TRB, ATRI
- Created Date: Mar 1 2019 3:51PM