Distributionally robust origin–destination demand estimation
Authors:
- Jingxing WangJWJingxing Wang
- Jun SongJSJun Song
- Chaoyue ZhaoCZChaoyue Zhao
- Xuegang (Jeff) BanXBXuegang (Jeff) Ban
- 6 July 2024
- journal article
- research article
- Published by Elsevier in Transportation Research Part C: Emerging Technologies
- Vol. 165
Abstract
No abstract availableKeywords
Funding Information
- National Science Foundation (CMMI-1825053)
This publication has 27 references indexed in Scilit:
- Data-driven risk-averse stochastic optimization with Wasserstein metricOperations Research Letters, 2018
- Distributionally robust optimization for planning and scheduling under uncertaintyComputers & Chemical Engineering, 2018
- Stochastic travel demand estimation: Improving network identifiability using multi-day observation setsTransportation Research Part B: Methodological, 2018
- Data-driven distributionally robust optimization using the Wasserstein metric: performance guarantees and tractable reformulationsMathematical Programming, 2017
- Fine-grained OD estimation with automated zoning and sparsity regularisationTransportation Research Part B: Methodological, 2015
- Estimation of mean and covariance of peak hour origin–destination demands from day-to-day traffic countsTransportation Research Part B: Methodological, 2014
- Consistent formulation of network equilibrium with stochastic flowsTransportation Research Part B: Methodological, 2014
- Solving two-stage robust optimization problems using a column-and-constraint generation methodOperations Research Letters, 2013
- Estimation of origin–destination matrices from link counts and sporadic routing dataTransportation Research Part B: Methodological, 2012
- Modelling network travel time reliability under stochastic demandTransportation Research Part B: Methodological, 2005