Nonlinear inverse optimization for parameter estimation of commodity-vehicle-decoupled freight assignment

Joseph Y.J. Chow, Stephen G. Ritchie and Kyungsoo Jeong

Transportation Research Part E: Logistics and Transportation Review, 2014, vol. 67, issue C, 71-91

Abstract: A systematic approach to estimate parameters from noisy priors is proposed for traffic assignment problems. It extends inverse optimization theory to nonlinear problems, and defines a new class of parameter estimation problems in the transportation literature for networks under congestion. The approach is used to systematically calibrate a new link-based variation of the STAN model which decouples commodity flows and vehicle flows. The models are tested on a small network and then a case study with real data from California statewide implementation. Cross-validation shows 15% CV of the RMSE.

Keywords: Nonlinear optimization; Transshipment; Freight forecast; Inverse optimization; Network assignment (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (7)

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DOI: 10.1016/j.tre.2014.04.004

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