TY - JOUR
T1 - Dynamic trucking equilibrium through a freight exchange
AU - Miller, John
AU - Nie, Yu
N1 - Funding Information:
This work was partially funded by the US National Science Foundation and by the Chinese National Science Foundation (CNSF) under award numbers PFI:BIC 1534138 and 71728001 respectively. The data were obtained by a collaborative effort with Southwest Jiaotong University under the CNSF grant. The first author thanks the Eisenhower Transportation Fellowship for partly funding his Ph.D. at Northwestern University, during which this work was done. The authors are grateful to three anonymous reviewers for their constructive comments.
PY - 2018
Y1 - 2018
N2 - This paper proposes a new hyperpath-based dynamic trucking equilibrium (DTE) assignment model. Unlike existing freight assignment models, we focus on the interactions between individual truck operators that solely compete for loads advertised on an online freight exchange. The competitors are assumed to follow optimal bidding and routing strategies - represented using a hyperpath - to maximize their expected profit. The proposed DTE model (1) predicts system-wide truck flows (including empty truck flows), (2) identifies efficiency improvements gained by network-wide visibility, and (3) lays the foundation for building a system optimal model. We rewrite the DTE conditions as a variational inequality problem (VIP) and discuss the analytical properties of the formulation, including solution existence. A heuristic solution algorithm is developed to solve the VIP, which consists of three modules: a dynamic network loading procedure for mapping hyperpath flows onto the freight network, a column generation scheme for creating hyperpaths as needed, and a method of successive average for equilibrating profits on existing hyperpaths. The model and the solution algorithm are validated by numerical experiments constructed from empirical data collected in China. The results show that the DTE solutions outperform with wide margin the benchmark solutions that either ignore inter-truck interactions or operate trucks according to suboptimal routing and bidding decisions.
AB - This paper proposes a new hyperpath-based dynamic trucking equilibrium (DTE) assignment model. Unlike existing freight assignment models, we focus on the interactions between individual truck operators that solely compete for loads advertised on an online freight exchange. The competitors are assumed to follow optimal bidding and routing strategies - represented using a hyperpath - to maximize their expected profit. The proposed DTE model (1) predicts system-wide truck flows (including empty truck flows), (2) identifies efficiency improvements gained by network-wide visibility, and (3) lays the foundation for building a system optimal model. We rewrite the DTE conditions as a variational inequality problem (VIP) and discuss the analytical properties of the formulation, including solution existence. A heuristic solution algorithm is developed to solve the VIP, which consists of three modules: a dynamic network loading procedure for mapping hyperpath flows onto the freight network, a column generation scheme for creating hyperpaths as needed, and a method of successive average for equilibrating profits on existing hyperpaths. The model and the solution algorithm are validated by numerical experiments constructed from empirical data collected in China. The results show that the DTE solutions outperform with wide margin the benchmark solutions that either ignore inter-truck interactions or operate trucks according to suboptimal routing and bidding decisions.
KW - Dynamic trucking equilibrium
KW - Hyperpath
KW - Method of successive average
KW - Online freight exchange
KW - Variational inequality problem
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U2 - 10.1016/j.trpro.2019.05.018
DO - 10.1016/j.trpro.2019.05.018
M3 - Conference article
AN - SCOPUS:85074948529
VL - 38
SP - 320
EP - 340
JO - Transportation Research Procedia
JF - Transportation Research Procedia
SN - 2352-1457
T2 - 23rd International Symposium on Transportation and Traffic Theory, ISTTT 2019
Y2 - 24 July 2018 through 26 July 2018
ER -