Drayage Routing with Heterogeneous Fleet, Compatibility Constraints, and Truck Load Configurations. Bustos-Coral, D. & Costa, A. M. Transportation Research Part E: Logistics and Transportation Review, 168:102922, 2022. doi abstract bibtex This paper addresses drayage routing problems with heterogeneous fleets, compatibility constraints, and truck load configurations. In these problems, containers can be of any size and cargo category. In addition, compatibility and load configuration constraints define which and how many containers can be transported by each truck. We propose a state transition logic to model these constraints. Based on this logic, we develop two mixed-integer programming models for this family of problems. The first model is a compact formulation that can be input into a black-box solver. The second model combines partial routes in a space–time network and is solved with a tailored branch-and-cut approach. To analyze the efficiency of the proposed models, we conduct extensive computational tests on instances with different numbers of requests, geographical distributions of locations, time-window lengths, and fleet compositions. Moreover, we discuss how our modeling approach can assist decision-making in three different drayage routing applications.
@article{bustos-coral22drayagea,
title = {Drayage Routing with Heterogeneous Fleet, Compatibility Constraints, and Truck Load Configurations},
author = {{Bustos-Coral}, Daniel and Costa, Alysson M.},
year = {2022},
journal = {Transportation Research Part E: Logistics and Transportation Review},
volume = {168},
pages = {102922},
issn = {13665545},
doi = {10.1016/j.tre.2022.102922},
urldate = {2024-01-17},
abstract = {This paper addresses drayage routing problems with heterogeneous fleets, compatibility constraints, and truck load configurations. In these problems, containers can be of any size and cargo category. In addition, compatibility and load configuration constraints define which and how many containers can be transported by each truck. We propose a state transition logic to model these constraints. Based on this logic, we develop two mixed-integer programming models for this family of problems. The first model is a compact formulation that can be input into a black-box solver. The second model combines partial routes in a space--time network and is solved with a tailored branch-and-cut approach. To analyze the efficiency of the proposed models, we conduct extensive computational tests on instances with different numbers of requests, geographical distributions of locations, time-window lengths, and fleet compositions. Moreover, we discuss how our modeling approach can assist decision-making in three different drayage routing applications.},
langid = {english},
file = {/Users/acosta/Zotero/storage/AYKAP6EG/Bustos-Coral and Costa - 2022 - Drayage routing with heterogeneous fleet, compatib.pdf}
}
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