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3885. Integrated optimization of operations and capacity strategy for drayage procurement in first-mile & LCL container logistics

Invited abstract in session WB-6: Advancements of OR-analytics in statistics, machine learning and data science 17, stream Advancements of OR-analytics in statistics, machine learning and data science.

Wednesday, 10:30-12:00
Room: 1013 (building: 202)

Authors (first author is the speaker)

1. George Vassos
Department of Technology, Management and Economics Operations Research, Technical University of Denmark

Abstract

Integrated container logistics rely on efficient management of first-mile and less-than-container-load (LCL) processes, particularly in drayage, which involves the short-distance movement of full container loads to consolidation centers or for modality changes. Given that shipping companies often engage external carriers for drayage operations, effective drayage procurement becomes crucial. This study introduces a dynamic programming approach to tackle the drayage procurement problem, integrating capacity planning optimization to devise a reservation plan that maximizes operational value. The scalability of the proposed algorithm is assessed, with an extension to a model-free approach inspired by advancements in artificial intelligence aimed at mitigating computational burdens associated with executing the dynamic program for evaluating capacity plans. Execution times and optimality gaps between exhaustive and approximate dynamic programming methods are compared on small instances of the problem. Furthermore, the scalability of the approximate method to larger instances is demonstrated. Additionally, a parameterization of carrier capacities is proposed to further reduce the complexity of capacity optimization programming with minimal losses in optimality.

Keywords

Status: accepted

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