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Book Sections Year : 2016

A Revenue Management Approach for Network Capacity Allocation of an Intermodal Barge Transportation System

Abstract

We propose a revenue management (RM) model for the network capacity allocation problem of an intermodal barge transportation system. Accept/reject decisions are made based on a probabilistic mixed integer optimization model maximizing the expected revenue of the carrier over a given time horizon. Probability distribution functions are used to characterize future potential demands. The simulated booking system solves, using a commercial software, the capacity allocation problem for each new transportation request. A conventional model for dynamic capacity allocation considering only the available network capacity and the delivery time constraints is used as alternative when analyzing the results of the proposed model.
We propose a revenue management (RM) model for the network capacity allocation problem of an intermodal barge transportation system. Accept/reject decisions are made based on a probabilistic mixed integer optimization model maximizing the expected revenue of the carrier over a given time horizon. Probability distribution functions are used to characterize future potential demands. The simulated booking system solves, using a commercial software, the capacity allocation problem for each new transportation request. A conventional model for dynamic capacity allocation considering only the available network capacity and the delivery time constraints is used as alternative when analyzing the results of the proposed model.
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Dates and versions

hal-03379053 , version 1 (14-10-2021)

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Yunfei Wang, Ioana Bilegan, Teodor Gabriel Crainic, Abdelhakim Artiba. A Revenue Management Approach for Network Capacity Allocation of an Intermodal Barge Transportation System. Computational Logistics, 9855, Springer International Publishing, pp.243-257, 2016, Lecture Notes in Computer Science, ⟨10.1007/978-3-319-44896-1_16⟩. ⟨hal-03379053⟩
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