Forwarding containers to dry ports in congested logistic networks

This work investigates the impact of container arrival flow rate on the port surrounding network and proposes a mixed integer programming model to optimize their forwarding towards dry port destinations. A novel efficient model with limited network capacity and time period dependent travel cost func...

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Bibliographic Details
Main Authors: Anna Sciomachen, Giuseppe Stecca
Format: Article
Language:English
Published: Elsevier 2023-07-01
Series:Transportation Research Interdisciplinary Perspectives
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2590198223000933
Description
Summary:This work investigates the impact of container arrival flow rate on the port surrounding network and proposes a mixed integer programming model to optimize their forwarding towards dry port destinations. A novel efficient model with limited network capacity and time period dependent travel cost function is proposed. The aim is to give a decision support for operational planning with limited capacity of both the terminal yard and the logistic network, with respect to the quantity of containers transferred per time unit. The model considers time dependent costs and traveling times to reduce congestion. As a further novel issue of the model, arc costs and traveling times change during specific time slots. More precisely, new linear functions are derived as tangents to the nonlinear convex components of a classical traveling time function proposed in the literature. The aim is to produce a light model which can be effectively used for macro planning of forwarding operations. The model is proved to be fast in real case instances also if compared to classical literature approaches. The model is used to study the container dispatching process in a terminal which is going to be the main Italian container terminal equipped to manage mega-ship traffic. Results obtained from real-size instances are reported. We tested the behavior of the model under different scenarios. Our tests confirmed model efficiency and its of supporting the management of peak events also by controlling shut-down time slots to lower congestion.
ISSN:2590-1982