Optimisation models for Transportation Network Design under Uncertainty:a literature review

TL;DR

This literature review examines optimization models for transportation network design under uncertainty, highlighting mathematical and geometrical approaches to improve supply chain resilience and performance.

Contribution

It categorizes existing models into mathematical and geometrical approaches, providing a comprehensive overview of methods addressing uncertainty in transportation network design.

Findings

Models address facility location, routing, and zoning under uncertainty

Mathematical and geometrical approaches are key in current models

Uncertainty significantly impacts transportation network optimization

Abstract

Supply chain network is critical to serving customers, so the most common practices are to determine the number, location, and capacity of facilities. But at the same time, uncertainties and risks must be taken into account in order to control delays. In this context, many optimisation models have been developed to use the results in transportation network and therefore improve the supply chain performance. Models were developed in both routing and zoning/districting problems, and different cases have been discussed in the literature, such as facility location problems, urban problems, and transportation problems. This paper seeks to review the literature in this area and decompose the models into Mathematical modelling and Geometrical approaches. Distribution is an important part of the supply chain management, it is a process with multiple participants. This characteristic brings a high level of uncertainty. This article therefore presents the distribution process and in particular the design of the transportation network which can include both routing and districting problems.