Abstract

We consider a combined fleet deployment and inventory management problem in Roll-on Roll-off shipping. Along given trade routes there are ports with inventories that should be kept within their limits. Current planning practice is to visit all ports every time a trade route is serviced. We instead aim at determining the sailing routes of each voyage along the trade route, where some ports can be skipped on certain voyages. A novel mixed integer programming model is proposed and tested on realistic instances. The results indicate that substantial gains can be achieved from this more flexible way of planning.

Highlights

  • Liner shipping is one of the major transportation modes in maritime transportation and has similarities with a bus service where the ships service a given set of voyages along trades according to a published schedule

  • One important assumption in the models proposed by Chandra et al (2016) and Dong et al (2017), is that even though inventory management is integrated in the fleet deployment planning, one still requires that all ports along the trade routes are visited on each voyage

  • We have in this paper considered a combined fleet deployment and inventory management problem (FDIMP) emerging in Roll-on Roll-off (Ro-Ro) shipping

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Summary

Introduction

Liner shipping is one of the major transportation modes in maritime transportation and has similarities with a bus service where the ships service a given set of voyages along trades according to a published schedule. One important assumption in the models proposed by Chandra et al (2016) and Dong et al (2017), is that even though inventory management is integrated in the fleet deployment planning, one still requires that all ports along the trade routes are visited on each voyage. Despite that this represents the current practice, it may impose an unnecessary restriction in Ro-Ro shipping. This issue was discussed for the first time in Christiansen (1999)

Model formulation
Model with port choice flexibility
Objective function min
Routing constraints x
Scheduling constraints tim
Linearization
Preprocessing
Computational study
Test instance generation
Computational results
Comparison with the base model
The effects of the inventory limits
Findings
Conclusion
Full Text
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