Vessel routing with pickups and deliveries: An application to the supply of offshore oil platforms

Eirik Fernández Cuesta, Henrik Andersson, Kjetil Fagerholt, Gilbert Laporte

Research output: Contribution to journalArticlepeer-review

34 Citations (SciVal)

Abstract

This paper presents a new routing problem, the Vessel Routing Problem with Selective Pickups and Deliveries (VRPSPD), an extension of existing pickup and delivery problems that arises in the planning of logistics operations in the offshore oil and gas industry. The VRPSPD is a single-vessel model that can lead to significant economic improvements to the current planning scheme without having a very large impact on the operations. In addition, we formulate a Multi-Vessel Routing Problem with Pickups and Deliveries (mVRPPD) that leads to even larger economical gains, but also entails more important changes in the current planning and operations. To quantify and justify the benefits of the VRPSPD and mVRPPD, an industry case based on real data was constructed and solved for 300 days. The VRPSPD is solvable with a commercial solver for most real-size instances. However, for the mVRPPD on the largest instances, it was necessary to develop a state-of-the-art adaptive large neighborhood heuristic search to reduce computational time.

Original languageEnglish
Pages (from-to)140-147
Number of pages8
JournalComputers and Operations Research
Volume79
DOIs
Publication statusPublished - 1 Mar 2017

Funding

This research is funded and carried out as part of the Center for Integrated Operations in the Petroleum Industry and by the Canadian National Sciences and Engineering Research Council under grant 2015-06189 . This support is gratefully acknowledged. We would also like to express our gratitude to the reviewers for their valuable comments.

Keywords

  • Offshore supply
  • One-to-many-to-one
  • Pickup and delivery problem
  • Selective pickup and selective delivery
  • Vehicle routing

ASJC Scopus subject areas

  • General Computer Science
  • Modelling and Simulation
  • Management Science and Operations Research

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