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A simulation-based multi-objective optimization study of the fleet sizing problem in the offshore industry
Industrial Engineering Department, School of Engineering, Tarbiat Modares University, Tehran, Iran.ORCID iD: 0000-0002-5515-9399
Industrial Engineering Department, School of Engineering, Tarbiat Modares University, Tehran, Iran.ORCID iD: 0000-0002-3810-5313
2016 (English)In: Maritime Economics & Logistics, ISSN 1479-2931, E-ISSN 1479-294X, Vol. 18, no 4, p. 436-457Article in journal (Refereed) Published
Abstract [en]

Oil companies usually hire a number of offshore supply vessels (OSVs) under long-term contracts for offshore supply logistics. If the number of long-term chartered vessels is not sufficient to satisfy platform demands, one or more OSVs would be required under short-term contracts. In this article two policies for OSV routing to installations are compared: routing based on a fixed schedule, currently used in Iranian offshore oil company and routing based on platform demands. A discrete-event simulation model is developed and simulation-based optimization is used to find near-optimal fleet size and composition that minimize expected total cost subject to a minimum desired expected platform service level. Changing the platform service level constraint allows results to be obtained for multiple best compromise solutions along a performance trade-off curve. For each routing policy, an optimal trade-off curve is obtained using simulation-based optimization. Performance evaluation of routing policies is compared at different service levels. Experimental results indicate that the routing based on platform demands dominates the routing based on a fixed schedule under near-optimal decision variable settings. 

Place, publisher, year, edition, pages
Springer Nature, 2016. Vol. 18, no 4, p. 436-457
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:his:diva-23651DOI: 10.1057/mel.2015.21ISI: 000388094600005Scopus ID: 2-s2.0-85053861729OAI: oai:DiVA.org:his-23651DiVA, id: diva2:1843400
Note

© 2016 Macmillan Publishers Ltd.

Available from: 2024-03-10 Created: 2024-03-10 Last updated: 2024-03-13Bibliographically approved

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Mahmoodi, Ehsan

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