Cargo scheduling decision support for offshore oil and gas production: a case study
dc.contributor.author | Mardaneh, Elham | |
dc.contributor.author | Lin, Qun | |
dc.contributor.author | Loxton, Ryan | |
dc.contributor.author | Wilson, N. | |
dc.date.accessioned | 2017-04-28T13:59:51Z | |
dc.date.available | 2017-04-28T13:59:51Z | |
dc.date.created | 2017-04-28T09:06:07Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Mardaneh, E. and Lin, Q. and Loxton, R. and Wilson, N. 2017. Cargo scheduling decision support for offshore oil and gas production: a case study. Optimization and Engineering. 18 (4): pp. 991–1008. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/52760 | |
dc.identifier.doi | 10.1007/s11081-017-9348-3 | |
dc.description.abstract |
Woodside Energy Ltd (Woodside), Australia’s largest independent oil and gas company, operates multiple oil and gas facilities off the coast of Western Australia. These facilities require regular cargo shipments from supply vessels based in Karratha, Western Australia. In this paper, we describe a decision support model for scheduling the cargo shipments to minimize travel cost and trip duration, subject to various operational restrictions including vessel capacities, cargo demands at the facilities, time windows at the facilities, and base opening times. The model is a type of non-standard vehicle routing problem involving multiple supply vessels—a primary supply vessel that visits every facility during a round trip taking at most 1 week, and other supply vessels that are used on an ad hoc basis when the primary vessel cannot meet all cargo demands. We validate the model via test simulations using real data provided by Woodside. | |
dc.publisher | Springer New York LLC | |
dc.title | Cargo scheduling decision support for offshore oil and gas production: a case study | |
dc.type | Journal Article | |
dcterms.source.startPage | 1 | |
dcterms.source.endPage | 18 | |
dcterms.source.issn | 1389-4420 | |
dcterms.source.title | Optimization and Engineering | |
curtin.note |
The final publication is available at Springer via http://dx.doi.org/10.1007/s11081-017-9348-3 | |
curtin.department | Department of Mathematics and Statistics | |
curtin.accessStatus | Open access |