Please use this identifier to cite or link to this item: https://doi.org/10.1080/00207543.2010.527388
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dc.titleAggregate production planning for shipbuilding with variation-inventory trade-offs
dc.contributor.authorLiu, Z.
dc.contributor.authorChua, D.K.H.
dc.contributor.authorYeoh, K.-W.
dc.date.accessioned2014-06-17T05:28:42Z
dc.date.available2014-06-17T05:28:42Z
dc.date.issued2011-10-15
dc.identifier.citationLiu, Z., Chua, D.K.H., Yeoh, K.-W. (2011-10-15). Aggregate production planning for shipbuilding with variation-inventory trade-offs. International Journal of Production Research 49 (20) : 6249-6272. ScholarBank@NUS Repository. https://doi.org/10.1080/00207543.2010.527388
dc.identifier.issn00207543
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/58938
dc.description.abstractShipbuilding is a complex production system characterised by a complicated work and organisation structure, prolonged production lead time, and heterogeneous resource requirements. Thus, effectively planning all involved activities presents a challenging task and requires the timely coordination between the successive production stages at the plant level and effective resource allocation at the workshop level. With the work breakdown structure of all projects and their corresponding building strategies, the aggregate production planning (APP) is to address two important issues, namely, workforce level and inventory usage so that the fluctuating demands from downstream processes can be satisfied in a cost-effective manner. To achieve this, a novel APP model is proposed for ship production to minimise the variation of aggregate man-hour over the planning horizon and simultaneously minimise the logistic demands of the interim products. In view of the combinatorial nature and computational complexity, a directed genetic algorithm based solver has been developed to solve the two-conflicting-objective optimisation problem. The proposed approach has been applied to a case study and preliminary results have shown certain effectiveness in handling various situations with different planning strategies. © 2011 Taylor & Francis.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1080/00207543.2010.527388
dc.sourceScopus
dc.subjectaggregate production planning
dc.subjectgenetic algorithm
dc.subjectmulti-objective optimisation
dc.subjectshipbuilding
dc.typeArticle
dc.contributor.departmentCIVIL & ENVIRONMENTAL ENGINEERING
dc.description.doi10.1080/00207543.2010.527388
dc.description.sourcetitleInternational Journal of Production Research
dc.description.volume49
dc.description.issue20
dc.description.page6249-6272
dc.description.codenIJPRB
dc.identifier.isiut000299896000014
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