Logistics modelling: agricultural facility location analysis  /

dc.contributor.author	Pitaksringkarn, Ladda.
dc.contributor.school	University of South Australia.
dc.date.issued	2006
dc.description.abstract	Decisions on facility location play a vital role in the planning stage of a supply chain because a facility configuration provides a form, and structure for the supply chain, after which activity interaction between among supply chain members can be established. An optimal facility set can provide best operating performance of the supply chain. This research applied a Genetic Algorithm (GA) scheme for modelling a facility location problem for an agricultural supply chain. As a grouping problem, the research aim is to group production nodes into groups and then define group centroids as a facility (e.g. gran storage). Grouping genetic algorithm (GGA) is then specifically introduced to solve the problem because of the special characteristics of GGA in solving a grouping problem.
dc.description.dissertation	Thesis (PhDTransportSystemsEngineering)--University of South Australia, 2006.
dc.identifier.uri	https://hdl.handle.net/1959.8/80343
dc.language.iso	en
dc.subject.lcsh	Business logistics
dc.subject.lcsh	Business networks.
dc.title	Logistics modelling: agricultural facility location analysis /
dc.type	thesis
dcterms.accessRights	506 0#$fstar $2Unrestricted online access
ror.fileinfo	12146719360001831 13146706630001831 9915960408301831_53112396180001831.pdf
ror.mmsid	9915960408301831

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