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. / Thesis (PhDTransportSystemsEngineering)--University of South Australia, 2006.
| Identifer | oai:union.ndltd.org:ADTP/267203 |
| Creators | Pitaksringkarn, Ladda. |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
| Rights | copyright under review |
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