Please use this identifier to cite or link to this item:
Scopus Web of Science® Altmetric
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSchellenberg, S.-
dc.contributor.authorMohais, A.-
dc.contributor.authorIbrahimov, M.-
dc.contributor.authorWagner, N.-
dc.contributor.authorMichalewicz, Z.-
dc.contributor.editorChiong, R.-
dc.contributor.editorWeise, T.-
dc.contributor.editorMichalewicz, Z.-
dc.identifier.citationVariants of Evolutionary Algorithms for Real-World Applications, 2012 / Chiong, R., Weise, T., Michalewicz, Z. (ed./s), vol.9783642234248, pp.143-166-
dc.description.abstractThis chapter deals with the problem of balancing and optimising the multi-echelon supply chain network of an Australian ASX Top 50 company which specialises in the area of manufacturing agricultural chemicals. It takes into account sourcing of raw material, the processing of material, and the distribution of the final product. The difficulty of meeting order demand and balancing the plants’ utilisation while adhering to capacity constraints is addressed as well as the distribution and transportation of the intermediate and final products. The aim of the presented system is to minimise the time it takes to generate a factory plan while providing better accuracy and visibility of the material flow within the supply chain. The generation of factory plans within a short period of time allows for what-if-scenario analysis and strategic planning which would not have been possible otherwise. We present two approaches that drive a simulation to determine the quality of the generated solutions: an event-based approach and a fuzzy rule-based approach. While both of them are able to generate valid plans, the rule-based approach substantially outperforms the event-based one with respect to convergence time and quality of the solution.-
dc.description.statementofresponsibilitySven Schellenberg, Arvind Mohais, Maksud Ibrahimov, Neal Wagner and Zbigniew Michalewicz-
dc.titleA Fuzzy-Evolutionary Approach to the Problem of Optimisation and Decision-Support in Supply Chain Networks-
dc.typeBook chapter-
Appears in Collections:Aurora harvest
Computer Science publications

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.