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Type: Thesis
Title: Evolutionary algorithms for supply chain optimisation.
Author: Ibrahimov, Maksud
Issue Date: 2012
School/Discipline: School of Computer Science
Abstract: Many real-world problems can be modelled as a combination of several interacting components. Methods based on Evolutionary Algorithms seem to be appropriate for handling such problems, but they have not been extensively researched in such domains. In this thesis we study the applicability of Evolutionary Algorithms for today’s high complexity real-world problems which consist of several interacting components. A natural source of such problems emerged from supply chain management problems which consist of several interacting components, and are also generally non-linear, heavily constrained, and involve many variables. We aim to study possible approaches for supply chain optimisation problems that seamlessly integrate algorithms addressing the local components, under the framework of global optimisation.
Advisor: Michalewicz, Zbigniew
Mohais, Arvind
Lakos, Charles Andrew
Dissertation Note: Thesis (Ph.D.) -- University of Adelaide, School of Computer Science, 2012
Keywords: evolutionary algorithms; supply chain optimisation; global optimisation
Appears in Collections:Research Theses

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