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Optimization of stochastic manufacturing systems using genetic algorithms

thesis
posted on 2004-01-01, 00:00 authored by Alexander Paul. Cave
Effective manufacturing control requires careful management of inventory, work in progress and customer service. Modelling of these complex probabilistic systems requires simulation although this excludes analytical approaches for the determination of optimal control policy. Genetic algorithms were used to address this problem and were shown to generate high quality solutions with constructive implications for industry.

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xv, 244 leaves ; 30 cm

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thesis

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thesis

Language

eng

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Thesis (Ph.D.)--Deakin University, Victoria, 2004.

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Ph.D.

Faculty

Faculty of Science

School

Engineering and Built Environment

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