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Dynamic optimization of job distribution on machine tools using time decomposition into constant job-mix stages

This thesis deals with the development, analysis and application of a new method to optimize the allocation of jobs on machine tools. The benefits of this method are derived through time-decomposition of the scheduling horizon. / The decomposition scheme is based on the scheduled flow of jobs i.e., the input of jobs to the shop floor and their departure after processing. The partitioning procedure divides the planning horizon into 'stages', or time periods, at which the job-mix remains constant. The optimization of job allocation is carried out within each partition and successive stages are treated sequentially. The dynamic nature of the problem is such that the solution at a stage affects the boundary conditions of the subsequent stage. The Constant Job-Mix Stage (CMS) algorithm developed to solve the job allocation problem, accounts of the setup times and enables one to obtain integer solutions while reducing slack on machines and enforcing due date on jobs. / The application of the algorithm is demonstrated for three different cases. The first two cases focus on single operation jobs and represent two different approaches to scheduling. The third case deals with the assignment of multiple operation jobs to machine tools which are grouped according to processes.

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.60709
Date January 1992
CreatorsNatarajan, Subramanian
PublisherMcGill University
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
LanguageEnglish
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Formatapplication/pdf
CoverageMaster of Engineering (Department of Electrical Engineering.)
RightsAll items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated.
Relationalephsysno: 001284840, proquestno: AAIMM74560, Theses scanned by UMI/ProQuest.

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