Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.636353
Title: Computer aided scheduling
Author: Das, D.
Awarding Body: University College of Swansea
Current Institution: Swansea University
Date of Award: 1979
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Abstract:
The so called Job-Shop type scheduling situation, where a large number of jobs with few activities per job, queue for resources, arises in many different environments. The combinatorial nature of the scheduling problem makes it difficult, if not impossible to determine the 'Optimum Schedule' or the schedule which meets the objectives of the organisation most nearly. 'Heuristic Scheduling rules' have been accepted as fairly cheap methods of obtaining a 'near optimum schedule'. However, the performance of these rules under different shop loading conditions has not been fully tested. After studying several practical scheduling situations an approach is suggested which enables the study of the effect of loading conditions when various heuristic rules are applied. The model is such that it can, given certain assumptions, be used to study a wide variety of scheduling situations and compare their merits in meeting various objectives. A major assumption made was that the jobs requiring scheduling had a similar network pattern. This was tested and found to be the case in many practical situations and allowed a detailed study of the loading conditions in a particular company. The results show that loading conditions do play a considerable part in determining the 'better' scheduling rules to apply. Both the 'static' case with a given job set, and the 'dynamic' case with jobs arriving during the scheduling period are studied for both 'manual' and 'computer aided' scheduling rules. The graphical representation of results in the form of 'performance charts' for the simulation runs makes comparison of their characteristics readily assimilated.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.636353  DOI: Not available
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