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DC Field | Value | Language |
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dc.date.accessioned | 2022-04-18T08:24:53Z | - |
dc.date.available | 2022-04-18T08:24:53Z | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | Azzopardi, A. (2015). Optimizing scheduling in a pharmaceutical company (Bachelor's dissertation). | en_GB |
dc.identifier.uri | https://www.um.edu.mt/library/oar/handle/123456789/93900 | - |
dc.description | B.SC.(HONS)STATS.&OP.RESEARCH | en_GB |
dc.description.abstract | Scheduling is very important task which is used on a daily basis. A "good" schedule will increase the company's' profit and customers will be more willing to buy products as they are being satisfied in the shortest period of time. It is also important as it may solve many different objective functions such as minimization of makespan; minimization of delays; and minimization of total completion time. There has been an extensive research about algorithms to solve such problems. An overview of these algorithms both from a deterministic theoretical part and stochastic theoretical part is provided. This dissertation mainly focuses on solving the minimization of makespan on identical parallel machines scheduling problem. A mixed integer linear program (MILP) is built to solve this scheduling problem by using real live data from a local pharmaceutical company. In addition, the Longest Processing Time (LPT) heuristic algorithm which is one of the famous and oldest scheduling algorithms is used to compare its results with the MILP problem results and the original schedule by the company. | en_GB |
dc.language.iso | en | en_GB |
dc.rights | info:eu-repo/semantics/restrictedAccess | en_GB |
dc.subject | Computer algorithms | en_GB |
dc.subject | Integer programming | en_GB |
dc.subject | Computer scheduling | en_GB |
dc.title | Optimizing scheduling in a pharmaceutical company | en_GB |
dc.type | bachelorThesis | en_GB |
dc.rights.holder | The copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder. | en_GB |
dc.publisher.institution | University of Malta | en_GB |
dc.publisher.department | Faculty of Science. Department of Statistics and Operations Research | en_GB |
dc.description.reviewed | N/A | en_GB |
dc.contributor.creator | Azzopardi, Annalise (2015) | - |
Appears in Collections: | Dissertations - FacSci - 2015 Dissertations - FacSciSOR - 2015 |
Files in This Item:
File | Description | Size | Format | |
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BSCSTATS_OPRESEARCH_Azzopardi_Annalise_2015.pdf Restricted Access | 7.63 MB | Adobe PDF | View/Open Request a copy |
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