Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
Resource scheduling algorithm for maintenance planning
Mini Dissertation (B Eng. (Industrial and Systems Engineering))--University of Pretoria, 2017.
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English English |
| Published: |
University of Pretoria. Faculty of Engineering, Built Environment and Information Technology. Dept. of Industrial and Systems Engineering
2019
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| _version_ | 1867613627980185600 |
|---|---|
| access_status_str | Open Access |
| author | Young, Kirsten |
| author_browse | Young, Kirsten |
| author_facet | Young, Kirsten |
| author_sort | Young, Kirsten |
| collection | Thesis |
| dc_rights_str_mv | © 2017 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Mini Dissertation (B Eng. (Industrial and Systems Engineering))--University of Pretoria, 2017. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/68399 |
| institution | University of Pretoria (South Africa) |
| language | English English |
| last_indexed | 2026-06-10T12:39:09.918Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | University of Pretoria. Faculty of Engineering, Built Environment and Information Technology. Dept. of Industrial and Systems Engineering |
| publisherStr | University of Pretoria. Faculty of Engineering, Built Environment and Information Technology. Dept. of Industrial and Systems Engineering |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/68399 Resource scheduling algorithm for maintenance planning Young, Kirsten Mini-dissertations (Industrial and Systems Engineering) Mini Dissertation (B Eng. (Industrial and Systems Engineering))--University of Pretoria, 2017. “Company XYZ” is a company which outsources maintenance to various enterprises all over South Africa. Technicians are hired to travel to their customers which are geographically far from one another to perform maintenance on electrical devices such as servers, computers and air conditioners. An employee’s workday consists of both their travel time and working time and so routing must be carefully considered in order to reduce travel costs. Company XYZ’s employees find that their workloads are unbalanced i.e. some days they will work much longer hours than others. This has led to Company XYZ requiring a way to efficiently schedule their employees so that customers demand can be met, while keeping costs low, resource utilization high and workloads balanced. Fourier-E attempted solving Company XYZ’s problem by creating a linear programming resource allocation model. The model worked but there is still much room for improvement. All the data was therefore already available in a device database which could be used in the development of a new solution. After performing a literature study it was found that the problem at hand has many similar aspects to that of a Multiple Travelling Salesman Problem and so the many methods of solving this kind of problem were researched. The genetic algorithm was selected as the most suitable algorithm for solving the problem because of its short running time and the student’s ability to code it. Specific selection, crossover and mutation techniques were used to evolve the initial population of solutions. With every new generation, a better schedule was found. The best solution of the final generation was selected as the schedule to analyse. The genetic algorithm exhibited many advantages over using the existing linear programming method. The chosen schedule significantly reduced overtime, reduced travel distances and balanced resource workloads. It is up to the company to decide whether they should implement it or not. Company XYZ should validate the final schedule by using a testing team to ensure that the assumptions on which the model was based are acceptable. 2019-02-04T13:19:01Z 2019-02-04T13:19:01Z 2019 2017 Mini Dissertation http://hdl.handle.net/2263/68399 en en © 2017 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. PDF application/pdf University of Pretoria. Faculty of Engineering, Built Environment and Information Technology. Dept. of Industrial and Systems Engineering |
| spellingShingle | Mini-dissertations (Industrial and Systems Engineering) Young, Kirsten Resource scheduling algorithm for maintenance planning |
| title | Resource scheduling algorithm for maintenance planning |
| title_full | Resource scheduling algorithm for maintenance planning |
| title_fullStr | Resource scheduling algorithm for maintenance planning |
| title_full_unstemmed | Resource scheduling algorithm for maintenance planning |
| title_short | Resource scheduling algorithm for maintenance planning |
| title_sort | resource scheduling algorithm for maintenance planning |
| topic | Mini-dissertations (Industrial and Systems Engineering) |
| url | http://hdl.handle.net/2263/68399 |
| work_keys_str_mv | AT youngkirsten resourceschedulingalgorithmformaintenanceplanning |