Evolutionary Algorithms to Solve Agricultural Routing Planning
This doctoral thesis aims to develop effective Evolutionary Algorithms that can be competitively applied to Agricultural Routing Planning (ARP) and to formulate an extension of the ARP. The outcomes of this research will impact on the research community with the development of new algorithms as well...
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| Format: | Thesis |
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Curtin University
2020
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| Online Access: | http://hdl.handle.net/20.500.11937/82468 |
| _version_ | 1848764512758398976 |
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| author | Utamima, Amalia |
| author_facet | Utamima, Amalia |
| author_sort | Utamima, Amalia |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This doctoral thesis aims to develop effective Evolutionary Algorithms that can be competitively applied to Agricultural Routing Planning (ARP) and to formulate an extension of the ARP. The outcomes of this research will impact on the research community with the development of new algorithms as well as the dissemination of findings. This study is significant as it is expected to improve the management of agricultural machinery, to minimise the total cost and the settling time for completing field operations, and to produce better routing plans. |
| first_indexed | 2025-11-14T11:20:32Z |
| format | Thesis |
| id | curtin-20.500.11937-82468 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:20:32Z |
| publishDate | 2020 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-824682023-01-30T01:03:33Z Evolutionary Algorithms to Solve Agricultural Routing Planning Utamima, Amalia This doctoral thesis aims to develop effective Evolutionary Algorithms that can be competitively applied to Agricultural Routing Planning (ARP) and to formulate an extension of the ARP. The outcomes of this research will impact on the research community with the development of new algorithms as well as the dissemination of findings. This study is significant as it is expected to improve the management of agricultural machinery, to minimise the total cost and the settling time for completing field operations, and to produce better routing plans. 2020 Thesis http://hdl.handle.net/20.500.11937/82468 Curtin University fulltext |
| spellingShingle | Utamima, Amalia Evolutionary Algorithms to Solve Agricultural Routing Planning |
| title | Evolutionary Algorithms to Solve Agricultural Routing Planning |
| title_full | Evolutionary Algorithms to Solve Agricultural Routing Planning |
| title_fullStr | Evolutionary Algorithms to Solve Agricultural Routing Planning |
| title_full_unstemmed | Evolutionary Algorithms to Solve Agricultural Routing Planning |
| title_short | Evolutionary Algorithms to Solve Agricultural Routing Planning |
| title_sort | evolutionary algorithms to solve agricultural routing planning |
| url | http://hdl.handle.net/20.500.11937/82468 |