Evolutionary Algorithms to Solve Agricultural Routing Planning
dc.contributor.author | Utamima, Amalia | |
dc.contributor.supervisor | Torsten Reiners | en_US |
dc.contributor.supervisor | Amir Hossein Ansaripoor | en_US |
dc.date.accessioned | 2021-01-29T06:17:52Z | |
dc.date.available | 2021-01-29T06:17:52Z | |
dc.date.issued | 2020 | en_US |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/82468 | |
dc.description.abstract |
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. | en_US |
dc.publisher | Curtin University | en_US |
dc.title | Evolutionary Algorithms to Solve Agricultural Routing Planning | en_US |
dc.type | Thesis | en_US |
dcterms.educationLevel | PhD | en_US |
curtin.department | School of Management | en_US |
curtin.accessStatus | Open access | en_US |
curtin.faculty | Business and Law | en_US |
curtin.contributor.orcid | Utamima, Amalia [0000-0001-8203-4148] | en_US |