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dc.contributor.authorUtamima, Amalia
dc.contributor.supervisorTorsten Reinersen_US
dc.contributor.supervisorAmir Hossein Ansaripooren_US
dc.date.accessioned2021-01-29T06:17:52Z
dc.date.available2021-01-29T06:17:52Z
dc.date.issued2020en_US
dc.identifier.urihttp://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.publisherCurtin Universityen_US
dc.titleEvolutionary Algorithms to Solve Agricultural Routing Planningen_US
dc.typeThesisen_US
dcterms.educationLevelPhDen_US
curtin.departmentSchool of Managementen_US
curtin.accessStatusOpen accessen_US
curtin.facultyBusiness and Lawen_US
curtin.contributor.orcidUtamima, Amalia [0000-0001-8203-4148]en_US


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