Publication
Using districting and a data driven TSP to improve last mile delivery
| dc.contributor.advisor | Ramos, António José Galrão | |
| dc.contributor.author | Santos, Beatriz Barbosa dos | |
| dc.date.accessioned | 2023-11-09T12:37:34Z | |
| dc.date.available | 2024-10-10T00:31:06Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | This dissertation considers how a parcel delivery company can improve last mile delivery services’ performance using historical data. To tackle this challenge, we start by proposing a framework for data cleaning, in order to produce reliable data for vehicle routing problems. Data on the historical geographical location of clients is used to model a hierarchical districting problem, mid-level districts (named micro districts) are limited to an eight hour shift, representing a daily route. Using the districting solution as a procedure for package to driver/vehicle assignment, it is possible to achieve a 14% decrease in the number of vehicles needed, while keeping daily routes more balanced in terms of working times. Using a transition probabilities based TSP to sequence nano zones (the lower-level districts), the preferences of drivers are used as a cost function. The transition probabilities based TSP produces solutions with a total distance 12% higher, comparing with a distance based TSP. Moreover, sequencing the nano zones using the maximum likelihood routing enables the incorporation of the driver’s tacit knowledge. | pt_PT |
| dc.identifier.tid | 203380304 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.22/23877 | |
| dc.language.iso | eng | pt_PT |
| dc.subject | Districting | pt_PT |
| dc.subject | Data Driven | pt_PT |
| dc.subject | TSP | pt_PT |
| dc.subject | Maximum Likelihood Routing | pt_PT |
| dc.title | Using districting and a data driven TSP to improve last mile delivery | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | Mestrado em Engenharia e Gestão Industrial | pt_PT |