Optimizing Fleet Utilization by Adjusting Customer Delivery Appointment Times
The supply of trucks and drivers is struggling to keep up with the increasing and volatile demand for ground transportation. As a result, for companies like Niagara Bottling LLC., supply chain managers are pressured to optimize their logistics networks. Niagara Bottling is projected to deliver over...
| Main Authors: | , |
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| Format: | Other |
| Language: | en_US |
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2020
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| Online Access: | https://hdl.handle.net/1721.1/126382 |
| _version_ | 1826198170417233920 |
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| author | Copley, Colleen Lu, Charles |
| author_facet | Copley, Colleen Lu, Charles |
| author_sort | Copley, Colleen |
| collection | MIT |
| description | The supply of trucks and drivers is struggling to keep up with the increasing and volatile demand for ground transportation. As a result, for companies like Niagara Bottling LLC., supply chain managers are pressured to optimize their logistics networks. Niagara Bottling is projected to deliver over 1 million full truckloads of bottled beverages to customers across North America in 2020 and transportation costs are already their second highest contributor to Cost of Goods Sold (COGS). Currently, Niagara’s customers have overlapping delivery window requirements which cause significant fluctuations in delivery volumes throughout the day. Niagara hypothesizes that if these delivery appointments were more evenly distributed throughout the day, the same number of loads could be delivered with fewer trucks and therefore less cost. A heuristic algorithm is created to maximize fleet utilization by modifying these delivery appointment windows so that multiple scenarios can be compared based on fleet utilization and cost savings metrics. This paper will further articulate the methodology and assumptions used to generate these scenarios and provide context to the recommendations for utilization improvement on Niagara’s logistics network. Regions with high customer mix saw increases in utilization as high as 25% and decreases in cost as high as 45%. Regions with high delivery volumes saw increases of utilization as high as 13% and decreases in cost as high as 18%. |
| first_indexed | 2024-09-23T11:00:17Z |
| format | Other |
| id | mit-1721.1/126382 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T11:00:17Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | mit-1721.1/1263822020-07-31T09:53:23Z Optimizing Fleet Utilization by Adjusting Customer Delivery Appointment Times Copley, Colleen Lu, Charles Transportation Network Design Supply Chain Strategy The supply of trucks and drivers is struggling to keep up with the increasing and volatile demand for ground transportation. As a result, for companies like Niagara Bottling LLC., supply chain managers are pressured to optimize their logistics networks. Niagara Bottling is projected to deliver over 1 million full truckloads of bottled beverages to customers across North America in 2020 and transportation costs are already their second highest contributor to Cost of Goods Sold (COGS). Currently, Niagara’s customers have overlapping delivery window requirements which cause significant fluctuations in delivery volumes throughout the day. Niagara hypothesizes that if these delivery appointments were more evenly distributed throughout the day, the same number of loads could be delivered with fewer trucks and therefore less cost. A heuristic algorithm is created to maximize fleet utilization by modifying these delivery appointment windows so that multiple scenarios can be compared based on fleet utilization and cost savings metrics. This paper will further articulate the methodology and assumptions used to generate these scenarios and provide context to the recommendations for utilization improvement on Niagara’s logistics network. Regions with high customer mix saw increases in utilization as high as 25% and decreases in cost as high as 45%. Regions with high delivery volumes saw increases of utilization as high as 13% and decreases in cost as high as 18%. 2020-07-24T18:21:47Z 2020-07-24T18:21:47Z 2020-07-24 Other https://hdl.handle.net/1721.1/126382 en_US application/pdf |
| spellingShingle | Transportation Network Design Supply Chain Strategy Copley, Colleen Lu, Charles Optimizing Fleet Utilization by Adjusting Customer Delivery Appointment Times |
| title | Optimizing Fleet Utilization by Adjusting Customer Delivery Appointment Times |
| title_full | Optimizing Fleet Utilization by Adjusting Customer Delivery Appointment Times |
| title_fullStr | Optimizing Fleet Utilization by Adjusting Customer Delivery Appointment Times |
| title_full_unstemmed | Optimizing Fleet Utilization by Adjusting Customer Delivery Appointment Times |
| title_short | Optimizing Fleet Utilization by Adjusting Customer Delivery Appointment Times |
| title_sort | optimizing fleet utilization by adjusting customer delivery appointment times |
| topic | Transportation Network Design Supply Chain Strategy |
| url | https://hdl.handle.net/1721.1/126382 |
| work_keys_str_mv | AT copleycolleen optimizingfleetutilizationbyadjustingcustomerdeliveryappointmenttimes AT lucharles optimizingfleetutilizationbyadjustingcustomerdeliveryappointmenttimes |