Increasing Fleet Utilization Through a Heuristic to Determine Optimal Backhaul Routes
As transportation costs rise, companies need to become more efficient to remain profitable. One way to increase efficiency in transportation is to increase fleet utilization through the addition of backhaul routes. Most truck routes consist of delivering from a distribution center to stores and then...
| Main Authors: | , |
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| Published: |
2019
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| Online Access: | https://hdl.handle.net/1721.1/121315 |
| _version_ | 1811080963327787008 |
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| author | Tahilyani, Geetika Venkatesh, Shrihari |
| author_facet | Tahilyani, Geetika Venkatesh, Shrihari |
| author_sort | Tahilyani, Geetika |
| collection | MIT |
| description | As transportation costs rise, companies need to become more efficient to remain profitable. One way to increase efficiency in transportation is to increase fleet utilization through the addition of backhaul routes. Most truck routes consist of delivering from a distribution center to stores and then returning to the distribution center empty. Backhaul routes are created when a truck delivers to the last store in the route and then picks up a delivery from a supplier to the distribution center. By adding backhauls to routes, trucks are driving fewer empty miles, and companies have to rely less on expensive third-party logistics providers to deliver material from suppliers to the distribution centers. Backhauls not only reduce operating costs but also result in a reduction in carbon emissions. In this capstone project, we developed a methodology for determining backhaul routes to be added to an established routing pattern. This methodology makes sure that all of the backhauls routes that are found are feasible solution by ensuring the total trip will be completed within 14 hours, which is a federal regulation for the amount of time a driver can be on the road. We then performed a sensitivity analysis to evaluate the robustness of the solutions to changes in the parameters. This sensitivity analysis helped identify the practical solutions that should first be implemented since these solutions have a higher chance of being successful. A case study was performed on Ahold Delhaize, one of the largest food retailers in the world, to evaluate the results from using this methodology. The analysis was performed on one of the operating entities of Ahold Delhaize, Food Lion. We were able to identify 18 feasible backhaul routes that could generate $320,000 in annual savings and reduce 166,800 pounds of CO2 emissions. When applied to the entire company, this could result in up to $1.6 million in annual savings and reduce CO2 emissions by 830,000 pounds. |
| first_indexed | 2024-09-23T11:39:37Z |
| id | mit-1721.1/121315 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T11:39:37Z |
| publishDate | 2019 |
| record_format | dspace |
| spelling | mit-1721.1/1213152019-06-20T03:02:46Z Increasing Fleet Utilization Through a Heuristic to Determine Optimal Backhaul Routes Tahilyani, Geetika Venkatesh, Shrihari Optimization Retail Transportation Environment As transportation costs rise, companies need to become more efficient to remain profitable. One way to increase efficiency in transportation is to increase fleet utilization through the addition of backhaul routes. Most truck routes consist of delivering from a distribution center to stores and then returning to the distribution center empty. Backhaul routes are created when a truck delivers to the last store in the route and then picks up a delivery from a supplier to the distribution center. By adding backhauls to routes, trucks are driving fewer empty miles, and companies have to rely less on expensive third-party logistics providers to deliver material from suppliers to the distribution centers. Backhauls not only reduce operating costs but also result in a reduction in carbon emissions. In this capstone project, we developed a methodology for determining backhaul routes to be added to an established routing pattern. This methodology makes sure that all of the backhauls routes that are found are feasible solution by ensuring the total trip will be completed within 14 hours, which is a federal regulation for the amount of time a driver can be on the road. We then performed a sensitivity analysis to evaluate the robustness of the solutions to changes in the parameters. This sensitivity analysis helped identify the practical solutions that should first be implemented since these solutions have a higher chance of being successful. A case study was performed on Ahold Delhaize, one of the largest food retailers in the world, to evaluate the results from using this methodology. The analysis was performed on one of the operating entities of Ahold Delhaize, Food Lion. We were able to identify 18 feasible backhaul routes that could generate $320,000 in annual savings and reduce 166,800 pounds of CO2 emissions. When applied to the entire company, this could result in up to $1.6 million in annual savings and reduce CO2 emissions by 830,000 pounds. 2019-06-17T15:05:43Z 2019-06-17T15:05:43Z 2019 https://hdl.handle.net/1721.1/121315 application/pdf |
| spellingShingle | Optimization Retail Transportation Environment Tahilyani, Geetika Venkatesh, Shrihari Increasing Fleet Utilization Through a Heuristic to Determine Optimal Backhaul Routes |
| title | Increasing Fleet Utilization Through a Heuristic to Determine Optimal Backhaul Routes |
| title_full | Increasing Fleet Utilization Through a Heuristic to Determine Optimal Backhaul Routes |
| title_fullStr | Increasing Fleet Utilization Through a Heuristic to Determine Optimal Backhaul Routes |
| title_full_unstemmed | Increasing Fleet Utilization Through a Heuristic to Determine Optimal Backhaul Routes |
| title_short | Increasing Fleet Utilization Through a Heuristic to Determine Optimal Backhaul Routes |
| title_sort | increasing fleet utilization through a heuristic to determine optimal backhaul routes |
| topic | Optimization Retail Transportation Environment |
| url | https://hdl.handle.net/1721.1/121315 |
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