Vehicle routing and capacity decision models applicable to third party logistics providers
The importance of the logistics industry globally has risen in tandem with the expansion of global commerce and manufacturing. There is an increasing need to engage the services of third party logistics (3PL) service providers to aid in the rapid penetration of new markets and responsive order fulfi...
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| Format: | Thesis |
| Language: | English |
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2014
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| Online Access: | http://hdl.handle.net/10356/60542 |
| _version_ | 1811679043457646592 |
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| author | Wang, Ricardo Huan Ran |
| author2 | Yue Chee Yoon |
| author_facet | Yue Chee Yoon Wang, Ricardo Huan Ran |
| author_sort | Wang, Ricardo Huan Ran |
| collection | NTU |
| description | The importance of the logistics industry globally has risen in tandem with the expansion of global commerce and manufacturing. There is an increasing need to engage the services of third party logistics (3PL) service providers to aid in the rapid penetration of new markets and responsive order fulfillment. Consequently, 3PL firms have to acquire and expand service offerings and physical infrastructure to remain relevant. In such a highly competitive environment, 3PL firms need to improve asset utilization, especially of revenue generating asset classes of vehicle fleet and warehouses, to maintain price competitiveness and operational efficiency. In view of the lack of relevant models in this young and growing industry, we provide the practitioners a review of models in other industries, especially manufacturing, that are relevant and similar in operations of fleet management. Using this as a guide, the practitioner can identify models particularly suited to the unique challenges of his own 3PL operations and suggest improvements to his own algorithms. We also provide a simple yet efficient heuristic that aids the practitioner in the consolidation of warehousing operations to obtain cost economies and other indirect qualitative benefits of customer responsiveness and flexibility. Using the algorithm, the practitioner is able to decide which warehouses to consolidate to achieve maximum leasing and operational cost savings in an expedient manner, while taking into account early termination penalties and relocation costs. |
| first_indexed | 2024-10-01T03:02:53Z |
| format | Thesis |
| id | ntu-10356/60542 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:02:53Z |
| publishDate | 2014 |
| record_format | dspace |
| spelling | ntu-10356/605422020-11-01T11:29:10Z Vehicle routing and capacity decision models applicable to third party logistics providers Wang, Ricardo Huan Ran Yue Chee Yoon School of Mechanical and Aerospace Engineering Singapore-MIT Alliance Programme DRNTU::Engineering::Manufacturing The importance of the logistics industry globally has risen in tandem with the expansion of global commerce and manufacturing. There is an increasing need to engage the services of third party logistics (3PL) service providers to aid in the rapid penetration of new markets and responsive order fulfillment. Consequently, 3PL firms have to acquire and expand service offerings and physical infrastructure to remain relevant. In such a highly competitive environment, 3PL firms need to improve asset utilization, especially of revenue generating asset classes of vehicle fleet and warehouses, to maintain price competitiveness and operational efficiency. In view of the lack of relevant models in this young and growing industry, we provide the practitioners a review of models in other industries, especially manufacturing, that are relevant and similar in operations of fleet management. Using this as a guide, the practitioner can identify models particularly suited to the unique challenges of his own 3PL operations and suggest improvements to his own algorithms. We also provide a simple yet efficient heuristic that aids the practitioner in the consolidation of warehousing operations to obtain cost economies and other indirect qualitative benefits of customer responsiveness and flexibility. Using the algorithm, the practitioner is able to decide which warehouses to consolidate to achieve maximum leasing and operational cost savings in an expedient manner, while taking into account early termination penalties and relocation costs. Master of Science (IMST) 2014-05-28T04:19:57Z 2014-05-28T04:19:57Z 2005 2005 Thesis http://hdl.handle.net/10356/60542 en 74 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Manufacturing Wang, Ricardo Huan Ran Vehicle routing and capacity decision models applicable to third party logistics providers |
| title | Vehicle routing and capacity decision models applicable to third party logistics providers |
| title_full | Vehicle routing and capacity decision models applicable to third party logistics providers |
| title_fullStr | Vehicle routing and capacity decision models applicable to third party logistics providers |
| title_full_unstemmed | Vehicle routing and capacity decision models applicable to third party logistics providers |
| title_short | Vehicle routing and capacity decision models applicable to third party logistics providers |
| title_sort | vehicle routing and capacity decision models applicable to third party logistics providers |
| topic | DRNTU::Engineering::Manufacturing |
| url | http://hdl.handle.net/10356/60542 |
| work_keys_str_mv | AT wangricardohuanran vehicleroutingandcapacitydecisionmodelsapplicabletothirdpartylogisticsproviders |