Research on AGV task assignment and path planning in robotic mobile fulfilment systems
With the development of the e-commerce industry, the supply chain plays a significant role. The increasing demand needs more efficient and more effective service. As the key component of the online supply chain, the operation of the warehouse greatly affects the speed of order response. More and mor...
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| Format: | Thesis-Master by Coursework |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/173601 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | With the development of the e-commerce industry, the supply chain plays a significant role. The increasing demand needs more efficient and more effective service. As the key component of the online supply chain, the operation of the warehouse greatly affects the speed of order response. More and more e-commerce enterprises apply automation systems in the warehouse to improve order picking efficiency. The Robotic Mobile Fulfilment System (RMFS) is one of the systems which is widely used to solve the problem. It uses Automated Guided Vehicles (AGVs) to transport the items. To further improve the productivity of the warehouse, how to manage the operation of the AGVs in RMFS is of great importance.
This dissertation conducts research on the AGV task assignment and path planning problem in RMFS. For the task assignment, this dissertation proposed 4 strategies based on different assignment time and different assignment principles. For the path planning part, the A* algorithm is improved by grading the AGVs by the loading state and planning the path step by step to avoid conflicts between them. Then, the task assignment strategies and the improved A* algorithm are implemented by MATLAB to deal with the tasks in an RMFS warehouse. The conflict-free paths are successfully planned for AGVs. In the end, a sensitive analysis is made to compare the impact of different task volumes, different warehouse scales and different AGV numbers on warehouse operation time which could provide managerial insights for the enterprises in relevant aspects. The improved A* algorithm helps find the path more dynamically and the assignment strategies are compared and chosen. This dissertation provides a reference for the development of the E-commerce warehouse. |
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