This thesis focuses on dealing with the Tasks – Vehicles Assigning Problem in a two lane autonomous smart warehouse, which is a part in a three year project joining the Productivity 4.0 program hosted by Executive Yuan as well as the Taiwan Government, using autonomous guided vehicles (AGVs) as the main force for goods retrieval. The motivation of this thesis comes from the rapid risen and development in e – commerce as well as network flow, the foundation of Industry 4.0, and the Internet of Everything in the warehouse management field. Using the KIVA – Like robot used in the Amazon e – retailer, this thesis will solved a combinatorial problem by utilizing optimization method named Hungarian method, which recorded as one of the fastest resulting local optima results, for finding the best combinations among the tasks – vehicles ensuring that the tasks are fulfilled in ascendant order with minimum total time in retrieving goods. Another interest in this thesis is finding the relationships between the total number of vehicles and the warehouse’s parameters such as number of pods, number of total tasks and aisles length ensuring that deadlock conflictions are prohibited in a two – lane warehouse context. A simulated model also be proposed in this thesis, using MATLAB 2015a for optimizing the routing problem and NETLOGO 6.0 for simulating and visual interface on how the warehouse will function and also used for analyzing the warehouse systems’ performance.

This thesis focuses on dealing with the Tasks – Vehicles Assigning Problem in a two lane autonomous smart warehouse, which is a part in a three year project joining the Productivity 4.0 program hosted by Executive Yuan as well as the Taiwan Government, using autonomous guided vehicles (AGVs) as the main force for goods retrieval. The motivation of this thesis comes from the rapid risen and development in e – commerce as well as network flow, the foundation of Industry 4.0, and the Internet of Everything in the warehouse management field. Using the KIVA – Like robot used in the Amazon e – retailer, this thesis will solved a combinatorial problem by utilizing optimization method named Hungarian method, which recorded as one of the fastest resulting local optima results, for finding the best combinations among the tasks – vehicles ensuring that the tasks are fulfilled in ascendant order with minimum total time in retrieving goods. Another interest in this thesis is finding the relationships between the total number of vehicles and the warehouse’s parameters such as number of pods, number of total tasks and aisles length ensuring that deadlock conflictions are prohibited in a two – lane warehouse context. A simulated model also be proposed in this thesis, using MATLAB 2015a for optimizing the routing problem and NETLOGO 6.0 for simulating and visual interface on how the warehouse will function and also used for analyzing the warehouse systems’ performance.

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