Proceedings of ICLT 2024
FRAMEWORK FOR ACCESS HUBS SYSTEM VEHICLE ROUTING WITH STOCHASTIC CUSTOMER DEMAND
Maharshi Dhada; Duncan McFarlane
Institute for Manufacturing, Department of Engineering, University of Cambridge, Cambridge, UK; Institute for Manufacturing, Department of Engineering, University of Cambridge, Cambridge, UK
International Conference on Logistics & Transport 2024, Seoul, South Korea, pp. 68-74
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Abstract
Purpose: This paper presents a solution framework to a typical yet often encountered problem in last mile internal and external logistics. This is a case where a warehouse has a fleet of vehicles with limited capacities, and caters to customers in its neighbouring region with known locations. The customer demand is continuous, and each demand (package) is associated with weight, earliest start time, and latest arrival time. Design/ methodology/ approach: This paper presents a solution framework to a typical yet often encountered problem in last mile internal and external logistics. This is a case where a warehouse has a fleet of vehicles with limited capacities, and caters to customers in its neighbouring region with known locations. The customer demand is continuous, and each demand (package) is associated with weight, earliest start time, and latest arrival time. Findings: The findings presented in this paper are the results obtained using the proposed framework and a synthetic testing dataset approved by globally one of the largest shipping and logistics companies. The results show that the aforementioned problem can be solved using a framework relying on reinforcement learning technique that minimises the overall uncertainty while allocating and routing the fleet vehicles. Originality/ value: This paper presents a solution framework to address the split delivery vehicle routing problem with stochastic and continuous customer demand. The paper is impactful as this is an often encountered problem in internal and external last mile logistics, and more so because the testing dataset used for obtaining the results presented in this paper is approved by one of the globally largest shipping and logistics service provider.
Keywords
Last mile logistics; vehicle routing; stochastic problem; probabilistic modelling; transportation
Citation
Maharshi Dhada; Duncan McFarlane (2024). FRAMEWORK FOR ACCESS HUBS SYSTEM VEHICLE ROUTING WITH STOCHASTIC CUSTOMER DEMAND. Proceedings of the International Conference on Logistics & Transport (ICLT 2024), Seoul, South Korea, pp. 68-74.