Logistics and Distribution Centre Site Selection under Dynamic Spare Parts Demand - Path Optimisation

Aiming at the dynamic customer demand for multiple products in different cycles, with the lowest total cost of the distribution system as the goal, taking into account distribution centre capacity, vehicle loading and other resource constraints, vehicle loading and other resource constraints, we constructed a two-layer objective planning model of distribution centre siting-vehicle path optimization. The upper model is solved by Gurobi to obtain the distribution centre location and customer division scheme, the greedy algorithm will be applied to solve the initial vehicle path planning, and then uses the particle swarm algorithm for optimisation to obtain the corresponding location scheme and vehicle scheduling scheme. Taking an automotive aftermarket spare parts data as an example, the distribution centre site selection and vehicle path scheme are determined in t₁and t₂ cycles respectively, and the findings indicate that the model can be effective in reducing the possible waste of the total distribution cost under the condition of meeting the dynamic demand of the customers, and at the same time tests the model and algorithm effectiveness. This study can serve as a reference for site selection-route planning of spare parts distribution under dynamic demand.