Drug delivery route optimization with a capacity based on the ALNS algorithm

This paper established a vehicle routing problem (VRP) model with capacity limitation to solve the drug delivery route optimisation problem using an adaptive large-scale neighbourhood search algorithm. The research aims to match orders to riders based on information such as merchant location, rider location, customer location, order remaining time, and rider load to minimise the total delivery distance while ensuring that each order is delivered on time. The model includes multiple objective functions and constraints, such as travel cost and performance cost, as well as time Windows and load capacity limits. By designing three kinds of damage operators (random damage, worst damage and correlation damage) and three kinds of repair operators (greedy repair, regret repair and random repair), and applying the acceptance criteria of the simulated annealing algorithm, the solution process is optimised. The experimental results show that the ALNS algorithm can effectively solve the optimal path scheme after several iterations, significantly reduce the total distribution distance and time, and improve distribution efficiency. The results of this study have important reference value to the actual drug delivery system, which helps improve the rate of patient treatment and the timeliness of drug delivery. In this paper, detailed experiments and data analysis verify the proposed algorithm's effectiveness and feasibility.