Optimizing Resource Allocation and Routing in FMCG Logistics: A clustering and Simulated Annealing Approach

The Vehicle Routing Problem within specific time windows is a challenge faced by the FMCG industry. Company A, which specializes in distributing necessities and has a low punctuality rate, has been proposed to apply a novel mathematical model to enhance delivery efficiency and aid business decision-making processes. The model’s objective is to align with customer delivery expectations while optimizing the allocation of resources between in-house and outsourced delivery services. To generate solutions, machine learning techniques are leveraged for clustering first, followed by the Simulated Annealing algorithm for route optimization. The research has demonstrated the efficacy of this approach by comparing it with the optimal solution from CPLEX software and 10 different real-world datasets. This methodology holds promise for large and medium-sized enterprises seeking to refine their delivery logistics. This strategy can elevate service quality and simultaneously lower business operational costs by enabling efficient transportation management and adaptability.