Applying a Capacitated Heterogeneous Fleet Vehicle Routing Problem with Multiple Depots Model to Optimize a Retail Chain Distribution Network

Planning and operating retail chain distribution processes is becoming more challenging, due to the increasing demand and urban congestion. This research applied a Capacitated Heterogeneous Fleet Vehicle Routing Problem with Multiple Depots (CHFVRPMD) model to optimize a retail chain distribution network with a real-world road network. The model attempts to obtain a distribution plan that minimizes the total distribution cost. A hybrid solution algorithm was proposed to solve the CHFVRPMD model. The solution algorithm was developed by combining the heuristic and metaheuristic methods. A case study was carried out to collect actual data to test the proposed optimization model and the solution algorithm. All the input parameters were estimated using a real-world industry application, to minimize the gap between the theoretical model and the real-world applicability. Computation experiments demonstrate the proposed hybrid solution algorithm’s effectiveness in optimizing the CHFVRPMD model in a feasible computational time. The overall findings reveal that the CHFVRPMD model has achieved about 10.7% savings in daily distribution cost, in optimizing the selected retail distribution network. The proposed model and solution algorithm assist industry practitioners to mitigate transport inefficiencies in retail distribution networks.