The Vehicle Routing Problem (VRP) is a crucial subject in the discipline of logistics and transportation management since it connects the distribution centers to the arrival points of services and goods in the most efficient way possible. Considering the VRP in the framework of operational research, the optimization quality of the VRP mainly depends on an efficient model built for the network and the successful choice for the objective of the model. The optimization problem, which involves the objective function as the ratio of two functions, is described as Fractional Programming (FP), which has attracted noteworthy attention in the previous five decades because of its usefulness in modeling several decision processes in operations research, management science, and economics. In this research, we have studied a Linear Fractional Vehicle Routing Problem (LFVRP) regarding the contribution of the mathematical modeling of VRP to both the optimization literature and the commercial market, which is incontrovertible. For this purpose, we propose an iterative method for LFVRP that aims to optimize the delivery of goods and services while minimizing the rate of total cost/load without any variable transformation technique proposed for the first time. By this methodology of iterative optimization, unlike the literature, the mathematical complexity of the model will be facilitated as a Linear Programming Problem (LPP) and, meanwhile, provide the capability of considering multiple objectives (both cost and load) as one. Furthermore, by this advantage, it has been able to express a green-based approach by presenting an objective that minimizes fuel consumption which constructs transportation expenses, and hence it lowers its carbon footprint for our world while keeping the aim of maximum load. In order to illustrate the effectiveness of our approach, we have built a real-life model with real data in the retail sector in Türkiye and provided a comparative analysis.