Perspectives Of Green Vehicle Routing

Abstract

Transportation is an important process in all supply chains because it serves as the link that allows all order fulfilment activities to take place. The challenges posed by a more sustainable circular economy necessitate a greater emphasis on the environmental impact of transportation and logistics. Cost optimization and in-time delivery lead to customer satisfaction. Optimization of vehicle route plan is the method generally applied to deal with it. Such plans shall consider the minimization of pollution emissions. This proposed research makes significant contributions to the green vehicle routing literature in the following areas. Consideration of dynamic or real-time information in routing by considering uncertain customer demand, the green vehicle routing problem considering backhauls, and the green vehicle routing pick-up and delivery simultaneously with shared channel while minimizing greenhouse gases to the environment. According to the first requirement, a two-phase optimization technique is proposed to deal with the vehicle routing problem. The fuzzy C-mean clustering optimization method is applied for customer grouping, and the genetic algorithm is employed for the optimization of the group vehicle routing problem within each group in order to increase customer happiness while minimizing fuel consumption and emissions. The second scenario has three stages: clustering, routing, and local search. It assigns customers to vehicles based on a multi-objective programming model with three objectives. Reduce total distance, maximize overall savings, and reduce emissions. The third scenario for the Green Vehicle Routing issue deals/focusses Simultaneously on Pickup and Delivery (GVRSPD) of original and remanufactured products. We offer a multi-objective non-linear programming model. The model is linearized, verified, and solved using fuzzy and metaheuristic methods. This mathematical model can reduce the total distribution costs, fuel cost, and greenhouse gas emissions. Finally, we have provided a numerical stud