Metaheuristic Approach for Green Vehicle Routing Problem with Time Windows and Fuzzy Customer Demand

Abstract

Green Vehicle Routing Problem (GVRP) is one of the extensions of Vehicle Routing Problem. GVRP means that it is concerned with the environment. To fulfil the sustainable development goals, GVRP came into existence as the main motive is to minimize the $CO_2$ emissions in the environment along with optimizing the total travel cost and distance covered by the vehicles. Sustainable development goals (SDG) are also considered in this paper as 4 out of 17 SDG goals are being satisfied by our research. In this research article, the focus is to minimize the total operational costs and total number of vehicles to cover the routes and minimizing {$CO_2$} emissions combined with satisfying the fuzzy customer demand. The mathematical model is developed that integrates fuzzy set theory with energy- efficient routing constraints and time windows. Solomon R101 dataset is considered to check the efficiency of the proposed model. For this task, Ant Colony Optimization algorithm along with Mamdani fuzzy inference system is applied to calculate the optimal values. It is found that the applied approach gives better results in case of minimizing the number of vehicles used and reducing {$CO_2$} emissions along with satisfying the uncertain customer demand. Computational experiments are done to check the efficiency of the proposed model and it has given better results for the chosen Solomon dataset.