Green routing of multi-objective transport vehicles with cross docks under the time window constraint

In this research, a model for green routing of vehicles in the network of cross docks under time window constraints is presented. In this model, there are two goals, include reducing the cost of transportation and reducing the emission of environmental pollutants, reducing fuel. In general, the goal of the model is to obtain the best route in the distribution network, which imposes the lowest cost on the network and, in addition, minimizes fuel consumption. The presented model was solved with GAMS software. As the dimensions of the problem increase, the execution time of the program increases drastically, and this indicates that the problem is NP-hard. Therefore, in order to solve the model in large dimensions, the meta-heuristic non-dominant sorting genetic algorithm, NSGAII, was used. The results of examining various problems with the meta-heuristic algorithm show a very high efficiency of the presented algorithms in terms of time to solve the problem. The results showed that the proposed model, in addition to reducing the total cost of transportation and the cost of constructing cross docks in the candidate points, also reduced the emission of environmental pollutants. Also, according to the mentioned time window, the products were sent to the customers on time.