Traortation dedicates remarkable part of national gross production in every country and a large part of emissions occurs in this sector. For this reason, in recent years many attempts have been made to reduce emissions by vehicles. One of the traortation problems is vehicle routing problem that different constraints can be imposed on it and get closer to the real world. In this thesis, time dependent vehicle routing problem is taken in to consideration and emissions optimization of vehicle routing is studied by considering factors such as vehicle load, velocity, road gradient and urban traffic congestion. Due to importance of various alternative paths between two nodes in the proposed problem, also, the assumption of multi alternative graph is considered. Then, according to the mentioned assumptions, a mixed integer non-linear mathematical model is presented to reduce travel time and emissions considering multiple alternative graph. Considering the issue that the proposed problem is NP-hard, in order to optimally solve the proposed model, the complete enumeration technique is used for small-scale instances. Using large-scale instances, results of three suggested methods including Gaussian firefly, improved firefly and particle swarm optimization Algorithms are compared. Results shows that, improved firefly algorithm in terms of computational and quality of solutions has better performance than other suggested algorithms. Furthermore, proposed model causes major reduction in emissions by vehicles. Finally in order to investigate the effectiveness of the proposed model, a case study in Isfahan was considered; results show about 41% reduction in fuel consumption
