Optimizing the Gasoline Distribution Network in Iran

The global population is booming, and Iran is no exception. This additional capacity is placing considerable strain on many aspects of human life; in particular on transport. Fossil fuels will continue to play an important part of the transport fuel mix, and therefore the limited and dwindling reserves need to be optimized for economic, social and environmental reasons. The goal of this research is to determine the gasoline transport capacity from ports of the country and local refineries to different destinations throughout Iran. It is the aim of the study to determine an optimization alternative for the gasoline transport capacity from and to each specified destination by applying the trans-shipment model. The goal is to minimize transport expenses due to sending gasoline from two sources to seventy seven destinations, by using forty seven intermediate points and 6,076 decision variables (transport direction). By achieving this goal, industry is confronted with demand and supply restrictions, simplicity of use and non-negative portable gasoline capacity. Referring to the results obtained, the expense of 73% of gasoline transport by pipe-line was 70%, and for road transport of 23%, it came to 25% of the total gasoline transport expenses. Share of transfer by ship for 3.4% yields an expense equal to 5%, and in addition the results show a 17% cost saving of the gasoline distribution expense in 1387.Urban highways are one of the most important infrastructure facilities that play a vital role in daily transportation. There are several approaches for the management of urban highways; one of which is the Intelligent Transportation System (ITS), which integrates advanced information and control technologies to improve traffic flow in transportation networks. Different methods have been developed to improve the performance of highway networks, among which control strategies such as ramp metering (RM), variable speed limits (VSL), route recommendation and variable message signs (VMS) are recognized as the most effective for relieving traffic congestion. This research paper discusses the optimal coordination of variable speed limits and ramp metering in a highway traffic network. The control problem is to determine the optimal combination of control variables that result in the best network performance. Efficiency of this problem was evaluated based on the total time that a vehicle spent in the network (TTS). The applied co-ordination approach incorporates the macroscopic traffic flow model METANET as a prediction model, and a genetic algorithm as an optimization algorithm to co-ordinate the RM and VSL in a highway network. The proposed model was implemented on a highway network with two ramps and two VSLs upstream of each one. The results showed that in cases where ramp metering is insufficient to prevent congestion, variable speed limits can prevent a traffic system breakdown and maintain a higher outflow. In other words, optimal co-ordination of ramp metering and VSLs can significantly reduce congestion and result in a lower total time in the network for vehicles. The results have been compared with a previous study in this field and have been shown to be more beneficial, due to the use of the GA in comparison to the search methods used previously in the literature.