Environmental optimization of urban transportation network, using GIS and genetic algorithm

Today, transportation is one of the most important and effective infrastructures and at the same time is the basis for development and adaptive development, and this has caused the attention of managers and planners to the category of transportation. But with regard to the focus of transport planners on accesses and other dynamic aspects of urban transport, its environmental impact has been severely neglected. The city of Petaling Jaya, as an important and religious-tourist metropolis, requires the use of an efficient way of organizing and managing transport, which is not in conflict with other sectors of development, especially the environment. The present research aims to achieve this goal for the first time in the field of study. In this research, after studying the sources, environmental indicators related to transportation were identified, and five important indicators were determined. Then, these indicators were located locally and using GIS maps of transportation network and utilities of Qom and with Bachelor’s opinions are rated. In this way, the map of the Petaling Jaya network is networked, and the indicators in each cell are separately reviewed and rated from 1 to 9 for each indicator. To determine the final status of each cell, the results of the GIS are entered into the MATLAB software, and the results are derived using the genetic algorithm. In order to be able to achieve an optimal environmental situation, we need to make changes in the road network or change the locations that are more sensitive to transport pollution, the results of which are presented in the pictures featured in this paper. The results of this study showed that 40% of the network cells were in an inappropriate state, 35% in the state of appropriate, and 25% in an environmentally sound condition. The results from the optimal map of the transport network show that by transferring some of the uses, especially residential areas to areas around the city and with less pollution, there is a significant change in the status of cellular networks, in which cells with a score of 3 (inappropriate) and points 2 and 1 (relatively appropriate and appropriate) will change. Therefore, transferring parts of the city from the city to the surrounding area is a good way to reduce the impact of pollution.