Amirkabir University of TechnologyAmirkabir Journal of Civil Engineering2588-297X53920211122A fuzzy approach for designing of subway lines, case study: development of the Tehran subway networkA fuzzy approach for designing of subway lines, case study: development of the Tehran subway network1313425610.22060/ceej.2021.18121.6774FAAmir RezaMahdaviTransportation Planning Department, Faculty of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran0000-0001-7309-5002AmirrezaMamdoohiAssociate Professor, Faculty of Civil and Environmental Engineering, Tarbiat Modares University0000-0002-5339-9807MahdiehAllahviranlooGroove School of Engineering, City College of New York, United States of AmericaJournal Article20200315Subway network design can be classified as one of the most challenging problems in transportation planning, where different deterministic or non-deterministic approaches have been utilized for optimal design. Non-deterministic methods, having fewer limitations and representing reality with its intrinsic uncertainty, have thus been the focus of less research. This paper incorporates concepts of fuzzy set theory into the optimal design of subway networks to the case of Tehran. Two binary mathematical programming models with different objective functions are developed. The first model maximizes the covered population while minimizing construction cost, whereas the second maximizes the ratio of the covered population to construction cost. These objective functions are modeled in both a fuzzy and a deterministic state. In the fuzzy model, we use a fuzzy penalty factor instead of edge length constraints and propose a Sugeno fuzzy inference system for calculating the covered population. Results indicate that the total length of designed lines with the linear and nonlinear fuzzy approach is equal to 139.3 km (477000 billion Iranian Rials) and 144.6 km (494000 billion Iranian Rials), respectively. Considering topology improvement per construction cost index, designed lines with the linear fuzzy model are better than the nonlinear fuzzy model. In comparison to the classic deterministic approach, the proposed fuzzy approach can improve topology improvement per construction cost index by 23 percent.Subway network design can be classified as one of the most challenging problems in transportation planning, where different deterministic or non-deterministic approaches have been utilized for optimal design. Non-deterministic methods, having fewer limitations and representing reality with its intrinsic uncertainty, have thus been the focus of less research. This paper incorporates concepts of fuzzy set theory into the optimal design of subway networks to the case of Tehran. Two binary mathematical programming models with different objective functions are developed. The first model maximizes the covered population while minimizing construction cost, whereas the second maximizes the ratio of the covered population to construction cost. These objective functions are modeled in both a fuzzy and a deterministic state. In the fuzzy model, we use a fuzzy penalty factor instead of edge length constraints and propose a Sugeno fuzzy inference system for calculating the covered population. Results indicate that the total length of designed lines with the linear and nonlinear fuzzy approach is equal to 139.3 km (477000 billion Iranian Rials) and 144.6 km (494000 billion Iranian Rials), respectively. Considering topology improvement per construction cost index, designed lines with the linear fuzzy model are better than the nonlinear fuzzy model. In comparison to the classic deterministic approach, the proposed fuzzy approach can improve topology improvement per construction cost index by 23 percent.https://ceej.aut.ac.ir/article_4256_ab68ff84ef215fc96b4ff41d037bbf7b.pdf