Reserve Capacity of Mixed Urban Road Networks, Network Configuration and Signal Settings

Reserve Capacity of Mixed Urban Road Networks, Network Configuration and Signal Settings

Masoomeh Divsalar (Mazandaran University of Science and Technology, Babol, Iran), Reza Hassanzadeh (University College of Rouzbahan, Sari, Iran), Iraj Mahdavi (Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran) and Nezam Mahdavi-Amiri (Sharif University of Technology, Tehran, Iran)
Copyright: © 2017 |Pages: 21
DOI: 10.4018/IJAIE.2017010103
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Abstract

The authors formulate the transportation mixed network design problem (MNDP) as a mixed-integer bi-level mathematical problem, based on the concept of reserve capacity. The upper level goal is to maximize the reserve capacity by signal settings at intersections, determine street direction and increase street capacities via addition of lanes. The lower level problem is a deterministic user equilibrium traffic assignment problem to minimize the user travel time. The model being non-convex, meta-heuristic methods are used to solve the problem. A hybridization of genetic algorithm with simulated annealing and a bee algorithm are proposed. Numerical examples are illustrated to verify the effectiveness of the proposed model and the algorithms.
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Literature Review

Farahani et.al. (2013), a review of the definitions, classifications, objectives, constraints, decision variables and solution methods of the urban transportation network design problem are provided. This review shows that most studies on NDP are about CNDP. Most studies on CNDP lead to the development of algorithms and most problem definitions are similar (Abdulaal and LeBlanc, (1979); Marcotte, (1983); Davis, (1994); Ziyou and Yifan, (2002); Chiou, (2005); Gao, et. al. (2007); Chiou, (2008); Xu et. al. (2009)). Studies on DNDP are more limited, in comparison with CNDP because of the discrete variables. Researchers have mostly used heuristic and meta-heuristic algorithms to solve DNDP (Lee and Yang, (1994); Drezner and Salhi, (2002); Drezner and Wesolowsky (2003); Zhang and Gao, (2007); Poorzahedy and Rouhani, (2007); Wu et.al. (2009); Wang and Lo (2010)). Work on MNDP has been scarce in the past decade; the studies are summarized in Table 1.

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