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A bi-objective turning restriction design problem in urban road networks

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  • Long, Jiancheng
  • Szeto, W.Y.
  • Huang, Hai-Jun

Abstract

This paper introduces a bi-objective turning restriction design problem (BOTRDP), which aims to simultaneously improve network traffic efficiency and reduce environmental pollution by implementing turning restrictions at selected intersections. A bi-level programming model is proposed to formulate the BOTRDP. The upper level problem aims to minimize both the total system travel time (TSTT) and the cost of total vehicle emissions (CTVE) from the viewpoint of traffic managers, and the lower level problem depicts travelers’ route choice behavior based on stochastic user equilibrium (SUE) theory. The modified artificial bee colony (ABC) heuristic is developed to find Pareto optimal turning restriction strategies. Different from the traditional ABC heuristic, crossover operators are captured to enhance the performance of the heuristic. The computational experiments show that incorporating crossover operators into the ABC heuristic can indeed improve its performance and that the proposed heuristic significantly outperforms the non-dominated sorting genetic algorithm (NSGA) even if different operators are randomly chosen and used in the NSGA as in our proposed heuristic. The results also illustrate that a Pareto optimal turning restriction strategy can obviously reduce the TSTT and the CTVE when compared with those without implementing the strategy, and that the number of Pareto optimal turning restriction designs is smaller when the network is more congested but greater network efficiency and air quality improvement can be achieved. The results also demonstrate that traffic information provision does have an impact on the number of Pareto optimal turning restriction designs. These results should have important implications on traffic management.

Suggested Citation

  • Long, Jiancheng & Szeto, W.Y. & Huang, Hai-Jun, 2014. "A bi-objective turning restriction design problem in urban road networks," European Journal of Operational Research, Elsevier, vol. 237(2), pages 426-439.
  • Handle: RePEc:eee:ejores:v:237:y:2014:i:2:p:426-439
    DOI: 10.1016/j.ejor.2014.01.053
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    References listed on IDEAS

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    1. repec:eee:transb:v:112:y:2018:i:c:p:191-215 is not listed on IDEAS
    2. Khooban, Zohreh & Farahani, Reza Zanjirani & Miandoabchi, Elnaz & Szeto, W.Y., 2015. "Mixed network design using hybrid scatter search," European Journal of Operational Research, Elsevier, vol. 247(3), pages 699-710.
    3. Szeto, W.Y. & Jiang, Y., 2014. "Transit route and frequency design: Bi-level modeling and hybrid artificial bee colony algorithm approach," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 235-263.
    4. W. Y. Szeto, 2016. "Guest Editorial: Special Issue on Quantitative Approaches to Environmental Sustainability in Transportation Networks," Networks and Spatial Economics, Springer, vol. 16(1), pages 1-8, March.
    5. Hamdouch, Younes & Szeto, W.Y. & Jiang, Y., 2014. "A new schedule-based transit assignment model with travel strategies and supply uncertainties," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 35-67.
    6. Long, Jiancheng & Szeto, W.Y. & Huang, Hai-Jun & Gao, Ziyou, 2015. "An intersection-movement-based stochastic dynamic user optimal route choice model for assessing network performance," Transportation Research Part B: Methodological, Elsevier, vol. 74(C), pages 182-217.

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