IDEAS home Printed from https://ideas.repec.org/a/sae/envirb/v38y2011i3p520-538.html
   My bibliography  Save this article

Multiobjective Network Design for Emission and Travel-Time Trade-off for a Sustainable Large Urban Transportation Network

Author

Listed:
  • Sushant Sharma

    (NEXTRANS, Regional University Transportation Center, Purdue University, 3000 Kent Avenue, West Lafayette, Indiana 47906, USA)

  • Tom V Mathew

    (Indian Institute of Technology Bombay, Mumbai, 400076 India)

Abstract

Existing optimal road-network capacity-expansion models are based on minimizing travel time and rarely consider environmental factors such as vehicular emissions. In this study we attempt to solve such a transportation network design problem when the planner is environment conscious and thereby tries to minimize health-damage cost due to vehicular emissions along with total system travel time while performing optimal capacity expansion. This problem can be formulated as a multiobjective optimization model which minimizes emissions in addition to travel time, and under budget constraints. A prerequisite for this model is an accurate estimation of vehicle emissions due to changes in link capacities. Since the current practice of estimation of vehicular emissions by aggregate emission factors does not account for the improved speeds resulting from capacity improvements, speed-dependent emission functions for various transport modes and pollutants are used in this study. These functions help in calculating emission factors for use in the proposed model. The model uses a nondominated sorting genetic algorithm as the optimization tool to solve the network design problem. The model is tested on a small hypothetical network and solved for a real large-sized network in India taking into account three pollutants and five transport modes. The Pareto-optimal solutions generated can act as trade-offs between total emissions and total system travel time to account for the planner's desired objectives. Also, reduction in travel time as well as in emissions supports the present model compared with the single-objective model.

Suggested Citation

  • Sushant Sharma & Tom V Mathew, 2011. "Multiobjective Network Design for Emission and Travel-Time Trade-off for a Sustainable Large Urban Transportation Network," Environment and Planning B, , vol. 38(3), pages 520-538, June.
    • Handle: RePEc:sae:envirb:v:38:y:2011:i:3:p:520-538
    DOI: 10.1068/b37018
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1068/b37018
    Download Restriction: no
    File URL: https://libkey.io/10.1068/b37018?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Teng, Junn-Yuan & Tzeng, Gwo-Hshiung, 1996. "A multiobjective programming approach for selecting non-independent transportation investment alternatives," Transportation Research Part B: Methodological, Elsevier, vol. 30(4), pages 291-307, August.
    2. Agachai Sumalee & Simon Shepherd & Anthony May, 2009. "Road user charging design: dealing with multi-objectives and constraints," Transportation, Springer, vol. 36(2), pages 167-186, March.
    3. Current, John & Marsh, Michael, 1993. "Multiobjective transportation network design and routing problems: Taxonomy and annotation," European Journal of Operational Research, Elsevier, vol. 65(1), pages 4-19, February.
    4. Chaisak Suwansirikul & Terry L. Friesz & Roger L. Tobin, 1987. "Equilibrium Decomposed Optimization: A Heuristic for the Continuous Equilibrium Network Design Problem," Transportation Science, INFORMS, vol. 21(4), pages 254-263, November.
    5. Maher, Michael J. & Zhang, Xiaoyan & Vliet, Dirck Van, 2001. "A bi-level programming approach for trip matrix estimation and traffic control problems with stochastic user equilibrium link flows," Transportation Research Part B: Methodological, Elsevier, vol. 35(1), pages 23-40, January.
    6. Bose, Ranjan Kumar, 1998. "Automotive energy use and emissions control: a simulation model to analyse transport strategies for Indian metropolises," Energy Policy, Elsevier, vol. 26(13), pages 1001-1016, November.
    7. Sengupta, Ramprasad & Mandal, Subrata, 2005. "Health damage cost of automotive air pollution: Cost benefit analysis of fuel quality upgradation for Indian cities," Working Papers 05/37, National Institute of Public Finance and Policy.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xiang Zhang & S. Travis Waller, 2019. "Implications of link-based equity objectives on transportation network design problem," Transportation, Springer, vol. 46(5), pages 1559-1589, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dung-Ying Lin & Chi Xie, 2011. "The Pareto-optimal Solution Set of the Equilibrium Network Design Problem with Multiple Commensurate Objectives," Networks and Spatial Economics, Springer, vol. 11(4), pages 727-751, December.
    2. Karimi Dehnavi, Hadi & Rezvan, Mohammad Taghi & Shirmohammadli, Abdolmatin & Vallée, Dirk, 2013. "A solution for urban road selection and construction problem using simulation and goal programming—Case study of the city of Isfahan," Transport Policy, Elsevier, vol. 29(C), pages 46-53.
    3. Minghe Sun, 2005. "Warm-Start Routines for Solving Augmented Weighted Tchebycheff Network Programs in Multiple-Objective Network Programming," INFORMS Journal on Computing, INFORMS, vol. 17(4), pages 422-437, November.
    4. Joseph Y. J. Chow & Amelia C. Regan, 2011. "Real Option Pricing of Network Design Investments," Transportation Science, INFORMS, vol. 45(1), pages 50-63, February.
    5. Birbil, S.I. & Fang, S-C. & Han, J., 2002. "Entropic Regularization Approach for Mathematical Programs with Equilibrium Constraints," ERIM Report Series Research in Management ERS-2002-71-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    6. Castillo, Enrique & Menéndez, José María & Sánchez-Cambronero, Santos, 2008. "Predicting traffic flow using Bayesian networks," Transportation Research Part B: Methodological, Elsevier, vol. 42(5), pages 482-509, June.
    7. Caggiani, Leonardo & Camporeale, Rosalia & Ottomanelli, Michele, 2017. "Facing equity in transportation Network Design Problem: A flexible constraints based model," Transport Policy, Elsevier, vol. 55(C), pages 9-17.
    8. Giulio Cantarella & Antonino Vitetta, 2006. "The multi-criteria road network design problem in an urban area," Transportation, Springer, vol. 33(6), pages 567-588, November.
    9. David Watling, 2002. "A Second Order Stochastic Network Equilibrium Model, II: Solution Method and Numerical Experiments," Transportation Science, INFORMS, vol. 36(2), pages 167-183, May.
    10. Li, Guoyuan & Chen, Anthony, 2022. "Frequency-based path flow estimator for transit origin-destination trip matrices incorporating automatic passenger count and automatic fare collection data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    11. Badami, Madhav G., 2004. "Environmental policy-making in a difficult context: motorized two-wheeled vehicle emissions in India," Energy Policy, Elsevier, vol. 32(16), pages 1861-1877, November.
    12. Chang, Yu-Hern & Yeh, Chung-Hsing & Shen, Ching-Cheng, 2000. "A multiobjective model for passenger train services planning: application to Taiwan's high-speed rail line," Transportation Research Part B: Methodological, Elsevier, vol. 34(2), pages 91-106, February.
    13. Tan, Zhijia & Yang, Hai & Tan, Wei & Li, Zhichun, 2016. "Pareto-improving transportation network design and ownership regimes," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 292-309.
    14. Joaquín Pacheco & Rafael Caballero & Manuel Laguna & Julián Molina, 2013. "Bi-Objective Bus Routing: An Application to School Buses in Rural Areas," Transportation Science, INFORMS, vol. 47(3), pages 397-411, August.
    15. Liu, Haoxiang & Wang, David Z.W., 2017. "Locating multiple types of charging facilities for battery electric vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 30-55.
    16. C-C Chang & R-S Chen, 2007. "Project advancement and its applications to multi-air-route quality budget allocation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(8), pages 1008-1020, August.
    17. Wang, Y.B. & Liu, D. & Cao, X.C. & Yang, Z.Y. & Song, J.F. & Chen, D.Y. & Sun, S.K., 2017. "Agricultural water rights trading and virtual water export compensation coupling model: A case study of an irrigation district in China," Agricultural Water Management, Elsevier, vol. 180(PA), pages 99-106.
    18. Abdullah Alshehri & Mahmoud Owais & Jayadev Gyani & Mishal H. Aljarbou & Saleh Alsulamy, 2023. "Residual Neural Networks for Origin–Destination Trip Matrix Estimation from Traffic Sensor Information," Sustainability, MDPI, vol. 15(13), pages 1-21, June.
    19. Perny, Patrice & Spanjaard, Olivier, 2005. "A preference-based approach to spanning trees and shortest paths problems***," European Journal of Operational Research, Elsevier, vol. 162(3), pages 584-601, May.
    20. Cantarella, G.E. & Pavone, G. & Vitetta, A., 2006. "Heuristics for urban road network design: Lane layout and signal settings," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1682-1695, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:envirb:v:38:y:2011:i:3:p:520-538. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.