This paper considers the issue of air pollutants emission for the optimal and sustainable determination of cordon location, toll level, and price of park and ride (P&R). Although air pollutants emission decreases within the cordon by the implementation of cordon pricing scheme, it may increase outside the cordon and the whole network. Hence, air pollutants emission may only transfer from inside of the cordon to its outside. Therefore, in this paper, a multi-objective bi-level optimization model is developed. A solution algorithm is also presented based on the second version of strength Pareto evolutionary algorithm (SPEA2). The results reveal that this multi-objective model can be a useful tool for the sustainable and optimal design of the cordon and P&R scheme. In addition, cordon pricing is a multi-objective problem. Therefore, it is necessary to consider air pollutants emission. By choosing another non-dominated result in the solution space, air pollutants emission outside the cordon and the whole network can be reduced without a significant reduction in social welfare.
Wu D, Yin Y, Lawphongpanich S, Yang H. Design of more equitable congestion pricing and tradable credit schemes for multimodal transportation network. Transportation Research Part B. 2012;46(9):1273-1287.
Duranton G, Turner M. The fundamental law of road congestion: evidence from US cities. American Economic Review. 2011;101(6):2016-2052; 2011.
Goodwin P, Noland RB. Building new roads really does create extra traffic: a response to Prakash et al. Applied Economics. 2003;35(13):1451-1457.
Lindsey CR, Verhoef ET. Traffic congestion and congestion pricing. In: Handbook of transport systems and traffic control (eds., Button KJ, Hensher DA). Elsevier Science; 2001.
Levinson DM. Financing transportation networks. Edward Elgar; 2002.
Santos G. Urban congestion charging – a second-best alternative. Journal of Transport Economics and Policy. 2004;38(3):345-369.
Yang H, Verhoef ET. Guest editorial: road pricing problems: recent methodological advances. Networks and Spatial Economics. 2004;4(22):131-133.
Verhoef ET. The economics of regulating road transport. Edward Elgar; 1996.
May AD, Milne DS. Effects of alternative road pricing systems on network performance. Transportation Research Part A. 2000;34(6):407-436.
May AD, Milne DS, Shepherd SP, Sumalee A. Specification of optimal cordon pricing locations and charges. Transportation Research Record. 2002;1812:60-68.
Mun S, Konishi K, Yoshikawa K. Optimal cordon pricing. Journal of Urban Economics. 2003;54(1):21-38.
Santos G, Newbery D, Rojey L. Static vs. demand sensitive models and the estimation of efficient cordon tolls: an exercise for eight English towns. Transportation Research Record. 2001;1747:44-50.
Santos G. Double cordon tolls in urban areas to increase social welfare. Transportation Research Record. 2002;1812:49-55.
Afandizadeh Sh, Yadak M, Kalantari N. Simultaneous determination of optimal toll locations and toll levels in cordon-based congestion pricing problem (case study of Mashhad city). International Journal of Civil Engineering. 2011;9(1):33-40.
Verhoef ET. Second-best congestion pricing in general networks: heuristic algorithms for finding second-best optimal toll levels and toll points. Transportation Research Part B. 2002;36(8):707-729.
Yang H, Zhang XN. Determination of optimal toll levels and toll locations of alternative congestion pricing schemes. Proceedings of the 15th International Symposium on Transportation and Traffic Theory (ed., Taylor, MAP). Pergamon; 2002, p. 519-540.
Liu Z, Meng Q, Wang S. Variational inequality model for cordon-based congestion pricing under side constrained stochastic user equilibrium conditions. Transportmetrica A: Transport Science. 2014;10(8):693-704.
De Palma A, Lindsey R. Congestion pricing with heterogeneous travelers: A general-equilibrium welfare analysis.
Networks and Spatial Economics. 2004;4(2):135-160.
Marcotte P, Zhu DL. Equilibria with infinitely many differentiated classes of customers. In: Complementarity
and Variational Problems-State of the Art (eds., Ferris MC, Pang JS). SIAM, Philadelphia, PA; 2000.
Mayet J, Hansen M. Congestion pricing with continuously distributed values of time. Journal of Transport Economics and Policy. 2000;34(3):359-370.
Nagurney A. A multiclass, multicriteria traffic network equilibrium model. Mathematical and Computer Modeling. 2000;32(3-4):393-411.
Yang H, Huang HJ. The multiclass, multicriteria traffic network equilibrium and system optimum problem. Transportation Research Part B. 2004;38(1):1-15.
Meng Q, Liu Z, Wang S. Optimal distance tolls under congestion pricing and continuously distributed value of time. Transportation Research Part E. 2012;48(5):937–957.
Viegas JM. Making urban road pricing acceptable and effective: searching for quality and equity in urban mobility. Transport Policy. 2001;8(4):289-294.
Paulley N. Recent studies on key issues in road pricing. Transport Policy. 2002;9(3):175-177.
Raux C, Souche S. The acceptability of urban road pricing - A theoretical analysis applied to experience in Lyon. Journal of Transport Economics and Policy. 2004;38(2):191-215.
Santos G, Rojey L. Distributional impacts of road pricing: the truth behind the myth. Transportation. 2004;31(1):21-42.
Yang H, Meng Q, Hau TD. Optimal integrated pricing in a bi-modal transportation network. In: Lee DH, editor. Urban and Regional Transportation Modeling: Essays in Honor of David Boyce. 2004: p. 134-156.
Liu Z, Wang S, Meng Q. Optimal joint distance and time toll for cordon-based congestion pricing. Transportation Research Part B. 2014;69:81-97.
Liu Z, Meng Q, Wang S. Speed-based toll design for cordon-based congestion pricing scheme. Transportation Research Part C. 2013;31:83-98.
Bowen W. An analytical review of environmental justice research: what do we really know? Environmental Management. 2002;29(1):3-15.
[32] Anderton DL, Anderson AB, Oakes JM, Fraser MR. Environmental equity: the demographics of dumping. Demography. 1994;31(2):229-248.
Most MT, Sengupta R, Burguener MA. Spatial scale and population assignment choices in environmental justice analyses. The Professional Geographer. 2004;56(4):574-586.
Mills GS, Neuhauser KS. Quantitative methods for environmental justice assessment of transportation. Risk Analysis. 2000;20(3):377-384.
Chakraborty J. Evaluating the environmental justice impacts of transportation improvement projects in the US. Transportation Research Part D. 2006;11(55):315-323.
Clegg J, Smith M, Xiang Y, Yarrow R. Bi-level programming applied to optimizing urban transportation. Transportation Research Part B. 2001;35(1):41-70.
Dempe S. Foundation of bi-level programming. Kluwer Academic Publishers, New York; 2002.
Yang H, Bell MGH. Transport Bi-level Programming Problems: Recent Methodological Advances. Transportation Research Part B. 2001;35(1):1-4.
Sheffi Y. Urban transportation networks. Massachusetts Institute of Technology, Prentice-Hall, Inc., Englewood Cliffs, N.J. 07632; 1985.
Spiess H, Florian M. Optimal Strategies: a new assignment model for transit networks. Transportation Research Part B. 1989;23(2):83-102.
Agnello RJ. Economic evaluation of highway system benefits. Transportation Research. 1977;11(5):365-369.
Zitzler E, Laumanns M, Bleuler S. A tutorial on evolutionary multi-objective optimization. Metaheuristics for Multiobjective Optimisation. Lecture Notes in Economics and Mathematical Systems. 2004;535:3-37.
Schaffer JD. Multiple objective optimization with vector evaluated genetic algorithms. PhD thesis, Vanderbilt University, Nashville, TN; 1984.
Schaffer JD. Multiple objective optimization with vector evaluated genetic algorithms. Proceedings of the First International Conference on Genetic Algorithms. Hillsdale, NJ: L. Erlbaum Associates Inc.; 1985. p. 93-100.
Schaffer JD, Grefenstette JJ. Multi-objective learning via genetic algorithms. Proceedings of the 9th International Joint Conference on Artificial Intelligence (IJCAI-85). Los Angeles, CA; 1985. p. 593-595.
Coello Coello CA. A comprehensive survey of evolutionary- based multi-objective optimization techniques. Knowledge and Information Systems. 1999;1(3):269-308.
Coello Coello CA, Van Veldhuizen DA, Lamont GB. volutionary algorithms for solving multi-objective problems.
New York: Kluwer Academic Publishers; 2002.
Coello Coello CA, Mariano Romero CE. Evolutionary algorithms and multiple objective optimization. In: Ehrgott M, Gandibleux X, editors. Multiple Criteria Optimization: State of the Art Annotated Bibliographic Surveys. Boston: Kluwer Academic Publishers; 2002.
Zitzler E, Thiele L. Multi-objective evolutionary algorithms: a comparative case study and the strength Pareto approach. IEEE Transactions on Evolutionary Computation. 1999;3(4):257-271.
Zitzler E, Laumanns M, Thiele L. SPEA2: Improving the strength Pareto evolutionary algorithm. Technical Report 103. Zurich: Computer Engineering and Networks Laboratory (TIK); 2001.
Wang S, Meng Q, Yang H. Global optimization methods for the discrete network design problem. Transportation Research Part B. 2013;50:42-60.
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