http://iet.metastore.ingenta.com
1887

Optimising departure intervals for multiple bus lines with a multi-objective model

Optimising departure intervals for multiple bus lines with a multi-objective model

For access to this article, please select a purchase option:

Buy eFirst article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
— Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

A multi-objective model was developed to optimize departure intervals synchronously for multiple bus lines. Then, a Genetic Algorithm with “Elitist Preservation” strategy combining the economical method of “dynamic scoring” (GA-EPDS) was proposed to solve the multi-objective model. The proposed method included three objectives: the first objective was to maximize the bus operation profits; the second objective was to minimize the passengers’ transfer waiting time; and the last one was to minimize passengers’ costs. Transfer waiting time was crucial for multiple bus lines and long transfer waiting time would decrease the satisfaction of passengers, so transfer waiting time was regarded as a single objective. In addition, an evaluation function, which was obtained through a “dynamic scoring” method, was formulated to estimate whether the three objective functions reached a global optimum. In order to improve the solution generated in terms of computational effort and convergence, a GA-EPDS was designed to solve the multi-objective model. Finally, the proposed approach was applied in a case study of an actual network. The numerical results based on different scale instances and different traffic conditions demonstrate that our proposed model and method are effective and feasible to optimize departure intervals for multiple bus lines.

References

    1. 1)
      • D. Boyce .
        1. Boyce, D.: ‘Urban transit: operations, planning, and economics, edited by Vukan R. Vuchic’, J. Reg. Sci., 2006, 46, (3), pp. 566568.
        . J. Reg. Sci. , 3 , 566 - 568
    2. 2)
      • Z.R. Ye , C. Wang , Y.R. Xu .
        2. Ye, Z.R., Wang, C., Xu, Y.R.: ‘Modeling level-of-safety for bus stops in China’, Traffic Injury Prev., 2016, 17, (6), pp. 656661.
        . Traffic Injury Prev. , 6 , 656 - 661
    3. 3)
      • D. Sollohub , A. Tharanathan .
        3. Sollohub, D., Tharanathan, A.: ‘A multidisciplinary approach toward improving bus schedule readability’, J. Public Transp., 2006, 9, (4), pp. 6186.
        . J. Public Transp. , 4 , 61 - 86
    4. 4)
      • P. Bullock , Q. Jiang , P.R. Stopher .
        4. Bullock, P., Jiang, Q., Stopher, P.R.: ‘Using GPS technology to measure on-time running of scheduled bus services’, J. Public Transp., 2005, 8, (1), pp. 2140.
        . J. Public Transp. , 1 , 21 - 40
    5. 5)
      • M.E. Kim , P. Schonfeld .
        5. Kim, M.E., Schonfeld, P.: ‘Maximizing net benefits for conventional and flexible bus services’, Transp. Res. A, Policy Pract., 2015, 80, pp. 16133.
        . Transp. Res. A, Policy Pract. , 16 - 133
    6. 6)
      • S. Yan , C.J. Chi , C.H. Tang .
        6. Yan, S., Chi, C.J., Tang, C.H.: ‘Inter-city bus routing and timetable setting under stochastic demands’, Transp. Res. A, Policy Pract., 2006, 40, (7), pp. 572586.
        . Transp. Res. A, Policy Pract. , 7 , 572 - 586
    7. 7)
      • M. Friedrich , I. Hofsaess , S. Wekeck .
        7. Friedrich, M., Hofsaess, I., Wekeck, S.: ‘Timetable-based transit assignment using branch and bound techniques’, Transp. Res. Rec., 2001, 1752, (1), pp. 100107.
        . Transp. Res. Rec. , 1 , 100 - 107
    8. 8)
      • Z. Liu , J. Shen , H. Wang .
        8. Liu, Z., Shen, J., Wang, H., et al: ‘Regional bus timetabling model with synchronization’, J. Transp. Syst. Eng. Inf. Technol., 2007, 7, (2), pp. 109112.
        . J. Transp. Syst. Eng. Inf. Technol. , 2 , 109 - 112
    9. 9)
      • X. Zuo , C. Chen , W. Tan .
        9. Zuo, X., Chen, C., Tan, W., et al: ‘Vehicle scheduling of an urban bus line via an improved multiobjective genetic algorithm’, IEEE Trans. Intell. Transp. Syst., 2015, 16, (2), pp. 10301041.
        . IEEE Trans. Intell. Transp. Syst. , 2 , 1030 - 1041
    10. 10)
      • Y. Qian , J. Luo , J. Zeng .
        10. Qian, Y., Luo, J., Zeng, J.: ‘Bus departure intervals optimization considering crowing costs’, J. Theor. Appl. Inf. Technol., 2013, 47, (3), pp. 10711075.
        . J. Theor. Appl. Inf. Technol. , 3 , 1071 - 1075
    11. 11)
      • X. Chen , B. Hellinga , C. Chang .
        11. Chen, X., Hellinga, B., Chang, C., et al: ‘Optimization of headways with stop-skipping control: a case study of bus rapid transit system’, J. Adv. Transp., 2015, 49, (3), pp. 385401.
        . J. Adv. Transp. , 3 , 385 - 401
    12. 12)
      • D.J. Sun , Y. Xu , Z.R. Peng .
        12. Sun, D.J., Xu, Y., Peng, Z.R.: ‘Timetable optimization for single bus line based on hybrid vehicle size model’, J. Traffic Transp. Eng. (Engl. Ed.), 2015, 2, (2), pp. 179186.
        . J. Traffic Transp. Eng. (Engl. Ed.) , 2 , 179 - 186
    13. 13)
      • E. Castillo , I. Gallego , J.M. Ureña .
        13. Castillo, E., Gallego, I., Ureña, J.M., et al: ‘Timetabling optimization of a single railway track line with sensitivity analysis’, TOP, 2009, 17, (2), pp. 256287.
        . TOP , 2 , 256 - 287
    14. 14)
      • P. Shang , R. Li , L. Yang .
        14. Shang, P., Li, R., Yang, L.: ‘Optimization of urban single-line metro timetable for total passenger travel time under dynamic passenger demand’, Procedia Eng., 2016, 137, pp. 151160.
        . Procedia Eng. , 151 - 160
    15. 15)
      • G.K.D. Saharidis , C. Dimitropoulos , E. Skordilis .
        15. Saharidis, G.K.D., Dimitropoulos, C., Skordilis, E.: ‘Minimizing waiting times at transitional nodes for public bus transportation in Greece’, Oper. Res., 2014, 14, (3), pp. 341359.
        . Oper. Res. , 3 , 341 - 359
    16. 16)
      • O.J. Ibarra-Rojas , Y.A. Rios-Solis .
        16. Ibarra-Rojas, O.J., Rios-Solis, Y.A.: ‘Synchronization of bus timetabling’, Transp. Res. B, Methodol., 2012, 46, (5), pp. 599614.
        . Transp. Res. B, Methodol. , 5 , 599 - 614
    17. 17)
      • A. Ceder , B. Golany , O. Tal .
        17. Ceder, A., Golany, B., Tal, O.: ‘Creating bus timetables with maximal synchronization’, Transp. Res. A, Policy Pract., 2001, 35, (10), pp. 913928.
        . Transp. Res. A, Policy Pract. , 10 , 913 - 928
    18. 18)
      • A. Ceder , O. Tal .
        18. Ceder, A., Tal, O.: ‘Designing synchronization into bus timetables’, Transp. Res. Rec., J. Transp. Res. Board, 2001, 1760, (1), pp. 2833.
        . Transp. Res. Rec., J. Transp. Res. Board , 1 , 28 - 33
    19. 19)
      • M. Mollanejad , H. Zokaei-aashtiani , H. Rezaeestakhruie .
        19. Mollanejad, M., Zokaei-aashtiani, H., Rezaeestakhruie, H.: ‘Creating bus timetables with maximum synchronization’. 90th Annual Meeting of the Transportation Research Board, Washington, DC, USA, 2011, pp. 114.
        . 90th Annual Meeting of the Transportation Research Board , 1 - 14
    20. 20)
      • X. Yang , B. Ning , X. Li .
        20. Yang, X., Ning, B., Li, X., et al: ‘A two-objective timetable optimization model in subway systems’, IEEE Trans. Intell. Transp. Syst., 2014, 15, (5), pp. 19131921.
        . IEEE Trans. Intell. Transp. Syst. , 5 , 1913 - 1921
    21. 21)
      • Y. Wu , H. Yang , J. Tang .
        21. Wu, Y., Yang, H., Tang, J., et al: ‘Multi-objective re-synchronizing of bus timetable: model, complexity and solution’, Transp. Res. C, Emerg. Technol., 2016, 67, pp. 149168.
        . Transp. Res. C, Emerg. Technol. , 149 - 168
    22. 22)
      • S. Yuan , B. Wright , Y. Zou .
        22. Yuan, S., Wright, B., Zou, Y., et al: ‘Quantification of variability of valid travel times with FMMs for buses, passenger cars, and t-axis’, IET Intell. Transp. Syst., 2016, 11, (1), pp. 19.
        . IET Intell. Transp. Syst. , 1 , 1 - 9
    23. 23)
      • Z. Yu , J.S. Wood , V.V. Gayah .
        23. Yu, Z., Wood, J.S., Gayah, V.V.: ‘Using survival models to estimate bus travel times and associated uncertainties’, Transp. Res. C, 2017, 74, pp. 366382.
        . Transp. Res. C , 366 - 382
    24. 24)
      • S.C. Hsu .
        24. Hsu, S.C.: ‘Determinants of passenger transfer waiting time at multi-modal connecting stations’, Transp. Res. E, Logist. Transp. Rev., 2010, 46, (3), pp. 404413.
        . Transp. Res. E, Logist. Transp. Rev. , 3 , 404 - 413
    25. 25)
      • P. Vansteenwegen , D. Van Oudheusden .
        25. Vansteenwegen, P., Van Oudheusden, D.: ‘Decreasing the passenger waiting time for an intercity rail network’, Transp. Res. B, Methodol., 2007, 41, (4), pp. 478492.
        . Transp. Res. B, Methodol. , 4 , 478 - 492
    26. 26)
      • B. Yu , W.H.K. Lam , M.L. Tam .
        26. Yu, B., Lam, W.H.K., Tam, M.L.: ‘Bus arrival time prediction at bus stop with multiple routes’, Transp. Res. C, Emerg. Technol., 2011, 19, (6), pp. 11571170.
        . Transp. Res. C, Emerg. Technol. , 6 , 1157 - 1170
    27. 27)
      • P. Zhou , Y. Zheng , M. Li .
        27. Zhou, P., Zheng, Y., Li, M.: ‘How long to wait? Predicting bus arrival time with mobile phone based participatory sensing’, IEEE Trans. Mob. Comput., 2014, 13, (6), pp. 12281241.
        . IEEE Trans. Mob. Comput. , 6 , 1228 - 1241
    28. 28)
      • L. Chen , P. Schonfeld , E. Miller-Hooks .
        28. Chen, L., Schonfeld, P., Miller-Hooks, E.: ‘Welfare maximization for bus transit systems with timed transfers and financial constraints’, J. Adv. Transp., 2016, 50, (4), pp. 421433.
        . J. Adv. Transp. , 4 , 421 - 433
    29. 29)
      • A.J. Auerbach , A. Goolsbee , W. Gale .
        29. Auerbach, A.J., Goolsbee, A., Gale, W., et al: ‘Dynamic scoring: an introduction to the issues’, Am. Econ. Rev., 2005, 95, (2), pp. 421425.
        . Am. Econ. Rev. , 2 , 421 - 425
    30. 30)
      • E.M. Leeper , S.C.S. Yang .
        30. Leeper, E.M., Yang, S.C.S.: ‘Dynamic scoring: alternative financing schemes’, J. Public Econ., 2008, 92, (1–2), pp. 159182.
        . J. Public Econ. , 159 - 182
    31. 31)
      • J.R. Stinespring .
        31. Stinespring, J.R.: ‘Dynamic scoring, tax evasion, and the shadow economy’, Public Finance Rev., 2010, 39, (1), pp. 5074.
        . Public Finance Rev. , 1 , 50 - 74
    32. 32)
      • A. Ceder . (2010)
        32. Ceder, A.: ‘Public transit planning and operation: theory, modeling and practice’ (Tsinhua University Press, Beijing, 2010).
        .
    33. 33)
      • R.C. Larson , A.R. Odoni . (1981)
        33. Larson, R.C., Odoni, A.R.: ‘Urban operations research’ (Prentice-Hall, Englewood Cliffs, New Jersey, 1981).
        .
    34. 34)
      • R. Balcombe , R. Mackett , N. Paulley .
        34. Balcombe, R., Mackett, R., Paulley, N., et al: ‘The demand for public transport: a practical guide’(TRL Report, Crowthorne, UK, 2004).
        .
    35. 35)
      • 35. CJ 39.1-91.: ‘Urban public transport – the method of economic and technical indexes’, 1991.
        .
    36. 36)
      • J.H. Holland . (1992)
        36. Holland, J.H.: ‘Adaptation in nature and artificial systems’ (MIT Press, Cambridge, 1992).
        .
    37. 37)
      • D.W. Wang . (2007)
        37. Wang, D.W.: ‘Intelligent optimization algorithms’ (Higher Education Press, Beijing, 2007).
        .
    38. 38)
      • C.A.C. Coello .
        38. Coello, C.A.C.: ‘Handling preferences in evolutionary multi-objective optimization: a survey’. Congress on Evolutionary Computation, San Diego, CA, USA, 2000, pp. 3037.
        . Congress on Evolutionary Computation , 30 - 37
    39. 39)
      • G. Gentile , S. Nguyen , S. Pallottino .
        39. Gentile, G., Nguyen, S., Pallottino, S.: ‘Route choice on transit networks with online information at stops’, Transp. Sci., 2005, 39, (3), pp. 289297.
        . Transp. Sci. , 3 , 289 - 297
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-its.2017.0049
Loading

Related content

content/journals/10.1049/iet-its.2017.0049
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address