Skip to main content
SpringerLink
Log in

Multimodal Transport Network Problem: Classical and Innovative Approaches

  • Chapter
  • First Online:
Book cover Soft Computing for Sustainability Science

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 358))

Abstract

This work shows a review about the multimodal transport network problem. This kind of problem has been studied for several researchers who look for solutions to the large numbers of problems relating on the transport systems like: traffic jam, pollution, delays, among others. In this work are presented a standard mathematical formulation for this problem and some other variations, which make the problem more complex and harder to be solved. There are many approaches to solve it that are found in the literature and they are divided according to classical methods and soft computing methodologies, which combine approximate reasoning as fuzzy logic and functional as metaheuristics and neural networks. Each approach has its advantages and disadvantages that are also shown. A novel approach to solve the multimodal transport network problem in fuzzy environment is developed and this approach is also applied in a theoretical problem to illustrate its effectiveness.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Abbaspour, R.A., Samadzadegan, F.: An evolutionary solution for multimodal shortest path problem in metropolises. Comput. Sci. Inf. Syst. 7(4), 1–24 (2010)

    Article  Google Scholar 

  2. Abbaspour, R.A., Samadzadegan, F.: A solution for time-dependent multimodal shortest path problem. J. Appl. Sci. 9(21), 3804–3812 (2009)

    Article  Google Scholar 

  3. Akçelik, R.: Travel time functions for transport planning purposes: Davidson’s function, its time-dependent form and an alternative travel time function. Aust. Road Res. Rep. 21(3), 49–59 (1991)

    Google Scholar 

  4. Alivand, M., Alesheikh, A.A., Malek, M.R.: New method for finding optimal path in dynamic networks. World Appl. Sci. J. 3(1), 25–33 (2008)

    Google Scholar 

  5. Ammar, E.E., Youness, E.A.: Study on multiobjective transportation problem with fuzzy numbers. Appl. Math. Comput. 166, 241–253 (2005)

    MathSciNet  MATH  Google Scholar 

  6. Ambrosino, D., Sciomachen, A.: A shortest path algorithm in multimodal networks: a case study with time varying costs. In: Proceedings of International Network Optimization Conference, Pisa, Italy (2009)

    Google Scholar 

  7. Ayed, H., Galvez-Fernandez, C., Habbas, Z., Khadraoui, D.: Solving time-dependent multimodal transport problems using a transfer graph model. In: Computer & Industrial Engineering (2010, in Press)

    Google Scholar 

  8. Ayed, H., Galvez-Fernandez, C., Habbas, Z., Khadraoui, D.: Hybrid algorithm for solving a multimodal transport problems using a transfer graph model. In: UBIROADS Workshop, Tunisia (2009)

    Google Scholar 

  9. Bellman, R.E.: On a routing problem. Q. Appl. Math. 16, 87–90 (1958)

    Article  MathSciNet  MATH  Google Scholar 

  10. Beltran, B., Carrese, S., Cipriani, E., Petrelli, M.: Transit network design with allocation of green vehicles: A genetic algorithm approach. Transp. Res. Part C 17, 475–483 (2009)

    Article  Google Scholar 

  11. Bieli, M., Boumakoul, A., Mouncif, H.: Object modeling and path computation for multimodal travel systems. Eur. J. Oper. Res. 175, 1705–1730 (2006)

    Article  MATH  Google Scholar 

  12. Bousquet, A.: Rounting strategies minimizing travel time within multimodal urban transport networks. In: ECTRI Young Researcher Seminar, Torino, Italy (2009)

    Google Scholar 

  13. Bousquet, A., Sophie, C., Nour-Eddin, E.F.: On the adaptation of a label-setting shortest path algorithm for one-way and two-way routing in multimodal urban transport networks. In: International Network Optimization Conference, Pisa, Italy (2009)

    Google Scholar 

  14. Bovy, P.H.L., Uges, R., Lanser, S.H.: Modeling route choice behavior in multimodal transport networks. In: 10th International Conference on Travel Behaviour Research, Lucerne (2003)

    Google Scholar 

  15. Brito, J., Martínez, F.J., Moreno, J.A., Verdegay, J.L.: Fuzzy approach for vehicle routing problems with fuzzy travel time. In: International Conference Fuzzy Systems, Barcelona, Spain (2010)

    Google Scholar 

  16. Chanas, S.: The use of parametric programming in fuzzy linear programming. Fuzzy Sets Syst. 11, 243–251 (1983)

    Article  MATH  Google Scholar 

  17. Cipriani, E., Petrelli, M., Fusco, G.: A multimodal transit network design procedure for urban areas. Adv. Transp. Stud. Int. J. 10, 5–20 (2006)

    Google Scholar 

  18. Davidson, K.B.: A flow travel time relationship for use in transportation planning. In: Proceedings of the Australian Road Research Board, Conference 3(1) (1966)

    Google Scholar 

  19. Dijkstra, E.W.: A note on two problems in conexion with graphs. Numer. Math. 1, 269–271 (1959)

    Article  MathSciNet  MATH  Google Scholar 

  20. Dubois, H., Prade, D.: Fuzzy Sets and Systems: Theory and Applications. Academic Press, INC, New York (1980)

    MATH  Google Scholar 

  21. Flórez, J.E., Torralba, A., García, J., López, C.L., Olaya, A.G., Borrajo, D.: TIMIPLAN: an application to solve multimodal transportation problems. In: Association for the Advancement of Artificial Intelligence (2010)

    Google Scholar 

  22. Gattuso, D., Hashemi, S.M.: Estimating running speeds on urban roads. Traffic Eng. Control 45(5), 182–186 (2004)

    Google Scholar 

  23. Ghatee, M., Hashemi, S.M.: Generalized minimal cost flow problem in fuzzy nature: An application in bus network planning problem. Appl. Math. Model. 32, 2490–2508 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  24. Golnarkar, A., Alesheikh, A.A., Malek, M.R.: Solving best path on multimodal transportation networks with fuzzy costs. Iran. J. Fuzzy Syst. 7(3), 1–13 (2010)

    MathSciNet  MATH  Google Scholar 

  25. Hansen, P., Mladenovic, N., Moreno, J.A.: Variable neighbourhood search: methods and applications. Q. J. Oper. Res. 6(4), 319–360 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  26. Hernandes, F.: Algorithms for fuzzy graphs problems. Ph.D. thesis. School of Electrical and Computer Engineering, State University of Campinas (2007)

    Google Scholar 

  27. Julien, B.: An extension to possibilistic linear programming. Fuzzy Sets Syst. 64, 195–206 (1994)

    Article  MathSciNet  Google Scholar 

  28. Kheirikharzar, M.: Shortest path algorithm in multimodal networks for optimization of public transport. In: XXIV FIG Congress Facing the Challenges Building the Capacity, Sydnei, Australia (2010)

    Google Scholar 

  29. Khanbaghi, M., Malham, R.P.: Reducing travel energy costs for a subway train via fuzzy logic controls. In: International Symposium on Intelligent Control, Ohio, USA (1994)

    Google Scholar 

  30. Lam, S.K., Srikanthan, T.: Accelerating the K-shortest paths computation in multimodal transportation networks. In: 5th International Conference on Intelligent Transportation Systems, Singapura (2002)

    Google Scholar 

  31. Lawphongpanich, S., Yin, Y.: Solving the Pareto-improving toll problem via manifold suboptimization. Transp. Res. Part C 18, 234–246 (2010)

    Article  Google Scholar 

  32. Lawphongpanich, S., Yin, Y.: Pareto-improving congestion pricing for general road networks, Technical report, Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida (2007)

    Google Scholar 

  33. Lillo, F., Schmidt, F.: Optimal paths in real multimodal transportation Networks: An appraisal using GIS data from New Zealand and Europe. In: Proceedings of the 45th Annual Conference of the Operations Research Society of New Zealand, New Zealand (2010)

    Google Scholar 

  34. Liu, X., Lin, H.: Optimization model of multimodal transportation mode and its algorithm. In: International Conference on Transportation Information and Safety, pp. 1068–1075 (2011)

    Google Scholar 

  35. Loureiro, C.F.G.: Column generation in solving design problems of multimodal transport networks. In: XVII National Meeting of Production Engineering, Porto Alegre-RS (1997)

    Google Scholar 

  36. Lozano, A., Storchi, G.: Shortest viable path algorithm in multimodal networks. Transp. Res. 35, 225–241 (2001)

    Google Scholar 

  37. Lozano, A., Storchi, G.: Shortest viable hyperpath in multimodal networks. Transp. Res. - Part B 36, 853–874 (2002)

    Article  Google Scholar 

  38. Moccia, L., Cordeau, J.F., Laporte, G., Ropke, S., Valentini, M.P.: Modeling and solving a multimodal transportation problem with flexible-time and scheduled services. Networks 57(1), 53–68 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  39. Modesti, P., Sciomachen, A.: A utility measure for finding multiobjective shortest paths in urban multimodal transportations networks. Eur. J. Oper. Res. 111, 495–508 (1998)

    Article  MATH  Google Scholar 

  40. Mohaymany, A.S., Gholami, A.: Multimodal feeder network design problem: Ant colony optimization approach. J. Transp. Eng. 138(4), 323–331 (2010)

    Article  Google Scholar 

  41. Mouncif, H., Boulmakoul, A., Chala, M.: Integrating GIS-technology for modelling origin-destination trip in multimodal transportation networks. Int. Arab J. Inf. Technol. 3, 256–263 (2006)

    Google Scholar 

  42. Mouncif, H., Rida, M., Boulmakoul, A.: An eficient multimodal path computation integrated within location based service for transportation networks system (Multimodal path computation within LBS). J. Appl. Sci. 11(1), 1–15 (2011)

    Article  MathSciNet  Google Scholar 

  43. Na, L., Zhi, L.: Emergency relief goods multi-mode transportation based on genetic algorithm. In: Second International Conference on Intelligent Computation Technology and Automation, pp. 181–184 (2009)

    Google Scholar 

  44. Nielsen, L.R., Andersen, K.A., Pretolani, D.: Finding the k shortest hyperpaths using reoptimization. Oper. Res. Lett. 34(2), 155–164 (2006)

    Article  MathSciNet  Google Scholar 

  45. Nielsen, L.R.: Route choice in stochastic time-dependent networks. Ph.D. thesis. Department of Operations Research, University of Aarhus, Dinamarca (2004)

    Google Scholar 

  46. Nielsen, L.R., Andersen, K.A., Pretolani, D.: Bicriterion shortest hyperpaths in random time-dependent networks. IMA J. Manag. Math. 14(3), 271–303 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  47. Nijkamp, P., Reggiani, A., Tsang, W.F.: Comparative modelling of interregional transport flows: Applications to multimodal European freight transport. Eur. J. Oper. Res. 155, 584–602 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  48. Okada, T., Soper, S.: A shortest path problem on a network with fuzzy arc lengths. Fuzzy Sets Syst. 109, 129–140 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  49. Palma, A., Picard, N.: Route choice decision under travel time uncertainty. Transp. Res. Part A 39, 295–324 (2005)

    Google Scholar 

  50. Pallottino, S., Scutell, M.G.: Shortest path algorithms in transportation models: classical and innovative aspects. In: Proceedings of the Equilibrium and Advanced Transportation Modelling Colloquium, Klumer (1997)

    Google Scholar 

  51. Pandian, P., Natarajan, G.: A new method for finding an optimal solution of fully interval integer transportation problems. Appl. Math. Sci. 4(37), 1819–1830 (2010)

    MathSciNet  MATH  Google Scholar 

  52. Pattanamekar, P., Park, D., Rilett, L.R., Lee, J., Lee, C.: Dynamic and stochastic shortest path in transportation networks with two components of travel time uncertainty. Transp. Res. Part C 11, 331–354 (2003)

    Article  Google Scholar 

  53. Perugia, A., Moccia, L., Cordeau, J.F., Laporte, G.: Designing a home-to-work bus service in a metropolitan area. Transp. Res. Part B 45, 1710–1726 (2011)

    Article  Google Scholar 

  54. Qu, L., Chen, Y.: A hybrid MCDM method for route selection of multimodal transportation network. In: Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, pp. 374–383 (2008)

    Google Scholar 

  55. Qu, L., Chen, Y., Mu, X.: A transport mode selection method for multimodal transportation based on an adaptive ANN System. In: Fourth International Conference on Natural Computation, pp. 436–440 (2008)

    Google Scholar 

  56. Ramazani, H., Shafahi, Y., Seyedabrishami, S.E.: A shortest path problem in an urban transportation network based on driver perceived travel time. Sci. Iran. A 17(4), 285–296 (2010)

    MATH  Google Scholar 

  57. Ramazani, H., Shafahi, Y., Seyedabrishami, S.E.: A fuzzy traffic assignment algorithm based on driver perceived travel time of network links. Sci. Iran. A 18(2), 190–197 (2011)

    Article  MATH  Google Scholar 

  58. Resende, M.G.C., Ribeiro, C.C.: Greedy randomized adaptive search procedure. In: Handbook in Metaheuristics, pp. 219-249. Kluwer (2003)

    Google Scholar 

  59. Shih, L.H.: Cement transportation planning via fuzzy linear programming. Int. J. Prod. Econ. 58, 277–287 (1999)

    Article  Google Scholar 

  60. Sreelekha, M.G., Anjaneyulu, M.V.L.R.: Development of link travel time model in mixed mode environment. In: Proceedings of Inter-American Congress on Traffic and Transportation (2010)

    Google Scholar 

  61. Sumalee, A., Uchida, K., Lam, W.H.K.: Stochastic multi-modal transport network under demand uncertainties and adverse weather condition. Transp. Res. Part C 19(2), 338–350 (2011)

    Article  Google Scholar 

  62. Tuzkaya, U.R., Önüt, S.: A fuzzy analytic network process based approach to transportation-mode selection between Turkey and Germany: A case study. Inf. Sci. 178, 3133–3146 (2008)

    Article  Google Scholar 

  63. Xin-bo, W., Gui-jun, Z., Zhen, H., Hai-feng, G., Li, Y.: Modeling and implementing research of multimodal transportation network. In: The 1st International Conference on Information Science and Engineering, pp. 2100–2103 (2009)

    Google Scholar 

  64. Yu, H., Lu, F.: A multimodal route planning approach with an improved genetic algorithm. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 38(2), 343–348 (2011)

    Google Scholar 

  65. Wu, D., Yin, Y., Lawphongpanich, S.: Pareto-improving congestion pricing on multimodal transportation networks. Eur. J. Oper. Res. 210, 660–669 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  66. Wellman, M.P., Larson, K., Ford, M., Wurman, P.R.: Path planning under time-dependent uncertainty. In: Proceedings of the 11th Conference on Uncertainty in Artificial Intelligence (1995)

    Google Scholar 

  67. Yamada, T., Russ, B.F., Castro, J., Taniguchi, E.: Designing multimodal freight transport networks: A heuristic approach and applications. Transp. Sci. 43(2), 129–143 (2009)

    Article  Google Scholar 

  68. Zadeh, L.: Soft computing and fuzzy logic. IEEE Softw. 11(6), 48–56 (1994)

    Article  Google Scholar 

  69. Ziliaskopoulos, A., Wardell, W.: An intermodal optimum path algorithm for multimodal networks with dynamic arc travel times and switching delays. Eur. J. Oper. Res. 125, 486–502 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  70. Zimmermann, H.J.: Fuzzy Sets Theory and its Applications. Kluwer Academic Publishers, Boston (1991)

    Book  MATH  Google Scholar 

  71. Zografos, K.G., Androutsopoulos, K.N.: Algorithms for itinerary planning in multimodal transportation networks. IEEE Trans. Intell. Transp. Syst. 9, 175–184 (2008)

    Article  Google Scholar 

Download references

Acknowledgements

The authors want to thank the Brazilian agencies CAPES and FAPESP with project number 2010/51069-2.

Author information

Authors and Affiliations

  1. Department of Telematics, School of Electrical and Computer Engineering, University of Campinas, Av. Albert Einstein, 400, Campinas, SP, 13083-852, Brazil

    Juliana Verga & Akebo Yamakami

  2. Institute of Science and Technology, Federal University of São Paulo, Rua Talim, 330, Vila Nair, São José dos Campos, SP, 12231-280, Brazil

    Ricardo C. Silva

Authors
  1. Juliana Verga
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ricardo C. Silva
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Akebo Yamakami
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ricardo C. Silva .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain

    Carlos Cruz Corona

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this chapter

Cite this chapter

Verga, J., Silva, R.C., Yamakami, A. (2018). Multimodal Transport Network Problem: Classical and Innovative Approaches. In: Cruz Corona, C. (eds) Soft Computing for Sustainability Science. Studies in Fuzziness and Soft Computing, vol 358. Springer, Cham. https://doi.org/10.1007/978-3-319-62359-7_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-62359-7_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62358-0

  • Online ISBN: 978-3-319-62359-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation