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Development of a Web-Based Decision Support System for Strategic and Tactical Sustainable Fleet Management Problems in Intermodal Transportation Networks

  • Adil BaykasoğluEmail author
  • Kemal Subulan
  • A. Serdar Taşan
  • Nurhan Dudaklı
  • Murat Turan
  • Erdin Çelik
  • Özgür Ülker
Chapter
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 273)

Abstract

This paper presents a web-based decision support system (DSS) which uses a fuzzy-stochastic mathematical programming based model for strategic and tactical intermodal fleet management. Indeed, several sub-problems such as load planning, fleet sizing and composition, fleet allocation, vehicle inventory control, fleet expansion/reduction and empty vehicle repositioning decisions are incorporated into the proposed DSS. Therefore, it has a modular structure to support these interactive decisions in an integrated manner. In the model component of the proposed DSS, in addition to optimize overall transportation costs, users are able to provide environmentally conscious and customer-oriented freight and fleet plans by minimizing total transit times and CO2 emissions. In the data component, an object-relational database management system namely Oracle was utilized. The LINGO 15.0 optimization code of the proposed model is run over C# and object-oriented matching was utilized for connection among Oracle database and C# programs. The web-based user interface is designed by using .Net and C# programs on Microsoft Visual Studio. The proposed system is tested on a real-life application in an international logistics company of Turkey. By making use of such a DSS, effective and efficient fleet and freight plans can be generated under different types of uncertainties and risk-levels.

Keywords

Fleet management software Intermodal transportation Web-based decision support systems Mathematical programming Sustainable fleet planning 

Notes

Acknowledgement

This paper is supported by Ministry of Science, Industry & Technology of Turkey in the scope of SAN-TEZ project No: 0617.STZ.2014.

References

  1. Andersson, T. (2005). Decision support tools for dynamic fleet management – applications in airline planning and ambulance logistics. Dissertation No. 942, Department of Science and Technology Linköpings Universitet, Norrköping.Google Scholar
  2. Andersson, T., & Värbrand, P. (2007). Decision support tools for ambulance dispatch and relocation. Journal of the Operational Research Society, 58(2), 195–201.CrossRefGoogle Scholar
  3. Arnold, P., Peeters, D., & Thomas, I. (2004). Modelling a rail/road intermodal transportation system. Transportation Research Part E, 40(3), 255–270.CrossRefGoogle Scholar
  4. Assadipour, G., Ke, G. Y., & Verma, M. (2015). Planning and managing intermodal transportation of hazardous materials with capacity selection and congestion. Transportation Research Part E, 76, 45–57.CrossRefGoogle Scholar
  5. Avramovich, D., Cook, T. M., Langston, G. D., & Sutherland, F. (1982). A decision support system for fleet management: A linear programming approach. Interfaces, 12(3), 1–9.CrossRefGoogle Scholar
  6. Bandeira, D. L., Becker, J. L., & Borenstein, D. (2009). A DSS for integrated distribution of empty and full containers. Decision Support Systems, 47(4), 383–397.CrossRefGoogle Scholar
  7. Basnet, C., Foulds, L., & Igbaria, M. (1996). FleetManager: A microcomputer-based decision support system for vehicle routing. Decision Support Systems, 16, 195–207.CrossRefGoogle Scholar
  8. Bauer, J., Bektaş, T., & Crainic, T. G. (2010). Minimizing greenhouse gas emissions in intermodal freight transport: An application to rail service design. Journal of the Operational Research Society, 61, 530–542.CrossRefGoogle Scholar
  9. Baykasoğlu, A., & Subulan, K. (2016). A multi-objective sustainable load planning model for intermodal transportation networks with a real-life application. Transportation Research Part E, 95, 207–247.CrossRefGoogle Scholar
  10. Baykasoğlu, A., & Subulan, K. (2017). A new intermodal fleet planning model via hybrid fuzzy-stochastic mathematical programming method. In Abstract book of international workshop on mathematical methods in engineering (p. 123). Istanbul.Google Scholar
  11. Baykasoğlu, A., Subulan, K., Dudaklı, N., Taşan, A. S., Kaplan, M. C., & Turan, M. (2015). A new mixed-integer programming model for strategic and tactical fleet planning problems in intermodal transportation networks with a real life application. In Proceeding book of XIII: International logistics and supply chain congress (pp. 637–648). Izmir.Google Scholar
  12. Bhattacharya, A., Kumar, S. A., Tiwari, M. K., & Talluri, S. (2014). An intermodal freight transport system for optimal supply chain logistics. Transportation Research Part C, 38, 73–84.CrossRefGoogle Scholar
  13. Bierwirth, C., Kirschstein, T., & Meisel, F. (2012). On transport service selection in intermodal rail/road distribution networks. BuR-Business Research, 5(2), 198–219.CrossRefGoogle Scholar
  14. Bruns, F., & Knust, S. (2012). Optimized load planning of trains in intermodal transportation. OR Spectrum, 34(3), 511–533.CrossRefGoogle Scholar
  15. Caris, A., Macharis, C., & Janssens, G. K. (2008). Planning problems in intermodal freight transport: Accomplishments and prospects. Transportation Planning and Technology, 31(3), 277–302.CrossRefGoogle Scholar
  16. Caris, A., Macharis, C., & Janssens, G. K. (2013). Decision support in intermodal transport: A new research agenda. Computers in Industry, 64(2), 105–112.CrossRefGoogle Scholar
  17. Chang, T. S. (2008). Best routes selection in international intermodal networks. Computers & Operations Research, 35(9), 2877–2891.CrossRefGoogle Scholar
  18. Cho, J. H., Kim, H. S., & Choi, H. R. (2012). An intermodal transport network planning algorithm using dynamic programming—A case study: From Busan to Rotterdam in intermodal freight routing. Applied Intelligence, 36(3), 529–541.CrossRefGoogle Scholar
  19. Couillard, J. (1993). A decision support system for vehicle fleet planning. Decision Support Systems, 9(2), 149–159.CrossRefGoogle Scholar
  20. Dejax, P. J., & Crainic, T. G. (1987). Survey paper-a review of empty flows and fleet management models in freight transportation. Transportation Science, 21(4), 227–248.CrossRefGoogle Scholar
  21. Demir, E., Burgholzer, W., Hrusovsky, M., Arıkan, E., Jammernegg, W., & Woensel, T. V. (2016). A green intermodal service network design problem with travel time uncertainty. Transportation Research Part B, 93, 789–807.CrossRefGoogle Scholar
  22. Dudaklı, N., Baykasoğlu, A., Subulan, K., Tasan, A. S., Kaplan, M. C., & Turan, M. (2015). A mathematical model proposal for fleet planning problem of a real-life intermodal transportation network. In Abstract book international conference on operations research. Vienna.Google Scholar
  23. Ekol Logistics Inc. (2017). Retrieved from https://quadronet.ekol.com/login.aspx on 6th June.
  24. El-Din, M. M. M., Ghali, N. I., Sadek, A., & Abouzeid, A. A. (2015). Decision support system for airlines fleet capacity management. International Journal of Computer Applications, 109(16), 1–8.CrossRefGoogle Scholar
  25. Ezabadi, M. G., & Vergara, H. A. (2016). Decomposition approach for integrated intermodal logistics network design. Transportation Research Part E, 89, 53–69.CrossRefGoogle Scholar
  26. Fagerholt, K. (2004). A computer-based decision support system for vessel fleet scheduling – experience and future research. Decision Support Systems, 37, 35–47.CrossRefGoogle Scholar
  27. Fagerholt, K., Christiansen, M., Hvattum, L. M., Johnsen, T. A. V., & Vabø, T. J. (2010). A decision support methodology for strategic planning in maritime transportation. Omega, 38(6), 465–474.CrossRefGoogle Scholar
  28. Fagerholt, K., & Lindstad, H. (2007). TurboRouter: An interactive optimisation-based decision support system for ship routing and scheduling. Maritime Economics & Logistics, 9(3), 214–233.CrossRefGoogle Scholar
  29. Febbraro, A. D., Sacco, N., & Saeednia, M. (2016). An agent-based framework for cooperative planning of intermodal freight transport chains. Transportation Research Part C, 64, 72–85.CrossRefGoogle Scholar
  30. Garcia, J., Florez, J. E., Torralba, A., Borrajo, D., Lopez, C. L., Garcia-Olaya, A., & Saenz, J. (2013). Combining linear programming and automated planning to solve intermodal transportation problems. European Journal of Operational Research, 227(1), 216–226.CrossRefGoogle Scholar
  31. Guelat, J., Florian, M., & Crainic, T. G. (1990). A multimode multiproduct network assignment model for strategic planning of freight flows. Transportation Science, 24(1), 25–39.CrossRefGoogle Scholar
  32. Grzybowska, H., & Barceló, J. (2012). Decision support system for real-time urban freight management. Procedia – Social and Behavioral Sciences, 39, 712–725.CrossRefGoogle Scholar
  33. Herrera, M., Agrell, P. J., Manrique-de-Lara-Peñate, C., & Trujillo, L. (2017). Vessel capacity restrictions in the fleet deployment problem: An application to the Panama Canal. Annals of Operations Research, 253(2), 845–869.CrossRefGoogle Scholar
  34. Hill, A., & Böse, J. W. (2017). A decision support system for improved resource planning and truck routing at logistic nodes. Information Technology and Management, 18(3), 241–251.CrossRefGoogle Scholar
  35. Imai, A., & Rivera, F. (2001). Strategic fleet size planning for maritime refrigerated containers. Maritime Policy & Management, 28(4), 361–374.CrossRefGoogle Scholar
  36. Inghels, D., Dullaert, W., & Vigo, D. (2016). A service network design model for multimodal municipal solid waste transport. European Journal of Operational Research, 254(1), 68–79.CrossRefGoogle Scholar
  37. Jang, W., Noble, J., Klein, C., Nemmers, C., Yu, Z., & Zhang, Y. (2008). A decision support system for optimal depot and fleet management. A report from The Midwest Transportation Consortium Iowa State University.Google Scholar
  38. Jimenez, M., Arenas, M., Bilbao, A., & Rodriguez, M. V. (2007). Linear programming with fuzzy parameters: An interactive method resolution. European Journal of Operational Research, 177(3), 1599–1609.CrossRefGoogle Scholar
  39. Kalinina, M., Olsson, L., & Larsson, A. (2013). A multi objective chance constrained programming model for intermodal logistics with uncertain time. International Journal of Computer Science Issues, 10(6), 35–44.Google Scholar
  40. Kek, A. G. H., Cheu, R. L., Meng, Q., & Fung, C. H. (2009). A decision support system for vehicle relocation operations in carsharing systems. Transportation Research Part E, 45(1), 149–158.CrossRefGoogle Scholar
  41. Li, L., Negenborn, R. R., & Schutter, B. D. (2015). Intermodal freight transport planning – A receding horizon control approach. Transportation Research Part C, 60, 77–95.CrossRefGoogle Scholar
  42. Lin, C. C., & Lin, S. W. (2016). Two-stage approach to the intermodal terminal location problem. Computers & Operations Research, 67, 113–119.CrossRefGoogle Scholar
  43. Lindo Systems Inc. (2016). Retrieved from http://www.lindo.com/downloads/PDF/LINGO.pdf
  44. List, G. F., Wood, B., Nozick, L. K., Turnquist, M. A., Jones, D. A., Kjeldgaard, E. A., & Lawton, C. R. (2003). Robust optimization for fleet planning under uncertainty. Transportation Research Part E, 39(3), 209–227.CrossRefGoogle Scholar
  45. Macharis, C., & Bontekoning, Y. M. (2004). Opportunities for OR in intermodal freight transport research: A review. European Journal of Operational Research, 153(2), 400–416.CrossRefGoogle Scholar
  46. Macharis, C., Caris, A., Jourquin, B., & Pekin, E. (2011). A decision support framework for intermodal transport policy. European Transport Research Review, 3(4), 167–178.CrossRefGoogle Scholar
  47. Martínez-López, A., Sobrino, P. C., González, M. C., & Trujillo, L. (2018). Optimization of a container vessel fleet and its propulsion plant to articulate sustainable intermodal chains versus road transport. Transportation Research Part D, 59, 134–147.CrossRefGoogle Scholar
  48. Matsatsinis, N. F. (2004). Towards a decision support system for the ready concrete distribution system: A case of a Greek company. European Journal of Operational Research, 152, 487–499.CrossRefGoogle Scholar
  49. Meisel, F., Kirschstein, T., & Bierwirth, C. (2013). Integrated production and intermodal transportation planning in large scale production–distribution networks. Transportation Research Part E, 60, 62–78.CrossRefGoogle Scholar
  50. Müller, D., & Tierney, K. (2017). Decision support and data visualization for liner shipping fleet repositioning. Information Technology and Management, 18(3), 203–221.CrossRefGoogle Scholar
  51. Polo, A., Robol, F., Nardin, C., Marchesi, S., Zorer, A., Zappini, L., Viani, F., Massa, A. (2014). Decision support system for fleet management based on TETRA terminals geolocation. IEEE 8th European conference on antennas and propagation.Google Scholar
  52. Puetmann, C., & Stadtler, H. (2010). A collaborative planning approach for intermodal freight transportation. OR Spectrum, 32(3), 809–830.CrossRefGoogle Scholar
  53. Repede, J. F. (1994). Developing and validating a decision support system for locating emergency medical vehicles in Louisville, Kentucky. European Journal of Operational Research, 75(3), 567–581.CrossRefGoogle Scholar
  54. Resat, H. G., & Turkay, M. (2015). Design and operation of intermodal transportation network in the Marmara region of Turkey. Transportation Research Part E, 83, 16–33.CrossRefGoogle Scholar
  55. Ruiz, R., Maroto, C., & Alcaraz, J. (2004). A decision support system for a real vehicle routing problem. European Journal of Operational Research, 153(3), 593–606.CrossRefGoogle Scholar
  56. Saidane, C. (2007). Decision support system for the management of an Army’s tracked and wheeled vehicle fleet, Master Thesis, Naval Postgraduate School Monterey, California.Google Scholar
  57. Santos, L., Countinho-Rodrigues, J., & Antunes, C. H. (2011). A web spatial decision support system for vehicle routing using Google Maps. Decision Support Systems, 51(1), 1–9.CrossRefGoogle Scholar
  58. Schorpp, S. (2011). Dynamic fleet management for international truck transportation. Germany: Springer.CrossRefGoogle Scholar
  59. SteadieSeifi, M., Dellaert, N. P., Nuijten, W., Van Woensel, T., & Raoufi, R. (2014). Multimodal freight transportation planning: A literature review. European Journal of Operational Research, 233(1), 1–15.CrossRefGoogle Scholar
  60. Verma, M., & Verter, V. (2010). A lead-time based approach for planning rail–truck intermodal transportation of dangerous goods. European Journal of Operational Research, 202(3), 696–706.CrossRefGoogle Scholar
  61. Verma, M., Verter, V., & Zufferey, N. (2012). A bi-objective model for planning and managing rail-truck intermodal transportation of hazardous materials. Transportation Research Part E, 48(1), 132–149.CrossRefGoogle Scholar
  62. Wang, X., & Meng, Q. (2017). Discrete intermodal freight transportation network design with route choice behavior of intermodal operators. Transportation Research Part B, 95, 76–104.CrossRefGoogle Scholar
  63. Wayne, R. (1988). A decision support system for military vehicle fleet management, Thesis (M. Eng. Sc.), Australian Defence Force Academy, pp. 1–162.Google Scholar
  64. Yang, X., Low, J. M. W., & Tang, L. C. (2011). Analysis of intermodal freight from China to Indian Ocean: A goal programming approach. Journal of Transport Geography, 19(4), 515–527.CrossRefGoogle Scholar
  65. Zografos, K. G., & Androutsopoulos, K. N. (2008). A decision support system for integrated hazardous materials routing and emergency response decisions. Transportation Research Part C, 16(6), 684–703.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Adil Baykasoğlu
    • 1
    Email author
  • Kemal Subulan
    • 1
  • A. Serdar Taşan
    • 1
  • Nurhan Dudaklı
    • 1
  • Murat Turan
    • 2
  • Erdin Çelik
    • 2
  • Özgür Ülker
    • 2
  1. 1.Department of Industrial EngineeringDokuz Eylül UniversityIzmirTurkey
  2. 2.Ekol Logistics Inc.IstanbulTurkey

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