A Bilevel Optimization Model for Large Scale Highway Infrastructure Maintenance Inspection and Scheduling Following a Seismic Event

  • Manoj K. Jha
  • Konstantinos Kepaptsoglou
  • Matthew Karlaftis
  • Gautham Anand Kumar Karri
Chapter
Part of the Computational Methods in Applied Sciences book series (COMPUTMETHODS, volume 21)

Abstract

Major highway infrastructure elements, in need of post-earthquake maintenance for improved highway life-cycle, motorist’s guidance, and safety, include bridges, pavements, interchanges, and tunnels. In addition, there are numerous, minor infrastructure elements vital to motorist’s guidance and safety, such as overhead and roadside appurtenances, including signs, guardrails, and luminaries. The maintenance and upkeep of all infrastructure components is crucial for mobility, driver safety and guidance, and overall efficient functioning of a highway system. Successive research efforts have been made in developing optimal Maintenance Repair and Rehabilitation (MR&R) strategies for major infrastructure components, such as pavements and bridges. However, there has been limited studies reported on Maintenance Inspection and Scheduling (MI&S) of minor infrastructure elements, such as signs, guardrails, and luminaries, particularly after the occurrence of seismic events. Typically, a field inspection of such elements is carried out at fixed time intervals to determine their condition, which is used to develop optimal MR&R plan over a given planning horizon, which is not. In this paper we introduce a bilevel model for developing an optimal MI&S plan for large-scale highway infrastructure elements, following a seismic event. At the lower level a set of optimal inspection routes is obtained, which is used at the upper level to obtain optimal maintenance schedule over a given planning horizon. Separate algorithms are developed for solving the lower and upper level optimization models, including a genetic algorithm for solving the lower level model and a customized heuristic for solving the upper level model. A numerical example using a real highway network from Maryland is presented. Finally, directions for future work are discussed.

References

  1. 1.
    Abdullah J (2007) Models for the effective maintenance of roadside features. Doctoral dissertation, Morgan State University, Baltimore, MDGoogle Scholar
  2. 2.
    Brotcorne L, Labbe M, Marcotte P, Savard G (2001) A bilevel model for toll optimization on a multicommodity transportation network. Transport Sci 35(4):345–358MATHCrossRefGoogle Scholar
  3. 3.
    Golabi K, Kulkarni RB, Way GB (1982) A statewide pavement management system. Interfaces 12(6):5–21CrossRefGoogle Scholar
  4. 4.
    Greenfield D (1996) An OR bridge to the future. ORMS Online Edition 23(6)Google Scholar
  5. 5.
    Hejazi SR, Memariani A, Jahanshahloo G, Sepehri MM (2002) Linear bilevel programming solution by genetic algorithm. Com Oper Res 29(13):1913–1925CrossRefMathSciNetGoogle Scholar
  6. 6.
    Huang B, Liu N (2004) Bilevel programming approach to optimizing a logistic distribution network with balancing requirements. Trans Res Record 1894:188–197CrossRefGoogle Scholar
  7. 7.
    Jha MK, Abdullah J (2006a) A Markovian approach for optimizing highway life-cycle with genetic algorithms by considering maintenance of roadside appurtenances. J Frankl Inst 343:404–419MATHCrossRefGoogle Scholar
  8. 8.
    Jha MK, Kepaptsoglou K, Karlaftis M, Abdullah J (2006) A genetic algorithms-based decision support system for transportation infrastructure management in urban areas. In: Taniguchi E, Thompson R (eds) Recent advances in city logistics: proceedings of the 4th international conference on city logistics. Elsevier, New YorkGoogle Scholar
  9. 9.
    Jha MK, Abdullah J (2006b) A probabilistic approach to Maintenance Repair And Rehabilitation (MR&R) of roadside features. In: Proceedings of the 14th Pan-American conference on traffic and transportation engineering (PANAM XIV), Las Palmas de Gran Canaria, SpainGoogle Scholar
  10. 10.
    Kang M (2008) An alignment optimization model for a simple highway Network, Doctoral dissertation, University of Maryland, College park, MDGoogle Scholar
  11. 11.
    Karlaftis M, Kepaptsoglou K, Lambropoulos S (2007) Fund allocation for transportation network recovery following natural disasters. J Urban Plan Dev ASCE 133(1):1–8CrossRefGoogle Scholar
  12. 12.
    Kepaptsoglou K, Karlaftis M, Bitsikas T, Panetsos P, Lambropoulos S (2006) A methodology and decision support system for scheduling inspections in a bridge network following a natural disaster. IABMAS 2006 proceedings. Balkema Publishers, Porto, PortugalGoogle Scholar
  13. 13.
    Le Y, Miao L, Wang H, Wang C (2006) A bilevel programming model and a solution method for public logistics terminal planning. In: Proceedings of the 85th transportation research board conference, Washington, DCGoogle Scholar
  14. 14.
    Madanat S (1991) Optimizing sequential decisions under measurement and forecasting uncertainty: application to infrastructure inspection, maintenance and rehabilitation. D.Sc. dissertation, Massachusetts Institute of Technology, Boston, MAGoogle Scholar
  15. 15.
    Maji A, Jha MK (2007a) Modeling highway infrastructure maintenance schedule with budget constraint. Trans Res Record 1991:19–26CrossRefGoogle Scholar
  16. 16.
    Maji A, Jha MK (2007b) Maintenance schedule of highway infrastructure elements using a genetic algorithm. In: Proceedings of the international conference on civil engineering in the new millennium: opportunities and challenges (CENeM-2007), Bengal Engineering and Science University, Shibpur, Howrah, IndiaGoogle Scholar
  17. 17.
    Marcotte P, Savard G, Semet F (2004) A bilevel programming approach to the travelling salesman problem. Oper Res Lett 32(3):240–248MATHCrossRefMathSciNetGoogle Scholar
  18. 18.
    Mathur K, Puri MC (2005). A bilevel bottleneck programming problem. Eur J Oper Res 85:337–344Google Scholar
  19. 19.
    Murray-Tuite PM, Mahmassani HS (2004). Methodology for determining vulnerable links in a transportation network. Trans Res Record 1882:88–96CrossRefGoogle Scholar
  20. 20.
    Samanta S, Jha MK (2006). A bilevel model for station locations optimization along a rail transit line. In: Allan J et al. (eds) Computers in railways X (COMPRAIL 2006). WIT Press, Southampton, UKGoogle Scholar
  21. 21.
    Yang H, Yagar S (1994). Traffic assignment and traffic control in general freeway-arterial corridor systems, Transport Res B Meth 28:463–486CrossRefGoogle Scholar
  22. 22.
    Yin Y (2000). Genetic-algorithms based approach for bilevel programming models. J Transp Eng ASCE 126(2):115–120CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Manoj K. Jha
    • 1
  • Konstantinos Kepaptsoglou
    • 2
  • Matthew Karlaftis
    • 2
  • Gautham Anand Kumar Karri
    • 1
  1. 1.Department of Civil EngineeringMorgan State UniversityBaltimoreUSA
  2. 2.School of Civil EngineeringNational Technical University of AthensAthensGreece

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