A Genetic Algorithm-Based Decision Support System for Transportation Infrastructure Management in Urban Areas

Transportation infrastructure networks are vital to any nation’s economy in today’s competitive world, therefore, its’ timely and effective maintenance should be of foremost concern. One of the basic components of transportation infrastructure management in urban areas is the monitoring and inspection of highway infrastructure elements that will entail taking timely maintenance actions subject to a given budget. These elements typically include bridges, tunnels, road signs, traffic equipment, and roadside features, such as guardrails and luminaries. Given their usually limited resources as well as the extended road network in urban areas, road agencies have difficulties in inspecting their networks, which are constantly deteriorated due to traffic congestion, accidents, weather and other factors. In this paper, two models are developed for transportation infrastructure maintenance, one for minimizing inspection travel time and the other for obtaining an optimal maintenance schedule over a planning horizon. A genetic algorithm-based framework is developed as a possible solution approach. Previous approaches primarily used dynamic programming for maintenance scheduling, which was found to be computationally intensive as maintainable infrastructure elements increased. The proposed approach can be used to develop a decision-support system to assist a roadway authority in allocating their maintenance budget in a most effective manner.


  • English

Media Info

  • Media Type: Print
  • Features: Figures; References; Tables;
  • Pagination: pp 509-523
  • Monograph Title: Recent Advances in City Logistics

Subject/Index Terms

Filing Info

  • Accession Number: 01029900
  • Record Type: Publication
  • ISBN: 0080447996
  • Files: TRIS
  • Created Date: Jul 26 2006 3:11PM