Selecting replacement and maintenance alternatives for deteriorating facilities is challenging, and decisions become particularly complex for large systems of thousands of deteriorating units, especially under limited budgets. Only integer programming provides truly optimal solutions, but it is impossible for systems of realistic size. This research uses linear programming (LP) techniques together with aggregation to provide a new framework that can handle large deteriorating systems. The model collects similar units into aggregates. The model also reduces the number of feasible alternatives efficiently by introducing threshold concepts. Finally, it uses LP techniques to select the best alternative for each aggregate, which is also the best alternative for the aggregate's units. The model is implemented on the City of Ann Arbor street system. The performance of the aggregation is evaluated by measuring and comparing savings in effort (the solution times for an aggregate LP and for an unaggregated LP) and aggregate errors (objective function values for aggregated and unaggregated LPs). The computational savings range from 95% to 99%, and aggregation error is less than 0.1% in most cases and consistently less than 0.9%. The model is an effective tool especially for large deteriorating systems, because the number of aggregates can remain unchanged regardless of the number of units in a system. The model is also a very effective tool for a practical decision making process in which consistency of solutions is important and a variety of sensitivity analysis should be performed.

  • Corporate Authors:

    University of Michigan, Ann Arbor

    Department of Civil Engineering
    Ann Arbor, MI  United States  48109
  • Authors:
    • Kim, C-D
    • Carr, R I
  • Publication Date: 1992-3


  • English

Media Info

  • Features: Appendices; Figures; References; Tables;
  • Pagination: 180 p.

Subject/Index Terms

Filing Info

  • Accession Number: 00624885
  • Record Type: Publication
  • Report/Paper Numbers: GLCTTR 15-92/1
  • Files: TRIS
  • Created Date: Sep 4 1993 12:00AM