Equipment Replacement Optimization

The Texas Department of Transportation (TxDOT) has a fleet value of approximately $500,000,000 with an annual turnover of about $50,000,000. Substantial cost savings with fleet management has been documented in the management science literature. For example, a 1983 Interfaces article discussed how Phillips Petroleum saved $90,000 annually by implementing an improved system for a fleet of 5300 vehicles. Scaling up to the TxDOT fleet, the corresponding savings would be around $350,000 in 2008 dollars. Similar savings were reported in a 2008 presentation by Mercury Associates. TxDOT Research Project 7-4941 (1997), Equipment Replacement Criteria Based on LCCBA, created a SAS decision analysis tool to be used by the department in its equipment replacement process. While the 7-4941 analysis tool met project scope within the data limitations existing at the time of its delivery, an improved vehicle cost data base will now allow a more normative decision support tool for fleet replacement optimization. In this sense, optimization means minimizing the life-cycle sum of maintenance cost and replacement cost (new equipment price minus resale value). The Department needs a system which recommends whether to retain or replace a unit of equipment, given that class of equipment’s age, mileage, resale value, and the cost of replacement equipment. TxDOT categorizes, accounts for, and replaces equipment based on classes of equipment; the new automated fleet optimization system must use these class codes. The objective of this project is to (1) determine the best optimization methodology; (2) evaluate commercial fleet management systems; (3) develop the model if this is cost-effective relative to purchasing a commercial model; and (4) validate the new model as needed using data available on TxDOT’s current fleet. To accomplish this project, the research team will formulate the equipment replacement optimization problem as a Mixed-Integer Linear Programming (MILP) model, and propose both Deterministic Dynamic Programming (DDP) and Stochastic Dynamic Programming (SDP) approaches to solving the Equipment Replacement Optimization (ERO) problem. Certainly, this system will be user-friendly and designed so that it can be easily used by non-technical district personnel (to evaluate individual district units against a class) and by technical division personnel (Fleet Manager) to develop optimal aggregate classcode replacement cycles.

  • Record URL:
  • Supplemental Notes:
    • Project Title: Equipment Replacement Optimization.
  • Corporate Authors:

    University of Texas, Tyler

    College of Engineering and Computer Science
    3900 University Boulevard
    Tyler, TX  United States  75799

    University of Texas, Austin

    Center for Transportation Research, 1616 Guadalupe Street
    Austin, TX  United States  78701-1255

    Texas Department of Transportation

    Research and Technology Implementation Office, P.O. Box 5080
    Austin, TX  United States  78763-5080

    Federal Highway Administration

    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590
  • Authors:
    • Fan, Wei
    • Brown, Leonard
    • Patterson, Casey
    • Winkler, Mike
    • Schminkey, Justin
    • Western, Kevin
    • McQuigg, Jason
    • Tilley, Heather
    • Machemehl, Randy
    • Kortum, Katherine
    • Gemar, Mason
  • Publication Date: 2011-10

Language

  • English

Media Info

  • Media Type: Web
  • Edition: Technical Report
  • Features: Appendices; Figures; References; Tables;
  • Pagination: 162p

Subject/Index Terms

Filing Info

  • Accession Number: 01375423
  • Record Type: Publication
  • Report/Paper Numbers: FHWA/TX-11/0-6412-1, Report 0-6412-1
  • Contract Numbers: Project 0-6412
  • Files: TRIS, USDOT, STATEDOT
  • Created Date: Jul 13 2012 4:08PM