A Stochastic Decision Model for Contractor Prequalification

JEFFREY S. RUSSELL, CRAIG H. BENSON, PATRICK J. FOX

Research output: Contribution to journalArticlepeer-review

Abstract

In the construction industry, contractor prequalification is the process used to determine each contractor's competence to participate in a project bid. Contractors unqualified or overextended should be eliminated prior to the bidding process. Thus, prequalification can conserve resources of both the owner and the participating contractors. This article describes a computer program, QUALIFIER‐1.5, which is based in part on a previously developed prequalification program, QUALIFIER‐1. A brief description of QUALIFIER‐1 is provided for background information. Next, the stochastic decision model incorporated in QUALIFIER‐1.5 and a Monte Carlo simulation procedure are highlighted. An investigation into whether the aggregate rating is normally distributed has been performed and is described. The software is described along with an example application. A comparison of the two programs is also provided. The benefit of this program over prior work is that uncertainty in the prequalification process can be incorporated into the decision‐making process.

Original languageEnglish (US)
Pages (from-to)285-297
Number of pages13
JournalComputer‐Aided Civil and Infrastructure Engineering
Volume5
Issue number4
DOIs
StatePublished - Dec 1990

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Computational Theory and Mathematics

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