Analyzing hot-mix asphalt and portland cement concrete highway construction using probabilistic Optimization for profit

Shreenath Rao, Sofia M. Vidalis, Kelly Smith, Peter A. Kopac

Research output: Contribution to journalArticlepeer-review

Abstract

Contractors constantly have to make decisions about maximizing profits while considering risks associated with choosing construction target levels for various acceptance quality characteristics (AQCs). With more and more states adopting incentive-disincentive pay adjustment provisions for quality as measured by various AQCs, a contractor likely has to evaluate several options before selecting an optimum target quality that will maximize profit at an acceptable level of risk. The greater the number of AQCs, the more complex the assessment that the contractor is required to perform and the less intuition and experience can be relied on. The updated Probabilistic Optimization for Profit (Prob.O.Prof. 2.0) is a computer program used as a probabilistic-based tool designed to assist portland cement concrete and hot-mix asphalt paving contractors in evaluating statistical quality assurance specifications. In addition, it assists the highway agencies in evaluating the appropriateness of their specifications and ensuring that they have no undesirable consequences. This procedure allows the agency to adjust pay factors accordingly while developing specifications. The Prob.O.Prof. 2.0 program is discussed, and examples of its use are provided.

Original languageEnglish (US)
Pages (from-to)63-72
Number of pages10
JournalTransportation Research Record
Issue number2098
DOIs
StatePublished - 2009

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Mechanical Engineering

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