SGER: Soft Computing-Based Life-Cycle Cost Analysis of Transportation Infrastructure Investments

Virginia Polytechnic Institute And State University, Blacksburg VA

Investigators

Abstract

This Small Grant for Exploratory Research (SGER) focuses on the use soft computing for developing practical economic analysis tools to support transportation infrastructure asset management. The specific objectives of the research are to: (1) develop an overall framework for the incorporation of soft computing techniques in the life-cycle cost analysis of infrastructure assets, (2) formulate a prototype hybrid soft computing algorithm for life-cycle cost analysis, and (3) compare the algorithm against traditional life-cycle cost analysis tools using simple examples to assess its practical potential. One of the main concerns surrounding life-cycle cost analysis (LCCA) is the treatment of the uncertainty and subjectivity in the physical and economic aspects considered in the engineering economic analysis. This has been addressed extensively in the literature using probabilistic approaches. However, since some of the uncertainty is of an ambiguous nature, soft computing applications are theoretically more appropriate than the probabilistic methods. Soft computing provides a formal approach for the treatment of both random and ambiguous uncertainty and thus is expected to yield more robust, reliable, and stable results. Furthermore, a soft computing-based LCCA system could facilitate the incorporation of non-monetary factors, which require subjective assessments, into the analysis. Life-cycle cost analysis tools modified to treat ambiguity are expected to increase the efficiency of the infrastructure management process. Although the work will concentrate on a specific transportation infrastructure asset, pavements, the research should have a broader impact due to the generalizability of the methods and algorithms to other types of infrastructure assets and related areas. The knowledge acquired through the use of these tools will help agencies understand the technical and economical implications of infrastructure management decisions and the importance of efficiently managing and renewing the existing infrastructure systems.