Abstract

In the construction industry, contractor failure is always possible. Surety bonding is a technique that is used to reduce the risk the owner may face in case a contractor fails to complete a project. When a surety company undertakes to provide a contractor with the bonding facility for a specific construction project, the risks of project completion are shifted from the owner to the surety company. A very complex qualification or assessment process is done to assess project specifics and contractual risks. There are many qualitative and quantitative factors that are taken into consideration, and some of these factors have a nature of uncertainty and subjectivity. The purpose of this paper is to present a methodology for developing a framework for formalizing the contractor and project assessment process to obtain surety bonds for specific construction projects. The framework includes the integration of multiple technologies (genetic algorithms, fuzzy logic, neural networks, and learning from examples) into a single application.

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