Exploring the suitability of artificial intelligence for establishing criteria for prequalification of highway contractors in Sri Lanka

The extent of the successfulness of a construction project is highly influential on the selected contractor. The decision process has been made easier for the client with the use of prequalification. The selection criteria used for the prequalification are characterized by the co-existence of both quantitative and qualitative information. Therefore in such scenario, it become difficult to analyze the information by decision maker due to the complexity bound to the process. Hence, to improve the reliability and efficiency of the decision being made, it is essential to identify suitable decision support system for the process. The use of Artificial Intelligence (AI) techniques to the prequalification process helps to eliminate the complexity on the decision making of the prequalification process. This research demonstrates the practicality and the suitability on adopting Artificial Neural Network (ANN), Case-based Reasoning (CBR) and Knowledge Based Experts Systems (KBES) to the highway contractor prequalification in Sri Lanka. Therefore, the findings of this research conclude that with the help on identified prequalification model and the identified AI techniques, Sri Lanka can have an effective and efficient mechanism on Highway contractor prequalification.