Nguyen, P H D (2020) Development of fuzzy hybrid approaches to project delivery method selection in highway construction. PhD thesis, University of Kansas, USA.
Abstract
Selection of project delivery methods is a success factor in delivering highway construction projects because it has a substantial impact on the project performance, such as cost, time, and quality. Project delivery decision-making processes have been heavily relied on experts’ opinions and subjective judgements of professionals to evaluate quantitative and qualitative decision variables. Although current quantitative and probabilistic methods provide a robust means to analyze quantitative variables, they are not ideally suited for treating uncertainties encountered in qualitative variables. Fuzzy set theory is a mathematical approach that can accommodate a combination of quantitative and qualitative variables. This dissertation aimed at investigating the applications of fuzzy set theory and fuzzy logic to support decision-making processes in project delivery method selections. Using an empirical dataset of 254 completed highway construction projects, three fuzzy-based applications, including fuzzy cluster analysis, fuzzy pattern recognition, and fuzzy Bayesian inference system were developed, trained, and tested. As a result, fuzzy cluster analysis was used to establish seven common project clusters that share high similarities in project characteristics, project complexity, delivery risks, cost growth, and project delivery methods. Fuzzy pattern recognition was used to develop a fuzzy rule-based inference system based on the seven identified project clusters to help recognize an appropriate project delivery method associated with potential cost growth for new highway projects. Fuzzy Bayesian networks were used to develop the theoretical framework of fuzzy Bayesian inference system which is able to depict the causal relationships between project characteristics, project complexity, delivery risks, and project delivery methods. The flexibility of fuzzy membership functions in the developed applications helps leverage the evaluation of a combination of quantitative and qualitative variables in highway project delivery method selection. In addition, these data-driven fuzzy applications also allow for multiple decision scenarios based on the decision maker’s judgements of delivery risks and project complexity. This dissertation contributes to the body of knowledge by demonstrating quantitative approaches derived from fuzzy set theory and fuzzy logic to support the selection of project delivery methods in highway construction. Additionally, the results from the developed fuzzy-based applications also provide insights regarding cost performance comparisons between project delivery methods. This study may assist highway agencies in making project delivery decisions based on project attributes, historical data and their relevant experience.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Tran, D and Lines, B |
| Uncontrolled Keywords: | complexity; flexibility; fuzzy set; construction project; highway; delivery method; project delivery; professional; cluster analysis; fuzzy logic; project performance |
| Index terms: | highway construction, project performance, dissertation, project delivery, fuzzy logic, delivery method, decision-making process, fuzzy set theory, fuzzy set, bayesian network, cluster analysis, construction project, dataset, agency, body of knowledge, project complexity, complexity, cost performance, pattern recognition, success factor |
| Subjects: | research dissemination and communication, knowledge management, organizational theory, production management, computer vision, decision-making and optimization, data analysis and analytics, data science, health monitoring assessment and metrics, project delivery, project management theory and practice, economics, civil engineering, systems engineering, delivery method, data management, sociology, decision analysis, probabilistic model |
| Topics: | Digital Applications, Cost Management, Information Management, Research Practice, Health and Safety, Engineering Principles, Project Management, Risk Management, Procurement |
| Descriptive scope: | 4 PCTA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here