Chang, T-C (1987) Network resource allocation using an expert system with fuzzy logic reasoning. PhD thesis, University of California, Berkeley, USA.
Abstract
This dissertation focuses on the development of new methodologies to solve the priority problem encountered when utilizing resource allocation while scheduling a construction project. A project by its nature is impacted by both internal factors (i. e. , network related factors, such as float, downstream resource usage, etc. ) and external forces (weather conditions, changed conditions, resource availability are typical of these forces). In this dissertation, an algorithm to measure the impact of internal factors is combined with fuzzy logic (based on fuzzy set theory) which evaluates the impact of external forces to produce the allocation priorities. (Fuzzy logic is utilized because it is an excellent method of dealing with problems inherent with uncertainty, such as the impact of external forces. ) A demonstration expert system called Priority Ranking is created in this dissertation to help solve the priority problem. Priority Ranking is different from currently available expert systems in that it uses fuzzy modus ponens as its inference strategy. (Fuzzy modus ponens has been extended to meet the requirements of this research. ) Therefore, the knowledge base of Priority Ranking is organized as a fuzzy production rule system which can be easily and economically established. Priority Ranking also contains an algorithm based on Type II Evidence syllogism (expected possibility or expected certainty) to measure the relative weights of a set of criteria that are established in the knowledge base. An algorithm called RALS is proposed to demonstrate the methodologies developed in this dissertation for resource allocation. It is based on the concept of resource profiles and utilizes the output from the expert system Priority Ranking for its assignment criteria. The typical results contained in this dissertation show that the RALS is a promising algorithm for allocating resources. Although the domain problem of this research was in the construction resource allocation area, the principles and theoretical background developed is not limited to this specific area. Actually, they could be applied to other disciplines of engineering and management.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Crandall, K C |
| Uncontrolled Keywords: | expert system; fuzzy logic; fuzzy set; reasoning; resource allocation; scheduling; uncertainty; weather |
| Index terms: | weather, methodology, construction project, expert system, evidence, strategy, reasoning, knowledge base, scheduling, dissertation, fuzzy set theory, fuzzy set, resource allocation, fuzzy logic |
| Subjects: | data science, resource management, air quality, data management, information systems, management, operations research, research dissemination and communication, evaluation and assessment methods, cognitive psychology, decision-making and optimization, research methods, production management |
| Topics: | Business Strategy, Research Practice, Digital Applications, Time Control, Site Management, Project Management, Sustainability |
| 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