Paper Type

Master's Thesis


College of Computing, Engineering & Construction

Degree Name

Master of Science in Computer and Information Sciences (MS)



First Advisor

Dr. Behrooz K. Seyed-Abbassi

Second Advisor

Dr. Roger E. Eggen

Third Advisor

Dr. Robert Roggio

Department Chair

Dr. Asai Asaithambi

College Dean

Dr. Mark A. Tumeo


Knowledge-based expert systems are used to enhance and automate manual processes through the use of a knowledge base and modern computing power. The traditional methodology for creating knowledge-based expert systems has many commonly encountered issues that can prevent successful implementations. Complications during the knowledge acquisition phase can prevent a knowledge-based expert system from functioning properly. Furthermore, the time and resources required to maintain a knowledge-based expert system once implemented can become problematic. There are several concepts that can be integrated into a proposed methodology to improve the knowledge-based expert system lifecycle to create a more efficient process. These methods are commonly used in other disciplines but have not traditionally been incorporated into the knowledge-based expert system lifecycle. A container-loading knowledge-based expert system was created to test the concepts in the proposed methodology. The results from the container-loading knowledge-based expert system test were compared against the historical records of thirteen container ships loaded between 2008 and 2011.