A Comparative Study of Three Artificial Intelligence Techniques: Genetic Algorithm, Neural Network, and Fuzzy Logic, on Scheduling Problem

Abstract

Since scheduling process is an important and complicated process, many programmers have been searching and working on this issue for years. Still many researchers in the academic institutes are trying to find the best solution. As time is money, time optimization is the most important point, which makes the researchers develop a system for scheduling at the best way by applying the best solution. Once look at the production line of a factory or the number of classes and classrooms in a university, shows that having a time table in these places not only helps regulate things, but also it helps optimize consumption of resources such as time and energy within the constraints and limitations. This paper explains and reviews the three techniques, which have previously been applied on scheduling domain by researchers and developers among several artificial intelligence techniques. These three techniques i.e. Genetic Algorithm, Neural Network and Fuzzy Logic will be defined, discussed and compared in terms of some measures.