Genetic algorithm implementation with fuzzy processing times on non-identical parallel machines

In our daily lives we frequently come across with circumstances that we think of certain but infact are not. Prediction of these circumstances in a systematic manner is possible only aftermaking some assumptions. In a variety of social, economic and technical events uncertaintyand therefore complexity is always present. It is possible to analyze those uncertainties withinthe context of the fuzzy logic theory developed by Zadeh.GA is a search method based on parameter encoding that purposes optimum outcome usingsome of chosen solutions. GA produces continually improving solutions on the basis of naturerule which provides ?living which has best properties?. Because of this, it uses fitnessfunction that determines ?best properties? and cross over operator for producing newsolutions. GA is an evolutionary calculation technique which expands with ArtificialIntelligence.In this study we first summarize the fundamentals of the fuzzy logic theory and thensummarize genetic algorithm method in the scheduling problem with fuzzy processing timeson non-identical parallel machines. After that an application which is analized with fuzzylogic and genetic algorithm is defined. Problem solutions in job sequencing with GA isexamined, by using a program which is prepared in Java Eclipse Europa Program.