GENETIC ALGORITHM IN FUZZY ASSIGNMENT PROBLEM USING YAGER’S RANKING METHOD

Abstract

Fuzzy assignment problems is a special case linear programming model problems that allocate resources to labor or activities on a one-to-one basis, which means that each worker only does one job. This Thesis discussed about Genetic Algorithm which is an optimization algorithm to determine the best alternative solution from a set of solutions that exist through a process as happens in the natural evaluation process. In Genetic Algorithm there are several method used, including the Roulette Wheel Selection method, Partially Mapped Crossover method, and Reciprocal Exchange method to solve fuzzy assignment problem. Genetic Algorithm method can be used to solve fuzzy assignment problems with triangular fuzzy numbers. To convert fuzzy numbers into crisp numbers, use the Yager's Ranking method. Keywords: Fuzzy assignment problem, triangular fuzzy number, Genetic Algorithm, Roulette Wheel Selection method, Partially Mapped Crossover method, Reciprocal Exchange method, Yager’s Ranking method.