Integrating Developed Evolutionary Algorithm and Taguchi Method for Solving Fuzzy Facility’s Layout Problem

The quadratic assignment problem (QAP) is one of the combinatorial optimization problems belonging to the NP-hard problems’ class and has a wide application in the placement of facilities. Thus far, many efforts have been made to solve this problem and countless algorithms have been developed to achieve optimal solutions, one of which is the Genetic Algorithm (GA). This paper aims at finding a suitable layout for the facilities of an industrial workshop by using a developed genetic algorithm and Taguchi Method (TM). The research method in the current study is mathematical modeling and data was analyzed using genetic algorithm in Minitab and MATLAB. The results show that the Developed Genetic Algorithm (DGA) is highly efficient, as it has the power to discover many optimal solutions. Therefore, according to the obtained results, it is recommended that when the genetic algorithm (GA) is used to solve problems, it is better to run this algorithm several times; because the proposed method increases the variety of answers in the genetic algorithm and power for discovering the optimal solution becomes more.

Keywords:

fuzzy sets , Optimization , Facility's Layout , quadratic assignment problem