Optimizing facility layout planning for reconfigurable manufacturing system based on chaos genetic algorithm

Abstract

In order to solve the problems associated with the organization of the dynamic facility layout in a manufacturing workshop, utilizing a chaotic generic algorithm with improved Tent mapping is proposed as a solution. The tent map is used to generate the initial population which is distributed throughout the solution space. Excellent individuals have the Genetic Algorithm optimization with elitist strategy applied to them. Partially matched crossover and mutation operations for single-period-layout encoding string are executed, and adaptive chaotic disturbance is increased to the superior individual. This method is an important innovation in the field of layout optimization by chaotic genetic algorithm. Finally, the paper compares several algorithms by analyzing sample outcomes of their respective implementations. It is also more convenient to verify the T-CGA method, which is better than the traditional method in solving the accuracy and the efficiency.

Keywords

• cga
• dflp
• multi-objective optimization
• partheno genetic algorithm