Loop layout design problem in flexible manufacturing systems using genetic algorithms

A common layout for flexible manufacturing systems is a loop network with machines arranged in a cycle and materials transported in only one direction around the cycle. Traffic congestion is usually used as the measure for evaluating a loop layout, which is defined as the number of times a part traverses the loop before its processing is completed. This paper investigates the problem of designing a loop layout system with genetic algorithms. The essence of the problem is how to determine the order of machines around the loop subject to a set of part-route constraints so as to optimize some measures. A hybrid approach of genetic algorithms and neighborhood search is developed for solving the problem. The proposed method is tested on hypothetical problems. Computational results demonstrate that genetic algorithms can be a promising approach for loop layout design in flexible manufacturing systems. Two typical measures, the minsum and minmax congestion measures, are examined and computational experiments show that the minsum approach outperforms the minmax approach.