Multi-objective machine-component grouping in cellular manufacturing: a genetic algorithm

Abstract 

This paper presents a genetic algorithm (GA) approach to the machine-component grouping 
problem with multiple objectives: minimizing costs due to intercell and intracell part 
movements; minimizing the total within cell load variation; and minimizing exceptional 
elements. Manufacturing cells are formed based on production data, e.g. part routing 
sequence, production volume and workload. Also, we will discuss the implication of part 
alternative routings and the method we suggest to deal with it. Special genetic operators 
are developed and multiple experiments are performed. Finally, the results obtained with 
the proposed algorithm on the tested problems are compared with those of others.