This paper presents a genetic algorithm (GA)) approach to the machine-compon- ent 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 pro- duction 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 algor- ithm on the tested problems are compared with those of others.
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