

![0_image_0.png](0_image_0.png)

The proposed technique is thus compared with C-Linkage algorithm and results are presented in Table 5 which demonstrates that the proposed methodology is competent to attain better solution than C-
Linkage method and the optimal parameters setting enhances the effectiveness of the technique. Despite of the fact that the solutions obtained are not identical in all instances therefore the sum of similarities are not identical for the test datasets. It further depicts that SAPFOCS technique outperformed the C-Linkage method and obtained 80% improved solutions.

In terms of computational time the proposed SAPFOCS method is efficient and took minimum CPU
time (not more than 12 CPU seconds) for all the datasets tested as reported in Table 5. Table 6 reports the percentage of perfection achieved while developing the part groups by SAPFOCS and compares successfully with C-Linkage solutions. Further Fig. 12 establishes the superiority shown by SAPFOCS over C-Linkage technique. For the largest problem tested SAPFOCS achieved nearly 33.9% improved solution than the C-Linkage technique.

## 5. Conclusions

A state-of-the-art metaheuristic algorithm, SAPFOCS is proposed and employed in this research to form part families. Since part coding and classification techniques are merely adopted in group technology problems, therefore the objective of this study is to utilize the part coding system based on Opitz part coding. 5 test datasets ranging from 5×9 to 27×9 are tested using the aforementioned technique. Due to the NP-complete nature of the reported problems this method is highly effective to produce optimal solutions. Parameters selection is a critical decision for the simulated annealing to be able to obtain near optimal solutions, therefore Taguchi's orthogonal design method is employed to obtain optimal set of parameters for SAPFOCS algorithm. The proposed method is then compared with C-Linkage technique successfully. The objective function utilized in this study is to maximize the sum of similarities among parts in all the part families formed. From the foundation of this research work the number of part families to be formed is considered as constant. As shown in Table 6 SAPFOCS outperformed C-Linkage algorithm in terms of solution quality (sum of similarities value) which is further depicted in Fig. 12 in terms of the percentage of perfections achieved while forming the part families by each of the methods.

This study has assumed identical weightage for each and every attribute, however in formation of part families some attributes could be more significant than the other attributes. Therefore future work could be done by considering fractional weightage for each of the attributes. This work could also be extended by considering operational time and sequence of each part in more complex and realistic environment to develop more effective and robust part families.