Name
Abstract | ||
|---|---|---|
The cell formation problem determines the decomposition of the manufacturing cells of a production system in which machines are assigned to these cells to process one or more part families so that each cell is operated independently and the intercellular movements are minimized or the number of parts flow processed within cells is maximized. In this study, a simple yet effective simulated annealing-based approach, SACF, is proposed to solve the cell formation problem. Considerable efforts are devoted to the design of parts and machine assignment procedures to direct SACF to converge to solutions with good values of grouping efficacy. A set of 25 test problems with various sizes drawn from the literature is used to test the performance of the proposed heuristic algorithm. The corresponding results are compared to several well-known algorithms published. The comparative study shows that the proposed SACF algorithm improves the grouping efficacy for 72% of the test problems. The proposed algorithm should thus be useful to both practitioners and researchers. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.eswa.2007.01.012 | Expert Syst. Appl. |
Keywords | Field | DocType |
cell formation problem,grouping efficacy,simulated annealing algorithm,considerable effort,proposed sacf algorithm,proposed algorithm,well-known algorithm,simulated annealing,test problem,comparative study,manufacturing cell,proposed heuristic algorithm,production system,heuristic algorithm | Cell formation,Simulated annealing,Mathematical optimization,Manufacturing cell,Heuristic (computer science),Computer science,Adaptive simulated annealing,Artificial intelligence,Machine learning | Journal |
Volume | Issue | ISSN |
34 | 3 | Expert Systems With Applications |
Citations | PageRank | References |
58 | 3.63 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tai-Hsi Wu | 1 | 277 | 18.24 |
| Chin-Chih Chang | 2 | 528 | 42.33 |
| Shu-Hsing Chung | 3 | 119 | 10.75 |