Name
Abstract | ||
|---|---|---|
Available research on the manufacturing cell formation problem shows that most solution approaches are either single- or multiple-solution-agent-based, with a fixed size of solution agents. Frequent problems encountered during the process of solving the cell formation problem include solutions being easily trapped in local optima and bad solution efficiency. Yang and Wang [Yang, F.-C., Wang, Y.-P., 2007. Water flow-like algorithm for object grouping problems. Journal of the Chinese Institute of Industrial Engineers, 24 (6), 475–488] proposed the water flow-like algorithm (WFA) to overcome the shortcomings of single- and multiple-solution -agent-based algorithms. WFA has the features of multiple and dynamic numbers of solution agents, and its mimicking of the natural behavior of water flowing from higher to lower levels coincides exactly with the process of searching for optimal solutions. This paper therefore adopts the WFA logic and designs a heuristic algorithm for solving the cell formation problem. Computational results obtained from running a set of 37 test instances from the literature and newly created have shown that the proposed algorithm has performed better than other benchmarking approaches both in solution effectiveness and efficiency, especially in large-sized problems. The superiority of the proposed WFACF over other approaches from the literature should be attributed to the collaboration of the WFA logic, the proposed prior estimation of the cell size, and the insertion-move. The WFA is a novel heuristic approach that deserves more attention. More attempts on adopting the WFA logic to solve many other combinatorial optimization problems are highly recommended. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.ejor.2010.01.020 | European Journal of Operational Research |
Keywords | Field | DocType |
Manufacturing,Heuristics,Cell formation,Meta-heuristics | Mathematical optimization,Heuristic,Water flow,Cellular manufacturing,Heuristic (computer science),Local optimum,Algorithm,Combinatorial optimization,Local search (optimization),Mathematics,Operations management,Metaheuristic | Journal |
Volume | Issue | ISSN |
205 | 2 | 0377-2217 |
Citations | PageRank | References |
13 | 0.64 | 8 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tai-Hsi Wu | 1 | 277 | 18.24 |
| Shu-Hsing Chung | 2 | 119 | 10.75 |
| Chin-Chih Chang | 3 | 528 | 42.33 |