## Abstract

The cell formation problem determines decomposition of the manufacturing cells of a production system. Machines are assigned to the cells to process one or more part families so that each cell is operated independently and the inter-cellular movements are minimized. This paper proposes a new algorithm for grouping problems (bin packing, graph coloring, scheduling, etc.) which is a grouping version of an almost new algorithm (league championship algorithm (LCA)), and we used it to solve benchmarked instances of cell formation problem posing as a grouping problem. To evaluate the effectiveness of our approach, we borrow a set of 35 most widely used benchmark problem instances from literature and compare the performance of grouping LCA (GLCA) and several well-known algorithms published. The proposed algorithm can reach the best solution for 29 of the 35 benchmark problems and differs with the best-known solution of three benchmark problems only with 0.7 % average gap. We also used a new method to find the number of initial cells. The results show that GLCA may hopefully be a new approach for such kinds of difficult-to-solve problems. Moreover, a real-world industrial case is provided to show how the proposed algorithm works. Considering the performance of the GLCA algorithm on all test problems, the proposed algorithm should thus be useful to both practitioners and researchers.

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Noktehdan, A., Seyedhosseini, S. & Saidi-Mehrabad, M. A Metaheuristic algorithm for the manufacturing cell formation problem based on grouping efficacy.
*Int J Adv Manuf Technol* **82, **25–37 (2016). https://doi.org/10.1007/s00170-015-7052-z

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### Keywords

- Cell formation problem
- Grouping genetic algorithm
- League championship algorithm