Document Type : Research Paper



The cell formation problem and the group layout problem, both are two important problems in designing a cellular manufacturing system. The cell formation problem is consist of grouping parts into part families and machines into production cells. In addition, the group layout problem is to find the arrangement of machines within the cells as well as the layout of cells.
In this paper, an integrated approach is presented to solve the cell formation, group layout and routing problems. By Considering the dimension of machines, the width of the aisles, and the maximum permissible length of the plant site, a new framework, called spiral layout, is suggested for the layout of cellular manufacturing systems. To extend the applicability of the problem, parameters such as part demands, operation sequences, processing times and machine capacities are considered in the problem formulation. The problem is formulated as a bi-objective integer programming model, in which the first objective is to minimize the total material handling cost and the second one is to maximize the total similarity between machines. As the problem is NP-hard, three metaheuristic algorithms, based on Genetic Algorithm and Simulated Annealing are proposed to solve it. To enhance the performance of the algorithms, a Dynamic Programming algorithm is embedded within them. The performance of the algorithms is evaluated by solving numerical examples from the related literature. Finally, a comparison is carried out between the proposed spiral layout and the linear multi-row layout which has recently presented in the literature


Adil, G.K, Rajamani, D. (2000) “The trade-off between intracell and intercell moves in group technology cell formation”, Journal of Manufacturing Systems, 19, 305–317.
Akturk, M.S. (1996) “A note on the within-cell layout problem based on operation sequences”, Production planning and control, 7, 99–103.
Arıkan, F, Güngör, Z. (2009) “Modeling of a manufacturing cell design problem with fuzzy multi-objective parametric programming”, Mathematical and Computer Modelling, 50, 407–420.
Bayram H., Şahin, R. (2016) “A comprehensive mathematical model for dynamic cellular manufacturing system design and Linear Programming embedded hybrid solution techniques”, Computers and Industrial Engineering, 91, 10–29.
Benjaafar, S. (2002) “Modeling and analysis of congestion in the design of facility layouts”, Management Science, 48, 679–704.
Caux, C., Bruniaux, R., Pierreval, H. (2000) “Cell formation with alternative process plans and machine capacity constraints: A new combined approach”, International Journal of Production Economics, 64, 279–284.
Chan, F.T.S., Lau, K.W., Chan, P.L.Y., Choy, K.L. (2006) “Two-stage approach for machine-part grouping and cell layout problems”, Robotics and Computer-Integrated Manufacturing, 22, 217–238.
Chiang, C.P, Lee, S.D. (2004) “Joint determination of machine cells and linear intercell layout”, Computers and Operations Research, 31, 1603–1619.
Deep, K., Singh, P.K. (2016) “Dynamic cellular manufacturing system design considering alternative routing and part operation tradeoff using simulated annealing based genetic algorithm”, Sādhanā, 41, 1063–1079.
Forghani, K., Mohammadi, M., Ghezavati, V.R. (2015) “Integrated cell formation and layout problem considering multi-row machine arrangement and continuous cell layout with aisle distance”, The International Journal of Advanced Manufacturing Technology, 78, 687–705.
Garbie, I.H., Parsaei, H.R., Leep, H.R. (2008) “Machine cell formation based on a mew similarity coefficient”,Journal of Industrial and Systems Engineering, 1, 318–344.
Garey, M.R, Johnson, D.S. (1979) Computers and intractability: a guide to the theory of NP-completeness, First edition, Freeman.
Golmohammadi, A.M., Bani-Asadi, H., Esmaeeli, H., Hadian, H., Bagheri, F. (2016) “Facility layout for cellular manufacturing system under dynamic conditions”, Decision Science Letters, 5, 407–416.
Jolai, F., Tavakkoli-Moghaddam, R., Golmohammadi, A., Javadi, B. (2012) “An Electromagnetism-like algorithm for cell formation and layout problem”, Expert Systems with Applications, 39, 2172–2182.
Kao, Y., Lin, C.H. (2012) “A PSO-based approach to cell formation problems with alternative process routings”, International Journal of Production Research, 50, 4075–4089.
Khaksar-Haghani, F., Kia, R., Mahdavi, I., Javadian, N., Kazemi, M. (2011) “Multi-floor layout design of cellular manufacturing systems”, International Journal of Management Science and Engineering Management, 6, 356–365.
Lee, S.D, Chiang, C.P. (2001) “A cut-tree-based approach for clustering machine cells in the bidirectional linear flow layout”, International Journal of Production Research, 39, 3491–3512.
Mohammadi, M, Forghani, K. (2014) “A novel approach for considering layout problem in cellular manufacturing systems with alternative processing routings and subcontracting approach”, Applied Mathematical Modelling, 38, 3624–3640.
Mungwattana, A. (2000) Design of cellular manufacturing systems for dynamic and uncertain production requirements with presence of routing flexibility, Ph.D. Thesis submitted to the Faculty of the Virginia Polytechnic Institute and State University.
Solimanpur, M., Vrat, P., Shankar, R. (2004) “A multi-objective genetic algorithm approach to the design of cellular manufacturing systems”, International Journal of Production Research, 42, 1419–1441.
Selim, H., Askin, R., Vakharia, A. (1998) “Cell formation in group technology: review, evaluation and directions for future research”,Computers and Industrial Engineering, 34, 3–20.
Singh, S., Kumar, G. (2015) “Design of instinctive part family formation by genetic algorithm considering alternating routing”, International Journal for Technological Research in Engineering, 3, 2347–4718.
Tompkins, J.A., White, J.A., Bozer, Y.A., Tanchoco, J.M.A. (2003) Facilities planning, Third edition, John Wiley & Sons.
Wemmerlöv, U, Hyer, N.L. (1986) “Procedures for the part family/machine group identification problem in cellular manufacture”, Journal of Operations Management, 6, 125–147.
Wemmerlov, U., John, D. (1997) “Cellular manufacturing at 46 user plants: implementation experiences and performance improvements”, InternationalJournal of Production Research, 35, 29–49.
Wu, X., Chu, C.H., Wang, Y., Yan, W. (2007) “A genetic algorithm for cellular manufacturing design and layout”, European Journal of Operational Research, 181, 156–167.
Wu, T.H., Chung, S.H., Chang, C.C. (2009) “Hybrid simulated annealing algorithm with mutation operator to the cell formation problem with alternative process routings”, Expert Systems with Applications, 36, 3652–3661.
Yin, Y, Yasuda, K. (2005) “Similarity coefficient methods applied to the cell formation problem: a comparative investigation, Computers and Industrial Engineering”, 48, 471–489.
Zeb, A., Khan, M., Khan, N., Tariq, A., Ali, L., Azam, F., Jaffery, S.H.I. (2016) “Hybridization of simulated annealing with genetic algorithm for cell formation problem”, The International Journal of Advanced Manufacturing Technology, 86, 2243–2254.