How to cite this paper
Delgoshaei, A., Parvin, M & Ariffin, M. (2016). Evaluating impact of market changes on increasing cell-load variation in dynamic cellular manufacturing systems using a hybrid Tabu search and simulated annealing algorithms.Decision Science Letters , 5(2), 219-244.
Refrences
Ahkioon, S., Bulgak, A., & Bektas, T. (2009). Cellular manufacturing systems design with routing flexibility, machine procurement, production planning and dynamic system reconfiguration. International Journal of Production Research, 47(6), 1573-1600. doi: 10.1080/00207540701581809
Ariafar, S., Firoozi, Z., & Ismail, N. (2014). A Triangular Stochastic Facility Layout Problem in a Cellular Manufacturing System. Paper presented at the International Conference on Mathematical Sciences and Statistics 2013.
Ariafar, S., & Ismail, N. (2009). An improved algorithm for layout design in cellular manufacturing systems. Journal of Manufacturing Systems, 28(4), 132-139. doi: 10.1016/j.jmsy.2010.06.003
Balakrishnan, J., & Cheng, C. H. (2005). Dynamic cellular manufacturing under multiperiod planning horizons. Journal of manufacturing technology management, 16(5), 516-530.
Banerjee, I., & Das, P. (2012). Group technology based adaptive cell formation using predator–prey genetic algorithm. Applied Soft Computing, 12(1), 559-572.
Boulif, M., & Atif, K. (2006). A new branch- & -bound-enhanced genetic algorithm for the manufacturing cell formation problem. Computers & operations research, 33(8), 2219-2245.
De Jong, K. A. (1975). Analysis of the behavior of a class of genetic adaptive systems.
Defersha, F. M., & Chen, M. (2006). A comprehensive mathematical model for the design of cellular manufacturing systems. International Journal of Production Economics, 103(2), 767-783.
Egilmez, G., & Süer, G. (2014). The impact of risk on the integrated cellular design and control. International Journal of Production Research, 52(5), 1455-1478.
Eiben, A. E., Hinterding, R., & Michalewicz, Z. (1999). Parameter control in evolutionary algorithms. Evolutionary Computation, IEEE Transactions on, 3(2), 124-141.
Elmi, A., Solimanpur, M., Topaloglu, S., & Elmi, A. (2011). A simulated annealing algorithm for the job shop cell scheduling problem with intercellular moves and reentrant parts. Computers & industrial engineering, 61(1), 171-178.
Glover, F. (1986). Future paths for integer programming and links to artificial intelligence. Computers & Operations Research, 13(5), 533-549.
Goncalves Filho, V., & José Tiberti, A. (2006). A group genetic algorithm for the machine cell formation problem. International Journal of Production Economics, 102(1), 1-21.
Gonçalves, J. F., & Resende, M. G. (2004). An evolutionary algorithm for manufacturing cell formation. Computers & industrial engineering, 47(2), 247-273.
Gravel, M., Luntala Nsakanda, A., & Price, W. (1998). Efficient solutions to the cell-formation problem with multiple routings via a double-loop genetic algorithm. European Journal of Operational Research, 109(2), 286-298.
Grznar, J., Mehrez, A., & Felix Offodile, O. (1994). Formulation of the machine cell grouping problem with capacity and material movement constraints. Journal of Manufacturing Systems, 13(4), 241-250.
Gupta, Y. P., Gupta, M. C., Kumar, A., & Sundram, C. (1995). Minimizing total intercell and intracell moves in cellular manufacturing: a genetic algorithm approach. International Journal of Computer Integrated Manufacturing, 8(2), 92-101.
Haleh, H., Iranmanesh, H., & Kor, H. (2009). A new hybrid evolutionary algorithm for solving multi objective cell formation problem. Paper presented at the Computers & Industrial Engineering, 2009. CIE 2009. International Conference on.
Harhalakis, G., Nagi, R., & Proth, J. (1990). An efficient heuristic in manufacturing cell formation for group technology applications. International Journal of Production Research, 28(1), 185-198.
Heragu, S. S. (1989). Knowledge based approach to machine cell layout. Computers & industrial engineering, 17(1), 37-42.
Jeon, G., & Leep, H. R. (2006). Forming part families by using genetic algorithm and designing machine cells under demand changes. Computers & operations research, 33(1), 263-283.
Li, Q., Gong, J., Fung, R. Y., & Tang, J. (2012). Multi-objective optimal cross-training configuration models for an assembly cell using non-dominated sorting genetic algorithm-II. International Journal of Computer Integrated Manufacturing, 25(11), 981-995.
Logendran, R., & Talkington, D. (1997). Analysis of cellular and functional manufacturing systems in the presence of machine breakdown. International Journal of Production Economics, 53(3), 239-256.
Moussa, S. E., & Kamel, M. (1998). A part-machine assignment algorithm for cellular manufacturing with machine capacity constraints. Computers & industrial engineering, 35(3), 483-486.
Nsakanda, A. L., Diaby, M., & Price, W. L. (2006). Hybrid genetic approach for solving large-scale capacitated cell formation problems with multiple routings. European Journal of Operational Research, 171(3), 1051-1070. doi: 10.1016/j.ejor.2005.01.017
Onwubolu, G., & Mutingi, M. (2001). A genetic algorithm approach to cellular manufacturing systems. Computers & industrial engineering, 39(1), 125-144.
Papaioannou, G., & Wilson, J. M. (2010). The evolution of cell formation problem methodologies based on recent studies (1997–2008): Review and directions for future research. European Journal of Operational Research, 206(3), 509-521.
Paydar, M. M., Mahdavi, I., Sharafuddin, I., & Solimanpur, M. (2010). Applying simulated annealing for designing cellular manufacturing systems using MDmTSP. Computers & industrial engineering, 59(4), 929-936.
Rafiee, K., Rabbani, M., Rafiei, H., & Rahimi-Vahed, A. (2011). A new approach towards integrated cell formation and inventory lot sizing in an unreliable cellular manufacturing system. Applied Mathematical Modelling, 35(4), 1810-1819.
Renna, P., & Ambrico, M. (2015). Design and reconfiguration models for dynamic cellular manufacturing to handle market changes. International Journal of Computer Integrated Manufacturing, 28(2), 170-186.
Roeva, O., Fidanova, S., & Paprzycki, M. (2013). Influence of the population size on the genetic algorithm performance in case of cultivation process modelling. Paper presented at the Computer Science and Information Systems (FedCSIS), 2013 Federated Conference on.
Safaei, N., Saidi-Mehrabad, M., & Jabal-Ameli, M. (2008). A hybrid simulated annealing for solving an extended model of dynamic cellular manufacturing system. European Journal of Operational Research, 185(2), 563-592. doi: 10.1016/j.ejor.2006.12.058
Safaei, N., & Tavakkoli-Moghaddam, R. (2009a). An extended fuzzy parametric programming-based approach for designing cellular manufacturing systems under uncertainty and dynamic conditions. International Journal of Computer Integrated Manufacturing, 22(6), 538-548.
Safaei, N., & Tavakkoli-Moghaddam, R. (2009b). Integrated multi-period cell formation and subcontracting production planning in dynamic cellular manufacturing systems. International Journal of Production Economics, 120(2), 301-314.
Sarker, B. R., & Yu, J. (2007). A quadra-directional decomposition heuristic for a two-dimensional, non-equidistant machine-cell location problem. Computers & operations research, 34(1), 107-151.
Schaffer, J. D., Caruana, R. A., Eshelman, L. J., & Das, R. (1989). A study of control parameters affecting online performance of genetic algorithms for function optimization. Paper presented at the Proceedings of the third international conference on Genetic algorithms.
Seifoddini, H., & Djassemi, M. (1993). A dynamic part assignment procedure in machine cell formation. Computers & industrial engineering, 25(1), 473-476.
Seifoddini, H., & Djassemi, M. (1996). Improving the performance of cellular manufacturing by a dynamic part assignment approach. Computers & industrial engineering, 30(4), 719-726.
Tavakkoli-Moghaddam, R., Aryanezhad, M.-B., Safaei, N., & Azaron, A. (2005). Solving a dynamic cell formation problem using metaheuristics. Applied Mathematics and Computation, 170(2), 761-780. doi: 10.1016/j.amc.2004.12.021
Tavakkoli-Moghaddam, R., Aryanezhad, M.-B., Safaei, N., Vasei, M., & Azaron, A. (2007). A new approach for the cellular manufacturing problem in fuzzy dynamic conditions by a genetic algorithm. Journal of Intelligent and Fuzzy Systems, 18(4), 363-376.
Tavakkoli-Moghaddam, R., Javadian, N., Javadi, B., & Safaei, N. (2007). Design of a facility layout problem in cellular manufacturing systems with stochastic demands. Applied Mathematics and Computation, 184(2), 721-728. doi: 10.1016/j.amc.2006.05.172
Tavakkoli-Moghaddam, R., Safaei, N., & Babakhani, M. (2005). Solving a dynamic cell formation problem with machine cost and alternative process plan by memetic algorithms Stochastic Algorithms: Foundations and Applications (pp. 213-227): Springer.
Wang, S., & Sarker, B. R. (2002). Locating cells with bottleneck machines in cellular manufacturing systems. International Journal of Production Research, 40(2), 403-424.
Wang, T.-Y., Wu, K.-B., & Liu, Y. (2001). A simulated annealing algorithm for facility layout problems under variable demand in cellular manufacturing systems. Computers in industry, 46(2), 181-188.
Won, Y., & Currie, K. (2007). Fuzzy ART/RRR-RSS: a two-phase neural network algorithm for part-machine grouping in cellular manufacturing. International Journal of Production Research, 45(9), 2073-2104.
Yu, J., & Sarker, B. R. (2006). A directional decomposition heuristic for one-dimensional, non-equidistant machine-cell location problems. Computers & operations research, 33(1), 64-92.
Zhang, Z. (2011). Modeling complexity of cellular manufacturing systems. Applied Mathematical Modelling, 35(9), 4189-4195.
Zhou, M., & Askin, R. G. (1998). Formation of general GT cells: an operation-based approach. Computers & industrial engineering, 34(1), 147-157.
Ariafar, S., Firoozi, Z., & Ismail, N. (2014). A Triangular Stochastic Facility Layout Problem in a Cellular Manufacturing System. Paper presented at the International Conference on Mathematical Sciences and Statistics 2013.
Ariafar, S., & Ismail, N. (2009). An improved algorithm for layout design in cellular manufacturing systems. Journal of Manufacturing Systems, 28(4), 132-139. doi: 10.1016/j.jmsy.2010.06.003
Balakrishnan, J., & Cheng, C. H. (2005). Dynamic cellular manufacturing under multiperiod planning horizons. Journal of manufacturing technology management, 16(5), 516-530.
Banerjee, I., & Das, P. (2012). Group technology based adaptive cell formation using predator–prey genetic algorithm. Applied Soft Computing, 12(1), 559-572.
Boulif, M., & Atif, K. (2006). A new branch- & -bound-enhanced genetic algorithm for the manufacturing cell formation problem. Computers & operations research, 33(8), 2219-2245.
De Jong, K. A. (1975). Analysis of the behavior of a class of genetic adaptive systems.
Defersha, F. M., & Chen, M. (2006). A comprehensive mathematical model for the design of cellular manufacturing systems. International Journal of Production Economics, 103(2), 767-783.
Egilmez, G., & Süer, G. (2014). The impact of risk on the integrated cellular design and control. International Journal of Production Research, 52(5), 1455-1478.
Eiben, A. E., Hinterding, R., & Michalewicz, Z. (1999). Parameter control in evolutionary algorithms. Evolutionary Computation, IEEE Transactions on, 3(2), 124-141.
Elmi, A., Solimanpur, M., Topaloglu, S., & Elmi, A. (2011). A simulated annealing algorithm for the job shop cell scheduling problem with intercellular moves and reentrant parts. Computers & industrial engineering, 61(1), 171-178.
Glover, F. (1986). Future paths for integer programming and links to artificial intelligence. Computers & Operations Research, 13(5), 533-549.
Goncalves Filho, V., & José Tiberti, A. (2006). A group genetic algorithm for the machine cell formation problem. International Journal of Production Economics, 102(1), 1-21.
Gonçalves, J. F., & Resende, M. G. (2004). An evolutionary algorithm for manufacturing cell formation. Computers & industrial engineering, 47(2), 247-273.
Gravel, M., Luntala Nsakanda, A., & Price, W. (1998). Efficient solutions to the cell-formation problem with multiple routings via a double-loop genetic algorithm. European Journal of Operational Research, 109(2), 286-298.
Grznar, J., Mehrez, A., & Felix Offodile, O. (1994). Formulation of the machine cell grouping problem with capacity and material movement constraints. Journal of Manufacturing Systems, 13(4), 241-250.
Gupta, Y. P., Gupta, M. C., Kumar, A., & Sundram, C. (1995). Minimizing total intercell and intracell moves in cellular manufacturing: a genetic algorithm approach. International Journal of Computer Integrated Manufacturing, 8(2), 92-101.
Haleh, H., Iranmanesh, H., & Kor, H. (2009). A new hybrid evolutionary algorithm for solving multi objective cell formation problem. Paper presented at the Computers & Industrial Engineering, 2009. CIE 2009. International Conference on.
Harhalakis, G., Nagi, R., & Proth, J. (1990). An efficient heuristic in manufacturing cell formation for group technology applications. International Journal of Production Research, 28(1), 185-198.
Heragu, S. S. (1989). Knowledge based approach to machine cell layout. Computers & industrial engineering, 17(1), 37-42.
Jeon, G., & Leep, H. R. (2006). Forming part families by using genetic algorithm and designing machine cells under demand changes. Computers & operations research, 33(1), 263-283.
Li, Q., Gong, J., Fung, R. Y., & Tang, J. (2012). Multi-objective optimal cross-training configuration models for an assembly cell using non-dominated sorting genetic algorithm-II. International Journal of Computer Integrated Manufacturing, 25(11), 981-995.
Logendran, R., & Talkington, D. (1997). Analysis of cellular and functional manufacturing systems in the presence of machine breakdown. International Journal of Production Economics, 53(3), 239-256.
Moussa, S. E., & Kamel, M. (1998). A part-machine assignment algorithm for cellular manufacturing with machine capacity constraints. Computers & industrial engineering, 35(3), 483-486.
Nsakanda, A. L., Diaby, M., & Price, W. L. (2006). Hybrid genetic approach for solving large-scale capacitated cell formation problems with multiple routings. European Journal of Operational Research, 171(3), 1051-1070. doi: 10.1016/j.ejor.2005.01.017
Onwubolu, G., & Mutingi, M. (2001). A genetic algorithm approach to cellular manufacturing systems. Computers & industrial engineering, 39(1), 125-144.
Papaioannou, G., & Wilson, J. M. (2010). The evolution of cell formation problem methodologies based on recent studies (1997–2008): Review and directions for future research. European Journal of Operational Research, 206(3), 509-521.
Paydar, M. M., Mahdavi, I., Sharafuddin, I., & Solimanpur, M. (2010). Applying simulated annealing for designing cellular manufacturing systems using MDmTSP. Computers & industrial engineering, 59(4), 929-936.
Rafiee, K., Rabbani, M., Rafiei, H., & Rahimi-Vahed, A. (2011). A new approach towards integrated cell formation and inventory lot sizing in an unreliable cellular manufacturing system. Applied Mathematical Modelling, 35(4), 1810-1819.
Renna, P., & Ambrico, M. (2015). Design and reconfiguration models for dynamic cellular manufacturing to handle market changes. International Journal of Computer Integrated Manufacturing, 28(2), 170-186.
Roeva, O., Fidanova, S., & Paprzycki, M. (2013). Influence of the population size on the genetic algorithm performance in case of cultivation process modelling. Paper presented at the Computer Science and Information Systems (FedCSIS), 2013 Federated Conference on.
Safaei, N., Saidi-Mehrabad, M., & Jabal-Ameli, M. (2008). A hybrid simulated annealing for solving an extended model of dynamic cellular manufacturing system. European Journal of Operational Research, 185(2), 563-592. doi: 10.1016/j.ejor.2006.12.058
Safaei, N., & Tavakkoli-Moghaddam, R. (2009a). An extended fuzzy parametric programming-based approach for designing cellular manufacturing systems under uncertainty and dynamic conditions. International Journal of Computer Integrated Manufacturing, 22(6), 538-548.
Safaei, N., & Tavakkoli-Moghaddam, R. (2009b). Integrated multi-period cell formation and subcontracting production planning in dynamic cellular manufacturing systems. International Journal of Production Economics, 120(2), 301-314.
Sarker, B. R., & Yu, J. (2007). A quadra-directional decomposition heuristic for a two-dimensional, non-equidistant machine-cell location problem. Computers & operations research, 34(1), 107-151.
Schaffer, J. D., Caruana, R. A., Eshelman, L. J., & Das, R. (1989). A study of control parameters affecting online performance of genetic algorithms for function optimization. Paper presented at the Proceedings of the third international conference on Genetic algorithms.
Seifoddini, H., & Djassemi, M. (1993). A dynamic part assignment procedure in machine cell formation. Computers & industrial engineering, 25(1), 473-476.
Seifoddini, H., & Djassemi, M. (1996). Improving the performance of cellular manufacturing by a dynamic part assignment approach. Computers & industrial engineering, 30(4), 719-726.
Tavakkoli-Moghaddam, R., Aryanezhad, M.-B., Safaei, N., & Azaron, A. (2005). Solving a dynamic cell formation problem using metaheuristics. Applied Mathematics and Computation, 170(2), 761-780. doi: 10.1016/j.amc.2004.12.021
Tavakkoli-Moghaddam, R., Aryanezhad, M.-B., Safaei, N., Vasei, M., & Azaron, A. (2007). A new approach for the cellular manufacturing problem in fuzzy dynamic conditions by a genetic algorithm. Journal of Intelligent and Fuzzy Systems, 18(4), 363-376.
Tavakkoli-Moghaddam, R., Javadian, N., Javadi, B., & Safaei, N. (2007). Design of a facility layout problem in cellular manufacturing systems with stochastic demands. Applied Mathematics and Computation, 184(2), 721-728. doi: 10.1016/j.amc.2006.05.172
Tavakkoli-Moghaddam, R., Safaei, N., & Babakhani, M. (2005). Solving a dynamic cell formation problem with machine cost and alternative process plan by memetic algorithms Stochastic Algorithms: Foundations and Applications (pp. 213-227): Springer.
Wang, S., & Sarker, B. R. (2002). Locating cells with bottleneck machines in cellular manufacturing systems. International Journal of Production Research, 40(2), 403-424.
Wang, T.-Y., Wu, K.-B., & Liu, Y. (2001). A simulated annealing algorithm for facility layout problems under variable demand in cellular manufacturing systems. Computers in industry, 46(2), 181-188.
Won, Y., & Currie, K. (2007). Fuzzy ART/RRR-RSS: a two-phase neural network algorithm for part-machine grouping in cellular manufacturing. International Journal of Production Research, 45(9), 2073-2104.
Yu, J., & Sarker, B. R. (2006). A directional decomposition heuristic for one-dimensional, non-equidistant machine-cell location problems. Computers & operations research, 33(1), 64-92.
Zhang, Z. (2011). Modeling complexity of cellular manufacturing systems. Applied Mathematical Modelling, 35(9), 4189-4195.
Zhou, M., & Askin, R. G. (1998). Formation of general GT cells: an operation-based approach. Computers & industrial engineering, 34(1), 147-157.