參考文獻 |
Adil, G. K., Rajamani, D. and Strong, D., 1996, “Cell formation considering alternate routings,” International Journal of Production Research, vol. 34, no. 5, pp. 1361-1380.
Benjaafar, S., 1992, “Modeling and analysis of flexibility in manufacturing systems,” Ph.D. Thesis, School of Industrial Engineering, Purdue University, West Lafayette, IN47907, USA.
Bezdek, J. C.,1981,”Pattern Recognition with Fuzzy Objective Function Algorithms(New York:Plenum Press)
Burbidge, J. L., 1971, “Production flow analysis,” The Production Engineer, April/May, pp. 139-152.
Burbidge, J. L., 1977, “A manual method of production flow analysis,” The Production Engineer, Oct, pp. 34-38.
Burbidge, J. L., 1989, “Production flow analysis─for planning group technology,” Oxford: Clarendon Press.
Burke, L. I. and Kamal, S., 1992, “Fuzzy art and celluar manufacturing,” ANNIE 92 Conference Proceedings, pp. 779-784.
Carpenter, G. A. and Grossberg, S., 1987, “A massively parallel architecture for a self-organizing neural pattern recognition machine,” Computer Vision Graphics Image Process, vol. 37, pp. 54-115.
Carpenter, G. A. and Grossberg, S., 1987, “ART2:self-organization of stable category recognition codes for analog input patterns,” Applied Optics, vol. 26, pp. 4919-4930.
Carpenter, G. A. and Grossberg, S., 1990, “ART3:hierarchical search using chemical transmitters in self-organization pattern recognition architectures,” Neural Networks, vol. 3, no.2, pp. 129-152.
Carpenter, G. A. and Grossberg, S., 1991, “Fuzzy ART:Fast stable learning and categorization of analog parrerns by an adaptive reasonanace system,” Neural Networks, vol. 4, pp. 759-771.
Carrie, A. S., 1973, “Numerical taxonomy applied to group technology and plant layout,” International Journal of Production Research, vol. 27, no. 10, pp. 1795-1810.
Chan, H. M. and Miller, D. A., 1982, “Direct clustering algorithm for group formation in cellular manufacturing,” Journal of Manufacturing Systems, vol. 1, no. 10, pp. 65-74.
Chandrasekharan, M. P. and Rajagopalan, R., 1986, “MDROC: an extension of rank order clustering for group technology,” International Journal of Production Research, vol. 24, no. 5, pp. 1221-1233.
Chu, C. H., 1997, “An improved neural network for manufacturing cell formation,” Decision Support Systems, vol. 20, pp. 279-295.
Chu, C. H. and Hayya, J. C., 1991, “A fuzzy Clustering approach to manufacturing cell formation,” International Journal of Production Research, vol. 29, no. 7, pp.1475-1487
CPLEX, 1999, Using the CPLEX Callable Library and CPLEX Mixed Integer Library. (Incline Village, NV: CPLEX Optimization).
DeWitte, J., 1980, “The use of similarity coefficients in production flow analysis,” International Journal of Production Research, vol. 18, no. 4, pp. 503-514.
El-Essawy, I. G. K. and Torrance, J., 1972, “Component flow analysis─an affective approach to production system’s design,” The Production Engineer, Amy, pp. 165-170.
Gindy, N. N. Z., Ratchev, T. M. and Case, K., 1995, “Component grouping for GT applications- a fuzzy clustering approach with validity measure, ”International Journal of Production Research, vol.33, no.9, pp.2493-2509
Gunasingh, K. R. and Lashkari, R. S., 1989, “Machine grouping problem in cellular manufacturing systems─an integer programming approach,” International Journal of Production Research, vol. 27, no. 9, pp. 1465-1473.
Güngör, Z. and Arikan F., 2000,”Application of fuzzy decision making in part-machine grouping,” International Journal of Production Economics, vol.63, Iss.2, pp.181-193.
Ho, Y. C. and Moodie, C. L., 1996, “Solving cell formation problems in a manufacturing environment with flexible processing and outing capabilities,” International Journal of Production Research, vol. 34, no. 10, pp. 2901-2923.
Islam, K. M. S. and Sarker, B. R., 2000, “A similarity coefficient measure and machine-parts grouping in cellular manufacturing systems,” International Journal of Production Research, vol. 38, no. 3, pp.699-720
Josien, K.and Liao, T. W., 2000, “Integrated use of fuzzy c-means and fuzzy KNN for GT part family and machine cell formation,” International Journal of Production Research, vol.38, no. 15, pp.3513-3536
Kamal, S. and Burke, L. I., 1996, “A new neural network-based clustering algorithm for group technology,” International Journal of Production Research, vol. 34, no. 4, pp. 919-946.
Kao, Y. and Moon, Y. B., 1991, “A unified group technology implementation using the backpropagation learning rule of neural networks,” Computers Industrial Engineering, vol. 20, no. 4, pp. 425-437.
King, J. R. and Nakornchai, V., 1982, “Machine-component group formation in group technology: review and extension,” International Journal of Production Research, vol. 20, no. 2, pp. 117-133.
King, J. R., 1980, “Machine-component grouping in production flow analysis: an approach using a rank order clustering algorithm,” International Journal of Production Research, vol. 18, no. 2, pp. 213-232.
Kusiak, A. and Chung, Y., 1994, “Grouping parts with a neural network,” Journal of Manufacturing Systems, vol. 13, no. 4, pp. 262-275.
Kusiak, A. and Ibrahim, W. N., 1988, “Knowledge-based System for Group Technology (KGBT),” International Conference on Computer Integrated Manufacturing, New York, May, pp. 184-193.
Kusiak, A. and Lee, H., 1996, “Neural computing-based design of components for cellular manufacturing,” International Journal of Production Research, vol. 34, no. 7, pp. 1777-1790.
Leem, C. W. and Chen, J. J.G., 1996,”Fuzzy-set based machine-cell formation in cellular manufacturing,” Journal of Intelligent Manufacturing, vol. 7, pp.355-364
Lin, G. Y. and Solberg, J. J., 1991, “Effectiveness of Flexible Routing Control,” International Journal of Flexible Manufacturing System, no. 3, pp. 189-211.
Lin, G. Y., 1993, “A distributed production control for intelligent manufacturing systems,” PhD thesis, Purdue University.
Malakooti, B. and Yang, Z., 1995, “A variable-parameter unsupervised learning clustering neural network approach with application to machine-part group formation,” International Journal of Production Research, vol. 33, no. 9, pp. 2395-2413.
McAuley, J., 1972, “Machine grouping for efficient production,” The Production Engineer, February, pp. 53-57.
Moon, Y. B. and Chi, S. C., 1991, “Generalized part familary formation using neural network techniques,” Journal of Manufacturing Systems, vol. 11, no. 3, pp. 149-159.
Moon, Y. B., 1990, “An interactive activation and competition model for machine-part family formation in group technology,” Proceeding of the International Joint Conference on Neural Networks, Washington DC, vol. 2, pp. 667-670.
Mosier, C. T., 1985, “An experiment investigating the application of clustering procedures and similarity coefficients to the GT machine cell formation problem,” International Journal of Production Research, vol. 27, no. 10, pp. 1811-1835.
Mukhopadhyay, S. K., Babu, K. R. and Sai, K. V. V., 2000, “Modified Hamiltonian chain:a graph theoretic approach to group technology,” International Journal of Production Research, vol.38, no.11, pp.2459-2470
Piplani, P. and Talavage, J., 1995, “Launching and dispatching strategies for multi-criteria control of closed manufacturing systems with flexible routeing capability,” International Journal of Production Research, vol. 33, no. 8, pp. 2181-2196.
Rajamani, D., Singh, N. and Aneja, Y. P., 1990, “Integrated design of cellular manufacturing systems in the presence of alternative process plans,” International Journal of Production Research, vol. 28, no. 8, pp. 1541-1554.
Rardin, L. R., 1998, “Optimization in operations research,” Prentice Hall, Upper Saddle River, N.J.
Sarker, B. R. and Xu, Y., 2000,”Designing multi-product lines: job routing in cellular manufacturing systems,” IIE Transactions, vol. 32, no.3, pp.219-235
Shafer, S. M. and Roger, D. F. , 1993, “Siomiliarity and distance measures for cellular manufacturing, part1:a survey, ” International Journal of Production Research, vol. 31, no. 5, pp. 1133-1142.
Su, C. T. and Hsu, C. M., 1998, “Manufacturing cell formation using genetic algorithm VS. neural network,” Journal of Chinese Institute of Industrial Engineers, vol. 15, no. 2, pp. 127-139.
Suresh, N. C., Slomp, J. and Kaparthi, S., 1995, “The capacitated cell formation problem: a new hierarchical methodology,” International Journal of Production Research, vol. 33, no. 6, pp. 1761-1784.
Tan, K. Y., 1990, “An operation sequence based similarity coefficient for part families formations,” Journal of Manufacturing Systems, vol. 9, no. 1, pp. 55-68.
Vakharia, A. J. and Wemmerlov, U., 1990, “Designing a Cellular Manufacturing System: A Material Flow Approach Based on Operations Sequences,” IIE Transaction, vol. 22, no. 1, pp. 84-97.
Wu, H. l., Venugopal, R. and Barash, M. M., 1986, “Design of cellular manufacturing system : a syntactice pattern recognition approach,” Journal of Manufacturing Systems, vol. 5, no. 2, pp. 81-87.
Wu, N. and Salvendy, G., 1999,”An efficient heuristic for the design of cellular manufacturing systems with multiple identical machines,” International Journal of Production Research, vol. 37, no.15, pp.3519-3540
Yoshikawa, K., Fukuta, T., Morukawa, K., Takahashi, K. and Nakamura, N., 1997, “A neural network approach to the cell formation problem,” The 14th International Conference on Production Research, Osaka Japan, August 4-8, pp. 1100-1103.
Timothy, J. R.,1997, Fuzzy logic with engineering applications, McGraw Hill, New York.
何應欽、林裕智, 1998, “在具製程與途程彈性之製造環境下之以類似係數為基礎的單元成型法,” 中國工業工程學會八十七年年會, 台灣彰化(大葉大學)。
何應欽、楊家興,1999, “在具製程與途程彈性之製造環境下之以機器使用機率為基礎的單元成型法,” 中國工業工程學會八十八年年會, 台灣新竹(清華大學)。 |