How to cite this paper
Rao, R. (2012). A note on “An alternative multiple attribute decision making methodology for solving optimal facility layout design selection problems”.International Journal of Industrial Engineering Computations , 3(3), 519-524.
Refrences
Chakraborty, S., & Banik, B. (2007). An analytic hierarchy process (AHP) based approach for optimal facility layout design. IE(I) Journal–PR, 88, 12–18.
Chen, S.J., & Hwang, C.L. (1982). Fuzzy multiple attribute decision making methods and
applications. Lecture notes in economics and mathematical systems. Berlin: Springer-Verlag. Choo,
E.U., & Wedley, W.C. (1985). Optimal criterion weights in repetitive multicriteria decision making. Journal of Operational Research Society, 36(11), 983–992.
Chu, A.T.W., Kalaba, R.E., & Spingarn, K. (1979). A comparison of two methods for determining the weights of belonging to fuzzy sets. Journal of Optimization Theory and Applications, 27(4), 531–538.
Deng, H., Yeh, C.H., & Willis, R.J. (2000). Inter-company comparison using modified TOPSIS with objective weights. Computers & Operations Research, 27(10), 963-973.
Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: the CRITIC method. Computers & Operations Research, 22(7), 763-770.
Edwards, W., & Newman, J.R. (1982). Multiattribute evaluation. California: Sage Publications.
Fan, Z.P. (1996). Complicated multiple attribute decision making: Theory and applications. Ph.D Dissertation, Northeastern University, Shenyang, China.
Hwang, C.L., & Lin, M.J. (1987). Group decision making under multiple criteria: Methods and applications. Berlin: Springer-Verlag.
Kuo, Y., Yang, T., & Huang, Gaun-Wei (2008). The use of grey relational analysis in solving multiple attribute decision making problems. Computers & Industrial Engineering, 55, 80–93.
Maniya, K., & Bhatt, M. G. (2010). A selection of material using a novel type decision-making method: Preference selection index method. Materials and Design, 31(4), 1785–1789.
Maniya, K., & Bhatt, M. G. (2011). An alternative multiple attribute decision making methodology for solving optimal facility layout design selection problems. Computers & Industrial Engineering, 61, 542-549.
Rao, R.V. (2007). Decision making in the manufacturing environment using graph theory and
fuzzy multiple attribute decision making methods. London: Springer-Verlag.
Rao, R. V., & Patel, B.K. (2010). Subjective and objective integrated multiple attribute decision making method for material selection. Materials and Design, 31(10), 4738-4747.
Rao, R. V., Patel, B.K., & Parnichkun, M. (2011). Industrial robot selection using a novel decision making method. Robotics & Autonomous Systems, 59(6), 367-375.
Saaty, T.L. (2000). Fundamentals of decision making and priority theory with the AHP. Pittsburg: RWS Publications.
Shannon, C.E. (1948). A mathematical theory of communication. Bell Systems and Technology Journal, 27, 379–423.
Yang, T., & Hung, C. (2007). Multiple-attribute decision making methods for plant layout design problem. Robotics and Computer-Integrated Manufacturing, 23, 126–137.
Yang, T., & Kuo, C. (2003). A hierarchical AHP/DEA methodology for the facilities layout design problem. European Journal of Operational Research, 147, 128–136.
Chen, S.J., & Hwang, C.L. (1982). Fuzzy multiple attribute decision making methods and
applications. Lecture notes in economics and mathematical systems. Berlin: Springer-Verlag. Choo,
E.U., & Wedley, W.C. (1985). Optimal criterion weights in repetitive multicriteria decision making. Journal of Operational Research Society, 36(11), 983–992.
Chu, A.T.W., Kalaba, R.E., & Spingarn, K. (1979). A comparison of two methods for determining the weights of belonging to fuzzy sets. Journal of Optimization Theory and Applications, 27(4), 531–538.
Deng, H., Yeh, C.H., & Willis, R.J. (2000). Inter-company comparison using modified TOPSIS with objective weights. Computers & Operations Research, 27(10), 963-973.
Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: the CRITIC method. Computers & Operations Research, 22(7), 763-770.
Edwards, W., & Newman, J.R. (1982). Multiattribute evaluation. California: Sage Publications.
Fan, Z.P. (1996). Complicated multiple attribute decision making: Theory and applications. Ph.D Dissertation, Northeastern University, Shenyang, China.
Hwang, C.L., & Lin, M.J. (1987). Group decision making under multiple criteria: Methods and applications. Berlin: Springer-Verlag.
Kuo, Y., Yang, T., & Huang, Gaun-Wei (2008). The use of grey relational analysis in solving multiple attribute decision making problems. Computers & Industrial Engineering, 55, 80–93.
Maniya, K., & Bhatt, M. G. (2010). A selection of material using a novel type decision-making method: Preference selection index method. Materials and Design, 31(4), 1785–1789.
Maniya, K., & Bhatt, M. G. (2011). An alternative multiple attribute decision making methodology for solving optimal facility layout design selection problems. Computers & Industrial Engineering, 61, 542-549.
Rao, R.V. (2007). Decision making in the manufacturing environment using graph theory and
fuzzy multiple attribute decision making methods. London: Springer-Verlag.
Rao, R. V., & Patel, B.K. (2010). Subjective and objective integrated multiple attribute decision making method for material selection. Materials and Design, 31(10), 4738-4747.
Rao, R. V., Patel, B.K., & Parnichkun, M. (2011). Industrial robot selection using a novel decision making method. Robotics & Autonomous Systems, 59(6), 367-375.
Saaty, T.L. (2000). Fundamentals of decision making and priority theory with the AHP. Pittsburg: RWS Publications.
Shannon, C.E. (1948). A mathematical theory of communication. Bell Systems and Technology Journal, 27, 379–423.
Yang, T., & Hung, C. (2007). Multiple-attribute decision making methods for plant layout design problem. Robotics and Computer-Integrated Manufacturing, 23, 126–137.
Yang, T., & Kuo, C. (2003). A hierarchical AHP/DEA methodology for the facilities layout design problem. European Journal of Operational Research, 147, 128–136.