How to cite this paper
Karande, P & Chakraborty, S. (2012). Application of PROMETHEE-GAIA method for non-traditional machining processes selection.Management Science Letters , 2(6), 2049-2060.
Refrences
Behzadian, M., Kazemzadeh, R.B., Albadvi, A., & Aghdasi, M. (2010). PROMETHEE: A comprehensive literature review on methodologies and applications. European Journal of Operational Research, 200, 198-215.
Brans, J.P., & Vincke, P. (1985). A preference ranking organisation method: The PROMETHEE method for MCDM. Management Science, 31, 647-56.
Brans, J.P., Vincke, P., & Mareschal, B. (1986). How to select and how to rank projects: The PROMETHEE method. European Journal of Operational Research, 24, 228-38.
Brans, J.P., & Mareschal, B. (1994). The Promcalc and Gaia decision-support system for multi-criteria decision aid. Decision Support Systems, 12, 297-310.
Chakladar, N.D., & Chakraborty, S. (2008). A combined TOPSIS-AHP-method-based approach for non-traditional machining processes selection. Proc. IMechE Part B: Journal of Engineering Manufacture, 222, 1613-1623.
Chakladar, N.D., Das, R., & Chakraborty, S. (2009). A digraph-based expert system for non-traditional machining processes selection. International Journal of Advanced Manufacturing Technology, 43, 226-237.
Chakraborty, S., & Dey, S. (2006). Design of an analytic-hierarchy-process-based expert system for non-traditional machining process selection. International Journal of Advanced Manufacturing Technology, 31, 490-500.
Chakrabarti, S., Mitra, S., & Bhattacharyya, B. (2007). Development of a management information system as knowledge base model for machining process characterization. International Journal of Advanced Manufacturing Technology, 34, 1088-1097.
Chakraborty, S., & Dey, S. (2007). QFD-based expert system for non-traditional machining processes selection. Expert Systems with Applications, 32, 1208-1217.
Chakraborty, S. (2011). Applications of the MOORA method for decision making in manufacturing environment, International Journal of Advanced Manufacturing Technology, 54, 1155-1166.
Chandraseelan, E.R., Jehadeesan, R., & Raajenthiren, M. (2008). Web-based knowledge base system for selection of non-traditional machining processes. Malaysian Journal of Computer Science, 21, 45-56.
Cogun, C. (1993). Computer-aided system for selection of nontraditional machining operations. Computers in Industry, 22, 169-179.
Cogun, C. (1994). Computer-aided preliminary selection of nontraditional machining processes. International Journal of Machine Tools & Manufacturer, 34, 315-326.
Das, S., & Chakraborty, S. (2011). Selection of non-traditional machining processes using analytic network process. Journal of Manufacturing Systems, 30, 41-53.
De Keyser W., & Peeters, P. (1996). A note on the use of PROMETHEE multicriteria methods. European Journal of Operational Research, 89, 457-461.
Jain, V.K. (2005). Advanced machining processes. New Delhi: Allied Publishers Pvt. Limited.
Pandey, P.C., & Shan, H.S. (2005). Modern machining processes. New Delhi: Tata MacGraw-Hill Publishing Company Limited.
Yurdakul, M., & Cogun, C. (2003). Development of a multi-attribute selection procedure for non-traditional machining processes. Proc. IMechE Part B: Journal of Engineering Engineering Manufacture, 217, 993-1009.
Brans, J.P., & Vincke, P. (1985). A preference ranking organisation method: The PROMETHEE method for MCDM. Management Science, 31, 647-56.
Brans, J.P., Vincke, P., & Mareschal, B. (1986). How to select and how to rank projects: The PROMETHEE method. European Journal of Operational Research, 24, 228-38.
Brans, J.P., & Mareschal, B. (1994). The Promcalc and Gaia decision-support system for multi-criteria decision aid. Decision Support Systems, 12, 297-310.
Chakladar, N.D., & Chakraborty, S. (2008). A combined TOPSIS-AHP-method-based approach for non-traditional machining processes selection. Proc. IMechE Part B: Journal of Engineering Manufacture, 222, 1613-1623.
Chakladar, N.D., Das, R., & Chakraborty, S. (2009). A digraph-based expert system for non-traditional machining processes selection. International Journal of Advanced Manufacturing Technology, 43, 226-237.
Chakraborty, S., & Dey, S. (2006). Design of an analytic-hierarchy-process-based expert system for non-traditional machining process selection. International Journal of Advanced Manufacturing Technology, 31, 490-500.
Chakrabarti, S., Mitra, S., & Bhattacharyya, B. (2007). Development of a management information system as knowledge base model for machining process characterization. International Journal of Advanced Manufacturing Technology, 34, 1088-1097.
Chakraborty, S., & Dey, S. (2007). QFD-based expert system for non-traditional machining processes selection. Expert Systems with Applications, 32, 1208-1217.
Chakraborty, S. (2011). Applications of the MOORA method for decision making in manufacturing environment, International Journal of Advanced Manufacturing Technology, 54, 1155-1166.
Chandraseelan, E.R., Jehadeesan, R., & Raajenthiren, M. (2008). Web-based knowledge base system for selection of non-traditional machining processes. Malaysian Journal of Computer Science, 21, 45-56.
Cogun, C. (1993). Computer-aided system for selection of nontraditional machining operations. Computers in Industry, 22, 169-179.
Cogun, C. (1994). Computer-aided preliminary selection of nontraditional machining processes. International Journal of Machine Tools & Manufacturer, 34, 315-326.
Das, S., & Chakraborty, S. (2011). Selection of non-traditional machining processes using analytic network process. Journal of Manufacturing Systems, 30, 41-53.
De Keyser W., & Peeters, P. (1996). A note on the use of PROMETHEE multicriteria methods. European Journal of Operational Research, 89, 457-461.
Jain, V.K. (2005). Advanced machining processes. New Delhi: Allied Publishers Pvt. Limited.
Pandey, P.C., & Shan, H.S. (2005). Modern machining processes. New Delhi: Tata MacGraw-Hill Publishing Company Limited.
Yurdakul, M., & Cogun, C. (2003). Development of a multi-attribute selection procedure for non-traditional machining processes. Proc. IMechE Part B: Journal of Engineering Engineering Manufacture, 217, 993-1009.