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ANALYSIS OF SELECTION CRITERIA FOR MANUFACTURING EMPLOYEES USING FUZZY- AHP

Year 2008, Volume 9, Issue 1, 141 - 160, 01.03.2008

Abstract

An analytical way to reach the best decision is more preferable in many business platforms. When variables are quantitative and number of criteria is not high, then one can use several analysis tools and make his/her decision and solve the problem. However, many times beside the measurable variables, there exist qualitative variables for decision making problems, or people are supposed to prefer the best among the many choices. Even if only linguistic evaluations may be available for such problems, an analytical way to find the solution systematically to make a successful decision is needed. Fuzzy Analytical Hierarchy Process (Fuzzy AHP) is one of the best ways for deciding among the complex criteria structure in different levels. Fuzzy AHP is a synthetic extension of classical AHP method when the fuzziness of the decision makers is considered. In this paper, the criteria set and their importance for the selection of manufacturing employee in a firm producing shoe machines are analyzed. Finally a systematic solution and decision support are provided for management.

References

  • Bard, J.F. & Sousk, S.F. (1990). A Trade Analysis for Rough Terrain Cargo Handlers Using the AHP: An Example of Group Decision Making. IEEE Transactions on Engineering Management 37 (3): 222–228.
  • Bevilacqua, M. D’Amore, A. & Polonara, F. (2004). A Multi-Criteria Decision Approach to Choosing the Optimal Blanching–Freezing System. Journal of Food Engineering, 63: 253-263.
  • Boender, C.G.E., De Graan, J.G. & Lootsma, F.A. (1989). Multicriteria Decision Analysis with Fuzzy Pairwise Comparisons. Fuzzy Sets and Systems, 29: 133–143.
  • Bouyssou, D., Marchant, T., Pirlot, M., Perny, P., Tsoukias, A. & Vincke, P. (2000). Evaluation Models: A Critical Perspective. Kluwer, Boston.
  • Buckley, J.J. (1985/a). Ranking Alternatives Using Fuzzy Members. Fuzzy Sets and Systems, 15: 21–31.
  • Buckley, J.J. (1985/b). Fuzzy Hierarchical Analysis. Fuzzy Sets and Systems, 17: 233–247.
  • Büyüközkan, G. Feyzioğlu, O. & Nebol, E. (2008). Selection of the Strategic Alliance Partner in Logistics Value Chain International Journal of Production Economics, 113 (1): 148-158.
  • Chang, D.Y. (1996). Applications of the Extent Analysis Method on Fuzzy- AHP. European Journal of Operational Research, 95: 649-655.
  • Chang, D.Y. (1992). Extent Analysis and Synthetic Decision, Optimization Techniques and Applications, World Scientific, Singapore, 1: 352.
  • Cheng, C.H. (1996). Evaluating Naval Tactical Missile Systems by Fuzzy AHP Based on the Grade Value of Membership Function. European Journal of Operational Research, 96: 343-350.
  • Cheng, C.H. Yang, K.L. & Hwang, C.L. (1999). Evaluating Attack Helicopters by AHP Based on Linguistic Variable Weight. European Journal of Operational Research, 116: 423-435.
  • Çakır, O. (2008). On the Order of the Preference Intensities in Fuzzy AHP. Computers & Industrial Engineering, 4: 993-1005
  • Durán, O. & Aguilo, J. (2008). Computer-Aided Machine-Tool Selection Based on A Fuzzy-AHP Approach Expert Systems with Applications, 34 (3): 1787-1794.
  • Huang, C.C. Chu, P.Y. & Chiang, Y.H. (2008). A Fuzzy AHP Application in Government-Sponsored R&D Project Selection. Omega, 36 (6): 1038-1052.
  • Kahraman, C., Cebeci, U. & Ruan, D. (2004). Multi-Criterion Comparison of Catering Service Companies Using Fuzzy AHP: The Case of Turkey. International Journal of Production Economics, 87: 171- 184.
  • Kuo, R.J., Chi, S.C. & Kao, S.S. (2002). A Decision Support System for Selecting Convenience Store Location Through Integration of Fuzzy AHP and Artificial Neural Network, Computers in Industry, 47 (2): 199-214.
  • Kulak, O. & Kahraman, C. (2005). Fuzzy Multi-Criterion Selection Among Transportation Companies Using Axiomatic Design and Analytic Hierarchy Process. Information Sciences, 170: 191-210.
  • Laarhoven, P.J.M. & Pedrycz, W. (1983). A Fuzzy Extension of Saaty’s Priority Theory. Fuzzy Sets and Systems, 11: 229–241.
  • Leung, L.C. & Chao, D. (2000). On Consistency and Ranking of Alternatives in Fuzzy AHP. European Journal of Operational Research, 124: 102-113.
  • Lootsma, F. (1997). Fuzzy Logic for Planning and Decision-Making. Kluwer, Dordrecht.
  • Pohekar, S.D. & Ramachandran, M. (2004). Application of Multi-Criteria Decision Making to Sustainable Energy Planning. A Review Renewable and Sustainable Energy Reviews, 8: 365-381.
  • Ribeiro, R.A. (1996). Fuzzy Multiple Criterion Decision Making: A Review and New Preference Elicitation Techniques. Fuzzy Sets and Systems, 78: 155–181.
  • Saaty, T.L. (1994). Fundamentals of Decision Making and Priority Theory with the Analytical Hierarchy Process. RWS Publications. Pittsburgh.
  • Saaty, T.L. (2001). Decision Making with Dependence and Feedback: Analytic Network Process. RWS Publications. Pittsburgh.
  • Sarkis, J. & Talluri, S. (2004). Evaluating and Selecting E-Commerce Software and Communication Systems for A Supply Chain. European Journal of Operational Research, 159: 318-329.
  • Sheu, J.B. (2008). A Hybrid Neuro-Fuzzy Analytical Approach to Mode Choice of Global Logistics Management. European Journal of Operational Research,189(3): 971-986.
  • Sheu, J.B. (2004). A Hybrid Fuzzy-Based Approach for Identifying Global Logistics Strategies. Transportation Research, 40: 39-61.
  • Taha, H.A. (2003). Operations Research. Pearson Education Inc. Fayetteville.
  • Taylor, B.W. (2004). Introduction to Management Science. Pearson Education Inc. New Jersey.
  • Tolga, E., Demircan, M. L. & Kahraman, C. (2005) Operating System Selection Using Fuzzy Replacement Analysis and Analytic Hierarchy Process. International Journal of Production Economics,97: 89-117.
  • Triantaphyllou, E. & Mann, S.H. (1995). Using The Analytic Hierarchy Process for Decision Making in Engineering Applications: Some Challenges. International Journal of Industrial Engineering: Applications and Practice, 2 (1): 35–44.
  • Wabalickis, R.N. (1988). Justification Of FMS with the Analytic Hierarchy Process. Journal of Manufacturing Systems. 17:175–182.
  • Yu, C.S. (2002). A GP-AHP Method For Solving Group Decision-Making Fuzzy AHP Problems. Computers and Operations Research, 29: 1969–2001.
  • Zaerpour, N., Rabbani, M., Gharehgozli, A.H. & Tavakkoli-Moghaddam, R. (2008). Make-to-Order or Make-To-Stock Decision by a Novel Hybrid Approach Advanced Engineering Informatics, 22 (2): 186- 201.
  • Zhu, K.J., Jing, Y. & Chang, D.Y. (1999). A Discussion On Extent Analysis Method and Applications Of Fuzzy-AHP. European Journal of Operational Research, 116: 450-456.
  • APPENDIX: Question Form for Evaluation
  • Read the following questions and put check marks on the pair wise
  • comparison matrices. If a criterion on the left is more important than the
  • matching one on the right, put your check mark to the left of the
  • importance ‘‘Equal’’ under the importance level you prefer. If a criterion
  • on the left is less important than the matching one on the right, put your
  • check mark to the right of the importance ‘Equal’ under the importance level you. With respect to the main criterion “technical attributes” Question 1: How important is “Occupational information” when it is
  • compared with “Dominating to the tools and equipment”? Question 2: How important is “Occupational information” when it is
  • compared with “Carefulness to the tools and equipment”? Question 3: How important is “Dominating to the tools and
  • equipment” when it is compared with “Carefulness to the tools and equipment”?

ANALYSIS OF SELECTION CRITERIA FOR MANUFACTURING EMPLOYEES USING FUZZY- AHP

Year 2008, Volume 9, Issue 1, 141 - 160, 01.03.2008

Abstract

An analytical way to reach the best decision is more preferable in many business platforms. When variables are quantitative and number of criteria is not high, then one can use several analysis tools and make his/her decision and solve the problem. However, many times beside the measurable variables, there exist qualitative variables for decision making problems, or people are supposed to prefer the best among the many choices. Even if only linguistic evaluations may be available for such problems, an analytical way to find the solution systematically to make a successful decision is needed. Fuzzy Analytical Hierarchy Process (Fuzzy AHP) is one of the best ways for deciding among the complex criteria structure in different levels. Fuzzy AHP is a synthetic extension of classical AHP method when the fuzziness of the decision makers is considered. In this paper, the criteria set and their importance for the selection of manufacturing employee in a firm producing shoe machines are analyzed. Finally a systematic solution and decision support are provided for management.

References

  • Bard, J.F. & Sousk, S.F. (1990). A Trade Analysis for Rough Terrain Cargo Handlers Using the AHP: An Example of Group Decision Making. IEEE Transactions on Engineering Management 37 (3): 222–228.
  • Bevilacqua, M. D’Amore, A. & Polonara, F. (2004). A Multi-Criteria Decision Approach to Choosing the Optimal Blanching–Freezing System. Journal of Food Engineering, 63: 253-263.
  • Boender, C.G.E., De Graan, J.G. & Lootsma, F.A. (1989). Multicriteria Decision Analysis with Fuzzy Pairwise Comparisons. Fuzzy Sets and Systems, 29: 133–143.
  • Bouyssou, D., Marchant, T., Pirlot, M., Perny, P., Tsoukias, A. & Vincke, P. (2000). Evaluation Models: A Critical Perspective. Kluwer, Boston.
  • Buckley, J.J. (1985/a). Ranking Alternatives Using Fuzzy Members. Fuzzy Sets and Systems, 15: 21–31.
  • Buckley, J.J. (1985/b). Fuzzy Hierarchical Analysis. Fuzzy Sets and Systems, 17: 233–247.
  • Büyüközkan, G. Feyzioğlu, O. & Nebol, E. (2008). Selection of the Strategic Alliance Partner in Logistics Value Chain International Journal of Production Economics, 113 (1): 148-158.
  • Chang, D.Y. (1996). Applications of the Extent Analysis Method on Fuzzy- AHP. European Journal of Operational Research, 95: 649-655.
  • Chang, D.Y. (1992). Extent Analysis and Synthetic Decision, Optimization Techniques and Applications, World Scientific, Singapore, 1: 352.
  • Cheng, C.H. (1996). Evaluating Naval Tactical Missile Systems by Fuzzy AHP Based on the Grade Value of Membership Function. European Journal of Operational Research, 96: 343-350.
  • Cheng, C.H. Yang, K.L. & Hwang, C.L. (1999). Evaluating Attack Helicopters by AHP Based on Linguistic Variable Weight. European Journal of Operational Research, 116: 423-435.
  • Çakır, O. (2008). On the Order of the Preference Intensities in Fuzzy AHP. Computers & Industrial Engineering, 4: 993-1005
  • Durán, O. & Aguilo, J. (2008). Computer-Aided Machine-Tool Selection Based on A Fuzzy-AHP Approach Expert Systems with Applications, 34 (3): 1787-1794.
  • Huang, C.C. Chu, P.Y. & Chiang, Y.H. (2008). A Fuzzy AHP Application in Government-Sponsored R&D Project Selection. Omega, 36 (6): 1038-1052.
  • Kahraman, C., Cebeci, U. & Ruan, D. (2004). Multi-Criterion Comparison of Catering Service Companies Using Fuzzy AHP: The Case of Turkey. International Journal of Production Economics, 87: 171- 184.
  • Kuo, R.J., Chi, S.C. & Kao, S.S. (2002). A Decision Support System for Selecting Convenience Store Location Through Integration of Fuzzy AHP and Artificial Neural Network, Computers in Industry, 47 (2): 199-214.
  • Kulak, O. & Kahraman, C. (2005). Fuzzy Multi-Criterion Selection Among Transportation Companies Using Axiomatic Design and Analytic Hierarchy Process. Information Sciences, 170: 191-210.
  • Laarhoven, P.J.M. & Pedrycz, W. (1983). A Fuzzy Extension of Saaty’s Priority Theory. Fuzzy Sets and Systems, 11: 229–241.
  • Leung, L.C. & Chao, D. (2000). On Consistency and Ranking of Alternatives in Fuzzy AHP. European Journal of Operational Research, 124: 102-113.
  • Lootsma, F. (1997). Fuzzy Logic for Planning and Decision-Making. Kluwer, Dordrecht.
  • Pohekar, S.D. & Ramachandran, M. (2004). Application of Multi-Criteria Decision Making to Sustainable Energy Planning. A Review Renewable and Sustainable Energy Reviews, 8: 365-381.
  • Ribeiro, R.A. (1996). Fuzzy Multiple Criterion Decision Making: A Review and New Preference Elicitation Techniques. Fuzzy Sets and Systems, 78: 155–181.
  • Saaty, T.L. (1994). Fundamentals of Decision Making and Priority Theory with the Analytical Hierarchy Process. RWS Publications. Pittsburgh.
  • Saaty, T.L. (2001). Decision Making with Dependence and Feedback: Analytic Network Process. RWS Publications. Pittsburgh.
  • Sarkis, J. & Talluri, S. (2004). Evaluating and Selecting E-Commerce Software and Communication Systems for A Supply Chain. European Journal of Operational Research, 159: 318-329.
  • Sheu, J.B. (2008). A Hybrid Neuro-Fuzzy Analytical Approach to Mode Choice of Global Logistics Management. European Journal of Operational Research,189(3): 971-986.
  • Sheu, J.B. (2004). A Hybrid Fuzzy-Based Approach for Identifying Global Logistics Strategies. Transportation Research, 40: 39-61.
  • Taha, H.A. (2003). Operations Research. Pearson Education Inc. Fayetteville.
  • Taylor, B.W. (2004). Introduction to Management Science. Pearson Education Inc. New Jersey.
  • Tolga, E., Demircan, M. L. & Kahraman, C. (2005) Operating System Selection Using Fuzzy Replacement Analysis and Analytic Hierarchy Process. International Journal of Production Economics,97: 89-117.
  • Triantaphyllou, E. & Mann, S.H. (1995). Using The Analytic Hierarchy Process for Decision Making in Engineering Applications: Some Challenges. International Journal of Industrial Engineering: Applications and Practice, 2 (1): 35–44.
  • Wabalickis, R.N. (1988). Justification Of FMS with the Analytic Hierarchy Process. Journal of Manufacturing Systems. 17:175–182.
  • Yu, C.S. (2002). A GP-AHP Method For Solving Group Decision-Making Fuzzy AHP Problems. Computers and Operations Research, 29: 1969–2001.
  • Zaerpour, N., Rabbani, M., Gharehgozli, A.H. & Tavakkoli-Moghaddam, R. (2008). Make-to-Order or Make-To-Stock Decision by a Novel Hybrid Approach Advanced Engineering Informatics, 22 (2): 186- 201.
  • Zhu, K.J., Jing, Y. & Chang, D.Y. (1999). A Discussion On Extent Analysis Method and Applications Of Fuzzy-AHP. European Journal of Operational Research, 116: 450-456.
  • APPENDIX: Question Form for Evaluation
  • Read the following questions and put check marks on the pair wise
  • comparison matrices. If a criterion on the left is more important than the
  • matching one on the right, put your check mark to the left of the
  • importance ‘‘Equal’’ under the importance level you prefer. If a criterion
  • on the left is less important than the matching one on the right, put your
  • check mark to the right of the importance ‘Equal’ under the importance level you. With respect to the main criterion “technical attributes” Question 1: How important is “Occupational information” when it is
  • compared with “Dominating to the tools and equipment”? Question 2: How important is “Occupational information” when it is
  • compared with “Carefulness to the tools and equipment”? Question 3: How important is “Dominating to the tools and
  • equipment” when it is compared with “Carefulness to the tools and equipment”?

Details

Primary Language Turkish
Journal Section Articles
Authors

Aşkın ÖZDAĞOĞLU This is me

Publication Date March 1, 2008
Published in Issue Year 2008, Volume 9, Issue 1

Cite

Bibtex @ { ifede62856, journal = {Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi}, issn = {1303-0027}, address = {}, publisher = {Dokuz Eylul University}, year = {2008}, volume = {9}, number = {1}, pages = {141 - 160}, title = {ANALYSIS OF SELECTION CRITERIA FOR MANUFACTURING EMPLOYEES USING FUZZY- AHP}, key = {cite}, author = {Özdağoğlu, Aşkın} }
APA Özdağoğlu, A. (2008). ANALYSIS OF SELECTION CRITERIA FOR MANUFACTURING EMPLOYEES USING FUZZY- AHP . Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi , 9 (1) , 141-160 . Retrieved from https://dergipark.org.tr/en/pub/ifede/issue/4598/62856
MLA Özdağoğlu, A. "ANALYSIS OF SELECTION CRITERIA FOR MANUFACTURING EMPLOYEES USING FUZZY- AHP" . Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi 9 (2008 ): 141-160 <https://dergipark.org.tr/en/pub/ifede/issue/4598/62856>
Chicago Özdağoğlu, A. "ANALYSIS OF SELECTION CRITERIA FOR MANUFACTURING EMPLOYEES USING FUZZY- AHP". Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi 9 (2008 ): 141-160
RIS TY - JOUR T1 - ANALYSIS OF SELECTION CRITERIA FOR MANUFACTURING EMPLOYEES USING FUZZY- AHP AU - AşkınÖzdağoğlu Y1 - 2008 PY - 2008 N1 - DO - T2 - Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi JF - Journal JO - JOR SP - 141 EP - 160 VL - 9 IS - 1 SN - 1303-0027- M3 - UR - Y2 - 2022 ER -
EndNote %0 Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi ANALYSIS OF SELECTION CRITERIA FOR MANUFACTURING EMPLOYEES USING FUZZY- AHP %A Aşkın Özdağoğlu %T ANALYSIS OF SELECTION CRITERIA FOR MANUFACTURING EMPLOYEES USING FUZZY- AHP %D 2008 %J Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi %P 1303-0027- %V 9 %N 1 %R %U
ISNAD Özdağoğlu, Aşkın . "ANALYSIS OF SELECTION CRITERIA FOR MANUFACTURING EMPLOYEES USING FUZZY- AHP". Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi 9 / 1 (March 2008): 141-160 .
AMA Özdağoğlu A. ANALYSIS OF SELECTION CRITERIA FOR MANUFACTURING EMPLOYEES USING FUZZY- AHP. Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi. 2008; 9(1): 141-160.
Vancouver Özdağoğlu A. ANALYSIS OF SELECTION CRITERIA FOR MANUFACTURING EMPLOYEES USING FUZZY- AHP. Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi. 2008; 9(1): 141-160.
IEEE A. Özdağoğlu , "ANALYSIS OF SELECTION CRITERIA FOR MANUFACTURING EMPLOYEES USING FUZZY- AHP", Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi, vol. 9, no. 1, pp. 141-160, Mar. 2008