Journal of Supply Chain Management Systems

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Supplier Selection with Interval SAW for a Group of Decision Makers when a Group cannot Reach to Consensus


Affiliations
1 Researcher, Business Studies and Development Office, Saipayadak (Saipa after Sales Services Organisation), Iran, Islamic Republic of
     

   Subscribe/Renew Journal


In the present paper, we investigate the group decision-making problem when decision makers (DMs) cannot reach consensus on a single scale value to represent their joint preference. In order to reflect uncertainty of the given information, interval SAW method and interval criteria weights are applied. To do so, we propose, first the individual preferences are obtained from the respective DMs and then they are aggregated. Whilst the individual preferences are crisp, the aggregated preference is composite intervals,which contain the different views in the group. In sum, this paper focused on the application of a SAW method with interval data to reach maximum degree of consensus in the group decision-making process. Finally, a numerical example for supplier selection is given to illustrate the application of the introduced methods. In addition, the proposed method is compared with an existed method(Borda’s Function approach). Comparative results indicate that results obtained by proposed method were different from those obtained using the existed method. However, the given priorities are not consistent with each other, but it seems the proposed method can more assure the results by applying a systematic model.

Keywords

Group Decision Making, SAW, Entropy, Interval Data, Supplier Selection Problem.
Subscription Login to verify subscription
User
Notifications
Font Size


  • Abdullah L., & Adawiyah, C. W. R. (2014). Simple additive weighting methods of multi criteria decision making and applications: A decade review. International Journal of Information Processing and Management, 5(1), 39-49.

  • Adriyendi. (2015). Multi attribute decision making using simple additive weighting and weighted product in food choice. International Journal of Information Engineering and Electronic Business, 6, 8-14.

  • Afshari, A., Mojahed, M., & Yusuff, R. M. (2010), Simple additive weighting approach to personnel selection problem. International Journal of Innovation, Management and Technology, 1(5), 511-515.

  • Alencar, L. H., Almeida, A. T. D., & Morais, D. C. (2010). A multi criteria group decision model aggregating the preferences of decision makers based on ELECTRE methods. Pesquisa Operacional, 30(3), 687-702.

  • Alinezhad, A., Sarrafha, K., & Amini, A. (2014). Sensitivity analysis of SAW technique: the impact of changing the decision making matrix elements on the final ranking of alternatives. Iranian Journal of Operations Research, 5(1), 82-94.

  • Anisseh, M., & Yusuff, R. B. M. (2011). A fuzzy group decision making model for multiple criteria based on Borda count. International Journal of the Physical Sciences, 6(3), 425-433.

  • Arbel, A., & Vargas, L. (2003). Interval judgments and Euclidean centers. ISAHP 2005, Honolulu, Hawaii, July 8-10, 2003, 1-9.

  • Asgari, M. S., & Abassi, A. (2015). Comparing MADM and artificial neural network methods for evaluating suppliers in multiple sourcing decision. Decision Science Letters, 4(2015), 193-202.

  • Azadfallah, M. (2015). A multiple attribute group decision making model for selecting the best supplier. International Journal of Business Analytics and Intelligence, 3(2), 13-19.

  • Azadfallah, M. (2016a). A supplier selection using a group decision making under multiple criteria by considering individual criteria set. Journal of Supply Chain Management System, 5(2), 38-45.

  • Azadfallah, M. (2016b). A new aggregation rule for ranking suppliers in group decision making under multiple criteria. Journal of Supply Chain Management System, 5(4), 38-48.

  • Boran, E., Genç S., Kurt, M., & Akay, D. (2009). A multi criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert Systems with Applications, 36(2009), 11363-11368.

  • Chen, T. Y. (2012). Comparative analysis of SAW and TOPSIS based on interval-valued fuzzy sets: discussions on score functions and weight constraints. Expert Systems with Applications, 39(2012), 1848-1861.

  • Chatterjee, D., & Chatterjee, R. (2012). Supplier evaluation in manufacturing environment using compromise ranking method with grey interval numbers. International Journal of Industrial Engineering Computations, 3(2012), 393-402.

  • Dhingra R., & Singh, P. (2015). A soft hierarchical process approach for decision making in a supply chain. Journal of Supply Chain Management System, 4(1&2), 72-81.

  • Entani, T. (2009). Interval AHP for a group of decision makers. IFSA-EUSFLAT 2009, ISBN: 978-989-95079-6-8, pp. 155-160.

  • Eshlaghy, A. T., Paydar, N. R., Joda, K., & Paydar, N. R. (2009). Sensitivity analysis for criteria values in decision making matrix of SAW method. International Journal Industrial Mathematics, 1(1), 69-75.

  • Goodridge, W. S. (2016). Sensitivity analysis using Simple additive weighting method. I. J. Intelligent Systems and Applications, 5, 27-33.

  • Hwang C. L., & Yoon, K. (1981). Multiple attribute decision making. Springer Verlag.

  • Hwang, C. L., & Lin, M. J. (1987). Group decision making under multiple criteria: Methods and applications. Springer Verlag.

  • Izadikhah M. (2012). Group decision-making process for supplier selection with TOPSIS method under interval-valued intuitionistic fuzzy numbers. Advances in Fuzzy Systems, 1-14. Doi: 10.1155/2012/407942.

  • Jaberidoost, M., Olfat, L., Hosseini, A., Kebriaeezadeh, A., Abdollahi, M., Alaeddini, M., & Dinarvand, R. (2015). Pharmaceutical supply chain risk assessment in IRAN using Analytic Hierarchy process (AHP) and Simple Additive Weighting (SAW) method. Journal of Pharmaceutical Policy and Practice, 8(9), 1-10.

  • Janic, M., & Reggiani. A. (2002). An application of the Multiple Criteria Decision Making (MCDM) analysis to the selection of a new hub airport. EJTIR, 2(2), 113-141.

  • Jounio, C. (2013). Supplier selection based on AHP methodsupplier in modern business scenario, the complex international business, Bachelor Thesis, supervisor: K. Haapasalo, Helsinki Metopolia University of Applied Sciences, Helsinki.

  • Karami A. (2011). Utilization and comparison of multi attribute decision making techniques to rank Bayesian network options, MSc. Degree project in informatics, supervisor: Riveiro, University of SKOVDE.

  • Kaur, P., & Kumar S. (2013). An intuitionistic fuzzy Simple Additive Weighting (IFSAW) method for selection of score vendor. IOSR Journal of Business and Management (IOSR_JBM), 15(2), 78-81.

  • Kumar, M., Raman, J., & Priya. (2015). A supply chain collaboration model for product development with R&D subsides. Journal of Supply Chain Management System, 4(1&2), 16-42.

  • Leoneti, A. B. (2016), Consideration regarding the choice of ranking multiple criteria decision making methods. Pesquisa Operacional, 36(2), 259-277.

  • Liu F. F., & Hai, H. L. (2005). The voting analytic hierarchy process method for selecting supplier. International Journal Production Economics, 97(2005), 308-317.

  • Lotfi F. H., & Fallahnejad, R. (2010). Imprecise Shannon’s entropy and multi attribute decision-making. Entropy, 12, 53-62.

  • Manokaran, E., Subhashini, S., Senthilvel, S., Muruganandha, R., & Ravischandran, K. (2011). Application of multi criteria decision making tools and validation with optimization technique-case study using TOPSIS, ANN & SAW. International Journal of Management & Business Studies, 1(3), 112-115.

  • Memariani, A., Amini, A., & Alinezhad, A. (2009). Sensitivity analysis of Simple Additive Weighting method (SAW): The results of change in the weight of one attribute on the final ranking of alternatives. Journal of Industrial Engineering, 4(2009), 13-18.

  • Mohaghar, A., Kashef, M., & Khanmohammadi, E. (2014). A novel technique to solve the supplier selection problems: Combination of decision making trial & evaluation laboratory, graph theory and matrix approach methods. International Journal of Industrial Engineering & Production Research, 25(2), 103-113.

  • Nadeem, A. H., Xu, J., & Javed, M. K. (2014). Supplier selection under uncertainty: A detailed case study. International Journal of Sciences: Basic and Applied Research, 15(1), 200-217.

  • Pang, J., & Liang, J. (2012). Evaluation of the results of Multi Attribute group decision making with linguistic information. Omega, 40(2012), 294-301.

  • Podvezko V. (2011). The comparative analysis of MCDA methods SAW and COPRAS. Inzinerine Ekonomika-Engineering Economics, 22(2), 134-146.

  • Pratiwi, D., Lestari, J. P., & Agushinta, R. D. (2014). Decision support system to majority high school student using Simple Additive Weighting method. International Journal of Computer Trends and Technology, 10(3), 153-159.

  • Salehi, A., & Izadikhah, M. (2014). A novel method to extend SAW for decision making problems with interval data. Decision Science Letters, 3(2014), 225-236.

  • Sanayei, A., Mousavi, S. F., & Yazdankhah, A. (2010). Group decision-making process for supplier selection with VIKOR under fuzzy environment. Expert Systems with Applications, 37(2010), 24-30.

  • Sener, Z., & Ozturk, E. (2015). A QFD-based decision model for ship selection in maritime transportation. International Journal of Innovation, Management and technology, 6(3), 202-205.

  • Shirouyehzad, H., Lotfi, F. H., & Dabestani, R. (2013). Aggregating the results of ranking models in data envelopment analysis by Shannon’s entropy: A case study in hotel industry. International Journal of Modeling in Operations Management, 3(2), 149-163.

  • Sorooshian, S. (2015). Alternative method for evaluation of DaGang Deep drilling applications. EJGE, 20(2015), 5209-5212.

  • Tzeng, G. H., & Huang, J. J. (2011). Multiple attribute decision making: Methods and applications. CRC Press.

  • Venkateswarlu, P., & Sarma, B. D. (2016). Selection of supplier by using SAW and VIKOR methods. Journal of Engineering Research and Application, 2(9), 80-88.

  • Wang Y. M., & K. S. Chin (2006). An eigenvector method for generating normalized interval and fuzzy weight. Applied Mathematics and Computation, 181(2), 1257-1275.

  • Wang, Y. M., Greatbanks, R., & Yang, J.-B. (2005). Interval efficiency assessment using data envelopment analysis. Fuzzy Sets and Systems, 153(2005), 347-370.

  • Xu, J., Jiang, B., Tang, L., & Yuan, Y. (2013). A multiple objective coordinated operation model for supply chain with uncertain demand based on fuzzy interval. Research Journal of Applied Sciences, Engineering and Technology, 5(22), 5237-5243.

  • Yue, Z. (2013a). An avoiding information loss approach to group decision making. Applied Mathematical Modeling, 37, 1-2, 112-126.

  • Yue Z. (2013b), Group decision making with Multi attribute interval data. Information Fusion, 14(2013), 551-561.

  • ZeinEldin, R. A. (2012). A decision support system for performance evaluation, IJCA special issue on Computational Intelligence & Information Security, 1-8.


Abstract Views: 247

PDF Views: 0




  • Supplier Selection with Interval SAW for a Group of Decision Makers when a Group cannot Reach to Consensus

Abstract Views: 247  |  PDF Views: 0

Authors

Mohammad Azadfallah
Researcher, Business Studies and Development Office, Saipayadak (Saipa after Sales Services Organisation), Iran, Islamic Republic of

Abstract


In the present paper, we investigate the group decision-making problem when decision makers (DMs) cannot reach consensus on a single scale value to represent their joint preference. In order to reflect uncertainty of the given information, interval SAW method and interval criteria weights are applied. To do so, we propose, first the individual preferences are obtained from the respective DMs and then they are aggregated. Whilst the individual preferences are crisp, the aggregated preference is composite intervals,which contain the different views in the group. In sum, this paper focused on the application of a SAW method with interval data to reach maximum degree of consensus in the group decision-making process. Finally, a numerical example for supplier selection is given to illustrate the application of the introduced methods. In addition, the proposed method is compared with an existed method(Borda’s Function approach). Comparative results indicate that results obtained by proposed method were different from those obtained using the existed method. However, the given priorities are not consistent with each other, but it seems the proposed method can more assure the results by applying a systematic model.

Keywords


Group Decision Making, SAW, Entropy, Interval Data, Supplier Selection Problem.

References