Refine your search
Collections
Co-Authors
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Azadfallah, Mohammad
- A Multiple Attribute Group Decision-Making Model for Selecting the Best Supplier
Abstract Views :333 |
PDF Views:1
Authors
Affiliations
1 Business Studies and Development Office, Saipa Yadak (Saipa after sales services), IR
1 Business Studies and Development Office, Saipa Yadak (Saipa after sales services), IR
Source
International Journal of Business Analytics and Intelligence, Vol 3, No 2 (2015), Pagination: 4-10Abstract
In the current literature, supplier selection is an important Multi Attribute Group Decision Making (MAGDM) problem which heavily contributes to the overall supply chain performance. Several solutions for the above problem are proposed. In this paper, TOPSIS and Borda’s function approach, which is one of these methods, is discussed. So that, in the present model, first TOPSIS is used to find the individual preference ordering. Then, Borda’s function is used to find the collective preference orderings. Finally, a simple example is provided in order to demonstrate its applicability and effectiveness of the proposed method.Keywords
MAGDM, Topsis, Borda’s Function, Supplier Selection Problem.
- Supplier Selection Under Incomplete Preference Information
Abstract Views :213 |
PDF Views:0
Authors
Affiliations
1 Business Studies and Development Office, Saipayadak (Saipa after sales services), IR
1 Business Studies and Development Office, Saipayadak (Saipa after sales services), IR
Source
International Journal of Business Analytics and Intelligence, Vol 4, No 2 (2016), Pagination: 51-57Abstract
Supplier selection is a Multiple Attribute Decision Making (MADM) problem which is affected by several conflicting factors as the suppliers' information and performances are usually incomplete and uncertain. Several MADM methods have been proposed for solving this problem, one of which is the Analytic Hierarchy Process (AHP). One of the advantages of this approach is the ability to make incomplete comparisons to get a final priority vector (particularly, in combination with Harker's method). Therefore, calculating priorities with incomplete preference information on alternatives is the aim of this paper. Finally, a numerical example for supplier selection is given to illustrate the application of the proposed method. The main findings of this study confirm the effectiveness of the proposed methods.Keywords
MADM, AHP, Harker’s Method, Incomplete Preference Information, Supplier Selection Problem.- The Impact of the Scale Elements Alteration on Priorities in Analytic Hierarchy Process Technique
Abstract Views :196 |
PDF Views:0
Authors
Affiliations
1 Business Studies and Development Office, Saipayadak, IR
1 Business Studies and Development Office, Saipayadak, IR
Source
International Journal of Business Analytics and Intelligence, Vol 5, No 1 (2017), Pagination: 43-51Abstract
The present study, presents a comparative analysis of different measurement scales adopted in Analytic Hierarchy Process (AHP), by testing them versus a problem with a known composite answers. Then experimentally, the impact of the different measurement scale elements alteration from three aspects: 1. The limited scale upper bound (up to 9), 2. Changing the scale parameters (a parameters), and 3. Changing the system numbers (from 1, 3…9; to 2, 4…10) on priorities are investigated. The results show that the linear measurement scale has the best performance in comparison to other scales.Keywords
AHP, Measurement Scale, Scale Elements Alteration.References
- Cox, M. A. A. (2009). Multidimensional scaling as an aid for the analytic network and analytic hierarchy process. Journal of Data Science, 7(2009), 381-396.
- Forman, E. H., & Gass, S. I. (2001). The analytic hierarchy process-an exposition. Operations Research, 49, 469-486.
- Ishizaka, A., & Labib, A. (2009). Analytic hierarchy process and expert choice: Benefits and limitations”, OR Insight, 22(4), 201-220.
- Ishizaka, A., Balkenborg, D., & Kaplan T. (2011). Influence of aggregation and measurement scale on ranking a compromise alternative in AHP. The Journal of the Operational Research Society, 62(4), 700-710.
- Ji, P., & Jiang, R. (2003). Scale transitivity in the AHP. The Journal of the Operational Research Society, 54(8), 896-905.
- Luce, R. D. (1997). Quantification and symmetry. British Journal of Psychology, 88, 395-398.
- Monat, J. P. (2009). The benefits of global scaling in multi criteria decision analysis, Judgment and Decision Making, 4(6), 492-508.
- Munshi J. (2014). Method for constructing likert scales, (April 2, 2014). Retrieved from http://ssrn.com/ abstract=2419366 or http://dx.doi.org/10.2139/ ssrn.2419366
- Narens, L. (1981). On the scales of measurement. Journal of Mathematical Psychology, 24, 249-275.
- Narens, L., & Luce, R. D. (1986). Measurement: The theory of numerical assignments. Psychological Bulletin, 99(2), 166-180.
- Pöyhönen, M., Hämäläinen, R. P., & Salo, A. (1997). An experiment on the numerical modeling of verbal ratio statements, 6. Journal of Multi Criteria Decision Analysis, 6.
- Ramanathan, R. (2001). A note on the use of the analytic hierarchy process for environmental impact assessment. Journal of Environmental Management, 63, 27-35.
- Sato, Y. (2001). The impact on scaling on the pair wise comparison of the Analytic Hierarchy Process. ISAHP, 2001, Berns Switzerland, August 2-4, 421-430.
- Saaty, T. L. (2000). Fundamentals of decision making and priority theory. RWS publication, 6.
- Saaty, T. L. (2004). Scales from measurement not measurement from scales. MCDM 2004, Whistler, B.C., Canada, August 6-11, 2004.
- Saaty T. L. (2005). The Analytic Hierarchy and Analytic Network Processes for the measurement of intangible criteria and for decision making”, in Multi Criteria Decision Analysis: state of the art survey (Figueira et al., Eds), Kluwer academic publisher, 345-406.
- Salo, A., & Hamalainen, R. (1997). On the measurement of preferences in the Analytic hierarchy Process. Journal of Multi Criteria Decision Analysis, 6, 309-319.
- Shinohara et al., (2001). Why not use the Entropy method for weight estimations. proceedings-6th ISAHP 2001, Berns, Switzerland, August 2–4, 2001, 431-434.
- Stevens, S. S. (1946). On the theory of scales of measurement. Science, 103(2684).
- Triantaphyllou et al., (1994). On the evaluation and application of different scales for quantifying pair wise comparisons in fuzzy sets. Journal of Multi Criteria Decision Analysis, 3, 133-155.
- Triantaphyllou, E., Shu, B., Sanchez, S. N., & Ray, T. (1998). Multi criteria decision making: an operations research approach. Encyclopedia of Electrical and Electronics Engineering, John Wiley & Sons, Newyork, 15, 175-186.
- Turskis, Z., Zavadskas, E. K., & Peldschus, F. (2009). Multi criteria optimization system for decision making in construction design and management. Engineering Economics, 1(61), 1-17.
- Vachajitpan, P. (2004). Measurements scales and derivation of priorities in pair wise and group decision making, MCDM 2004, Whistler, B.C., Canada, August 6–11, 2004, 1-6.
- Wang, X. (2007). Study of ranking irregularities when evaluating alternatives by using some ELECTRE methods and a proposed new MCDM method based on regret and rejoicing”, MSc. Thesis, Louisiana State University. USA.
- Wedley W. C. (2001). AHP answers to problems with known composite values, ISAHP 2001, Berns Switzerland, August 2-4, 2001, pp. 551-560.
- Wedley, W. C. (2007). AHP/ANP-where is natural zero? ISAHP 2007, VinaDel Mar, Chile, August 3-6, 2007, pp. 1-15.