Stratified multi criteria decision making
The stratified multi criteria decision making (SMCDM) method is a multi criteria decision making (MCDM) method proposed in 2018 by Asadabadi.[1] It brings a new insight to MCDM methods by considering the eventualities that may happen while a decision is being made. This method, unlike the existing multiple-criteria decision analysis, considers transition probabilities in the process of computing the weightings of criteria. Possible situations in the near future are considered as states, and the transition probabilities between the states are computed using pairwise comparisons. The method is fundamentally based on the concept of stratification (CST). [2] [3]
An illustrative example[edit]
Imagine that a person wants to rent a room and has the following criteria: location, budget, and the floor area of the house. If this person assigns single weighting of importance to each criterion and scores to the options with respect to each criterion, the best option can be selected using a range of existing MCDM methods. However, there are cases where the person considers some possible events, likely to happen in the near future, such as the likelihood of his girlfriend, for example, moving in, buying a pet, selling his vehicle, getting a loan, receiving a promotion. In each of these situation, the person may have different weightings of importance to assign to the criteria. SMCDM method considers the weightings of importance of the criteria associated with the probability of those events occurring and compute the value of each options, so that the option with the highest value is selected. Through this, the MCDM methods become more reliable and robust. The steps are set out in the figure.
Origin[edit]
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After proposing CST, [4] there have been a few studies trying to expose its applicability. [5] [6] In comparison with them, Asadabadi designed a decision making method as an application of Zadeh's concept.[7] [8] CST is a system that transitions through different strata of data using stationary states.[9] SMCDM uses this characteristic of CST and considers the decision as a system that transitions through different states which are located in different situations.[10] The decision environment is stratified through this and eventualities are considered in the process of making a decision.[11] Integrations of this method with other methods such as such as Analytical Hierarchy Process (AHP),[12] Analytic Network Process (ANP),[13] Elimination and Choice Expressing Reality (ELECTRE),[14][15] Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE),[16] Multi-criteria optimization and compromise solution (VIKOR)],[17] [18] Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS),[19] and Decision Making Trial and Evaluation Laboratory (DEMATEL)[20] addresses various decision making problems.
References[edit]
- ↑ Asadabadi, M. R. (2018). The stratified multi-criteria decision-making (MCDM) method. Knowledge-Based Systems.
- ↑ Fei, L., Xia, J., Feng, Y., & Liu, L. (2019). An ELECTRE-based multiple criteria decision making method for supplier selection using Dempster-Shafer theory. IEEE Access.
- ↑ Wang, H., Yao, J., & Zhang, X. (2018, November). A New Multi-attribute Decision Making Method Based on Interval Normal Type-2 Fuzzy Numbers. In 2018 International Conference on Fuzzy Theory and Its Applications (iFUZZY) (pp. 136-141). IEEE.
- ↑ Zadeh, L. A. (2016). Stratification, target set reachability and incremental enlargement principle. Information Sciences, 354, 131-139.
- ↑ Asadabadi, M. R., Saberi, M., & Chang, E. (2017, July). Logistic informatics modelling using concept of stratification (CST). In Fuzzy Systems (FUZZ-IEEE), 2017 IEEE International Conference on (pp. 1-7). IEEE.
- ↑ Asadabadi, M. R., Saberi, M., & Chang, E. (2018). The Concept of Stratification and Future Applications. Applied Soft Computing.
- ↑ Zadeh, L. A. (2016). Stratification, target set reachability and incremental enlargement principle. Information Sciences, 354, 131-139.
- ↑ Asadabadi, M. R. (2018). The stratified multi-criteria decision-making (MCDM) method. Knowledge-Based Systems.
- ↑ Asadabadi, M. R., Saberi, M., & Chang, E. (2018). The Concept of Stratification and Future Applications. Applied Soft Computing.
- ↑ Asadabadi, M. R. (2018). The stratified multi-criteria decision-making (MCDM) method. Knowledge-Based Systems.
- ↑ Targets of unequal importance using the concept of stratification in a big data environment. International Journal of Fuzzy Systems, 20(4), 1373-1384.
- ↑ Saaty, T. L. (1986). Axiomatic foundation of the analytic hierarchy process. Management science, 32(7), 841-855.
- ↑ Saaty, Thomas L. (1996). Decision Making with Dependence and Feedback: The Analytic Network Process. Pittsburgh, Pennsylvania: RWS Publications. ISBN 0-9620317-9-8 Search this book on
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- ↑ Roy, B. (1968). Classement et choix en présence de points de vue multiples. Revue franįaise d'informatique et de recherche opérationnelle, 2(8), 57-75.
- ↑ Saracoglu, B. O. (2015). "An Experimental Research Study on the Solution of a Private Small Hydropower Plant Investments Selection Problem by ELECTRE III/IV, Shannon's Entropy, and Saaty's Subjective Criteria Weighting". Advances in Decision Sciences. 2015: 1. doi:10.1155/2015/548460.
- ↑ J.P. Brans & P. Vincke (1985). "A preference ranking organisation method: The PROMETHEE method for MCDM". Management Science.
- ↑ Opricovic, S. (1998). Multicriteria optimization of civil engineering systems. Faculty of Civil Engineering, Belgrade, 2(1), 5-21.
- ↑ Opricovic, S., & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European journal of operational research, 156(2), 445-455.
- ↑ Assari, A., Mahesh, T. M., & Assari, E. (2012). Role of public participation in sustainability of historical city: usage of TOPSIS method. Indian Journal of Science and Technology, 5(3), 2289-2294.
- ↑ Fontela, E., & Gabus, A. (1976). The DEMATEL observer.
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