Presentation Uni Toulouse1. MCDA_pz.pptx

supply chain decision making

1. Decision Making theories & MCDA Seminar Dr. Morteza Yazdani Universidad Autónoma de Madrid

2. Headlines

3. How to make a decision…

4. Decision & Decision Making A decision is a choice made between two or more available alternatives. Decision making is the process of choosing the best alternative for reaching objectives.

5. Identifying the Problem

6. Decision making steps: Each decision-making problem contain these 7 steps : Identifying the main problem, what to solve? Finding the related and possible solutions, choices (alternatives) Determining relevant objectives (variables) Gathering information about alternatives & variables Analyzing data with predetermined algorithms Check the results and make a compromise

7. Decision Making Process Identifying the Problem Analyzing the Problem

8. Analyzing the Problem Qualitative Analysis: based on manager ' s judgment and experiences. Quantitative Analysis: based on mathematical and statistical tools

9. Introduction to m ultiple-criteria decision making Multiple-criteria decision-making , popularly known as MCDM, is concerned with those situations where a decision maker has to choose the best alternative from a finite set of alternatives while considering a set of conflicting criteria. The aim of decision support is to assist decision makers to make decisions that are consistent with their goals and preferences. Daily life important questions What option What model What hotel What destination Who is the best candidate Which one fits our requirements … Examples . Finding the best Laptop model Selecting the best investment proposal Analyzing Energy systems Locating a Hospital or an Airport & Thousands other cases

10. What is multi-criteria decision analysis Multi-criteria decision analysis (MCDA) is a formal, structured and transparent decision-making methodology. Its aim is to assist groups or individual decision makers to explore their decisions in the case of complex situations with multiple criteria. MCDA does not provide the ‘ right ’ answer. MCDA does not provide an objective analysis. MCDA does not relieve decision makers of the responsibility of making difficult judgments. MCDA assists the decision maker in confidently reaching a decision by:   enabling decision makers to gain a better understanding of the problem faced; organizing and synthesizing the entire range of information; making explicit and managing the decision maker’s subjectivity ; ensuring that all criteria and decision factors have been taken properly into account.

11. Common elements in MCDM methods Modelling process (interfaces) Aggregation (calculation) Construction Exploitation MCAP OUTPUT INPUT Information (data) Recommendation (Result)

12. MCDM requirement What type of problem is? Ranking, weighting criteria, sorting, classifying? How many alternatives and criterion we have Is that a group decision making? Are we using quantitative data or qualitative? Do we know the weight (importance) of each criterion? Type of decision criteria; beneficia, cost, or target based.

13. Different MCDM tools Simple Additive weighting (SAW) Best – Worst Method (BWM) Analytic Hierarchy Process (AHP) TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) ELECTREv ( ELimination and Choice Expressing REality )   MABAC, EDAS, CODAS, TODIM, MOORA, WASPAS, COPRAS. Combined compromise solution ( CoCoSo )

14. A typical decision-making process ( multiple attributes )

15. Combined Compromise Solution ( CoCoSo ) Decision making methods

16. Developed by Yazdani et al. (2019) * Method for ranking decision alternatives and selecting the best one when the decision maker has multiple criteria (variables) Based on combined techniques Comparability of options Possibility of sensitivity analysis Easily implemented & extended Overview of CoCoSo * Yazdani, M., Zarate, P., Kazimieras Zavadskas, E. and Turskis , Z. (2019), "A combined compromise solution ( CoCoSo ) method for multi-criteria decision-making problems", Management Decision , 57(9), pp. 2501-2519. https://doi.org/10.1108/MD-05-2017-0458

17. The algorithm for CoCoSo 1. Making initial decision Matrix 2. Normalization process

18. The algorithm for CoCoSo 3 . Obtain the total of the weighted normalized matrix and the power weighted normalized matrix for alternatives: 4 . Compute relative weights of the alternatives using the following aggregation strategies, K ia , K ib , K ic 5 . Obtain the total final ranking score:

19. A multiple attribute problem Problem : Olive harvester machines selection Alternatives : 1) Hand-held comb harvesters, 2) Side-pass comb harvesters: 3) Straddle harvesters, 4) Side-by-side shakers, 5) Umbrella shakers, & 6) Tractor-mounted shakers Criteria : C1 Cost (Euro/kg), C2 Vibration ( Hertz) , C3 E ffi ciency, C4 Suitability, C5 Damage, C6 Automation (qualitative) , C7 Work Capacity Hectare/hour, C8 Ergonomics, and C9 Safety Weight of 9 criterion 0.163 0.065 0.109 0.047 0.109 0.020 0.081 0.163 0.244 Evaluation (performance matrix)

20. Solution   Ka rank Kb rank Kc rank K Overal Rank A1 0,1247 6 2,1305 6 0,5894 6 1,4871 6 A2 0,1764 2 2,7417 4 0,834 2 1,9896 4 A3 0,1683 3 3,0788 2 0,7958 3 2,092 2 A4 0,2115 1 3,5814 1 1 1 2,5092 1 A5 0,1682 4 3,0246 3 0,7951 4 2,0688 3 A6 0,1509 5 2,2344 5 0,7134 5 1,6548 5 **The results were tested by sensitivity analysis and compared to other methods

21. Pamucar , D., Deveci , M., Gokasar , I., Işık , M., & Zizovic , M. (2021). Circular economy concepts in urban mobility alternatives using integrated DIBR method and fuzzy Dombi CoCoSo model.  Journal of Cleaner Production ,  323 , 129096. Zavadskas, E. K., Turskis , Z., Šliogerienė , J., & Vilutienė , T. (2021). An integrated assessment of the municipal buildings’ use including sustainability criteria.  Sustainable Cities and Society ,  67 , 102708. Wang, C. N., Nguyen, N. A. T., & Dang, T. T. (2022). Offshore wind power station (OWPS) site selection using a two-stage MCDM-based spherical fuzzy set approach.  Scientific reports , Nature   12 (1), 1-21. Alrasheedi , M., Mardani , A., Mishra, A. R., Streimikiene , D., Liao, H., & Al‐ nefaie , A. H. (2021). Evaluating the green growth indicators to achieve sustainable development: A novel extended interval‐valued intuitionistic fuzzy‐combined compromise solution approach.  Sustainable Development ,  29 (1), 120-142. Ali, S. S., Kaur, R., & Khan, S. (2022). Evaluating sustainability initiatives in warehouse for measuring sustainability performance: an emerging economy perspective.  Annals of Operations Research , 1-40. Cui, Y., Liu, W., Rani, P., & Alrasheedi , M. (2021). Internet of Things (IoT) adoption barriers for the circular economy using Pythagorean fuzzy SWARA- CoCoSo decision-making approach in the manufacturing sector.  Technological Forecasting and Social Change ,  171 , 120951. Maghsoodi , A. I., Soudian , S., Martínez, L., Herrera- Viedma , E., & Zavadskas, E. K. (2020). A phase change material selection using the interval-valued target-based BWM- CoCoMULTIMOORA approach: A case-study on interior building applications.  Applied Soft Computing , 95, 106508. Some recent publication!

22. Summary R anking by CoCoSo gives opportunity to release initial report on decision alternatives, It does not offer absolute solution. The results must be discussed and interpreted . Rank reversal is an effect the has been observed less in CoCoSo It offers possibility to check the consistency (by changing value) It can be extended easily and adopted to fuzzy evaluation Various K values in ranking score can be discussed for proof. For higher number of alternatives ( >= 10), it generates more accurate results than other MCDM tools It has received more than 220 citations in G.scholar and 133 in Web of Science for 3 years  

23. Invitation to submit Serie Book: Disruptive Technologies and Digital Transformations for Society 5.0: https://www.springer.com/series/16676 Serie Book: SUSTAINABLE COMPUTING AND OPTIMIZATION, SCRIVENER: https://scrivenerpublishing.com/series.php?id=Sustainable%20Computing%20and%20Optimization