Multi-Criteria Decision Making (MCDM) Using Matlab and Excel

Focused View

Dr. Reza Moghdani

12:00:25

558 View

1 - Background of MCDMs

1 - Introduction.mp4

21:04

2 - Simple Additive Weightage SAW

2 - Introduction.mp4

04:49

3 - Example 1.mp4

09:03

3 - SAW.xlsx

4 - Example 2.mp4

08:43

5 - Example 3.mp4

10:54

3 - Analytic Hierarchy Process AHP

6 - Introduction.mp4

09:58

7 - Example 1.mp4

10:38

8 - A framework for AHP.mp4

14:46

8 - ahp.xlsx

9 - Coding AHP.mp4

10:49

9 - ahp.zip

10 - Example 2.mp4

08:36

11 - Example 3.mp4

16:03

4 - Analytic Network Process ANP

12 - Introduction.mp4

14:29

13 - Using Supermatrix in AHPExample 1.mp4

05:56

13 - anp.xlsx

14 - Using Supermatrix in AHPExample 2.mp4

06:18

15 - ANPExample 1.mp4

06:44

16 - ANPExample 2.mp4

06:48

5 - Technique for Order Preference and Similarity to Ideal Solution TOPSIS

17 - Introduction.mp4

06:05

18 - Implementation of TOPSIS in Excel.mp4

09:34

18 - Topsis.xlsx

19 - Implementation of TOPSIS in Matlab.mp4

16:27

19 - topsis.zip

6 - Elimination Et Choice Translating Reality ELECTRE

20 - Introduction.mp4

09:03

21 - Implementation of ELECTRE in Excel.mp4

35:08

21 - electre.xlsx

22 - Implementation of ELECTRE in Matlab.mp4

31:40

22 - electre.zip

7 - Preference Ranking Organization Method for Enrichment Evaluations PROMETHEE

23 - Introduction.mp4

06:51

24 - Implementation of PROMETHEE in Excel.mp4

15:23

24 - PROMETHEE.xlsx

25 - Implementation of PROMETHEE in Matlab.mp4

21:25

25 - promethee.zip

8 - VIseKriterijumska Optimizacija I Kompromisno Resenje VIKOR

26 - Introduction.mp4

06:20

27 - Implementation of VIKOR in Excel.mp4

15:34

27 - vikor.xlsx

28 - Implementation of VIKOR in Matlab.mp4

13:33

28 - vikor.zip

9 - DecisionMaking Trial and Evaluation Laboratory DEMATEL

29 - Introduction.mp4

06:19

30 - Implementation of DEMATEL in Excel.mp4

14:47

30 - dematel.xlsx

31 - Implementation of DEMATEL in Matlab.mp4

09:09

31 - dematel.zip

10 - Grey Relational Analysis GRA

32 - Introduction.mp4

06:49

33 - GRA.xlsx

33 - Implementation of GRA in Excel.mp4

12:00

34 - Implementation of GRA in Matlab.mp4

13:02

34 - gra.zip

11 - Multiobjective Optimization on the Basis of Ratio Analysis Method MOORA

35 - Introduction.mp4

04:49

36 - Implementation of MOORA in Excel.mp4

08:16

36 - MOORA.xlsx

37 - Implementation of MOORA in Matlab.mp4

15:07

37 - moora.zip

12 - Complex Proportion Assessment Method COPRAS

38 - Introduction.mp4

05:26

39 - Implementation of COPRAS in Excel.mp4

08:22

39 - copras.xlsx

40 - Implementation of COPRAS in Matlab.mp4

11:43

40 - copras.zip

13 - Additive Ratio Assessment Method ARMARAS

41 - Introduction.mp4

06:30

42 - ARAS.xlsx

42 - Implementation of ARAS in Excel.mp4

06:30

43 - Implementation of ARAS in Matlab.mp4

11:30

43 - aras.zip

14 - Weighted Aggregated Sum Product Assessment WASPAS

44 - Introduction.mp4

05:29

45 - Implementation of WASPAS in Excel.mp4

10:05

45 - waspas.xlsx

46 - Implementation of WASPAS in Matlab.mp4

24:42

46 - waspas.zip

15 - Stepwise Weight Assessment Ratio Analysis SWARA

47 - Introduction.mp4

04:17

48 - Implementation of SWARA in Excel.mp4

04:32

48 - swara.xlsx

49 - Implementation of SWARA in Matlab.mp4

06:38

49 - swara.zip

16 - COmbinative Distancebased ASsessment CODAS

50 - Introduction.mp4

04:41

51 - Implementation of CODAS in Excel.mp4

13:44

51 - codas.xlsx

52 - Implementation of CODAS in Matlab.mp4

14:17

52 - codas.zip

17 - Evaluation Based on Distance from Average Solution EDAS

53 - Introduction.mp4

04:44

54 - Implementation of EDAS in Excel.mp4

10:53

54 - edas.xlsx

55 - Implementation of EDAS in Matlab.mp4

14:27

55 - edas.zip

18 - Measurement Alternatives and Ranking according to COmpromise Solution MARCOS

56 - Introduction.mp4

04:21

57 - Implementation of MARCOS in Excel.mp4

12:07

57 - MARCOS.xlsx

58 - Implementation of MARCOS in Matlab.mp4

16:10

58 - marcos.zip

19 - CRiteria Importance Through Intercriteria Correlation CRITIC

59 - Introduction.mp4

04:03

60 - CRITIC.xlsx

60 - Implementation of CRITIC in Excel.mp4

11:33

61 - Implementation of CRITIC in Matlab.mp4

09:37

61 - critic.zip

20 - Entropy

62 - Introduction.mp4

02:59

63 - Entropy.xlsx

63 - Implementation of Entropy in Excel.mp4

05:56

64 - Implementation of Entropy in Matlab.mp4

04:38

64 - entropy.zip

21 - Combined Compromise Solution CoCoSo

65 - Introduction.mp4

05:06

66 - CoCoSo.xlsx

66 - Implementation of CoCoSo in Excel.mp4

11:39

67 - Implementation of CoCoSo in Matlab.mp4

13:03

67 - cocoso.zip

22 - Fuzzy AHP

68 - An Introduction to Chang extension method.mp4

07:44

Description

A mega course to implement different approaches using Microsoft Excel and Matlab programming to solve MCDM problems

What You'll Learn?

Basic concepts and terms related to Multi-Criteria Decision Making (MCDM)
Basic rules of Matlab programming needed for implementing any MCDMs
Basic Skills of Excel needed for implementing any MCDMs
How to solve any MCDM problem via Matlab and Excel

Who is this for?

Anyone who wants to learn Multi-Criteria Decision Making (MCDM) approaches

Anyone who wants to solve MCDM problms via Excel

Anyone who wants to code MCDM problms in Matlab

What You Need to Know?

Basic knowledge in Multi-Criteria Decision Making (MCDM) approaches

More details

Description
Multiple Criteria Decision-Making (MCDM) has grown as a part of operations research, concerned with designing computational and mathematical tools for supporting the subjective evaluation of performance criteria by decision-makers.
This is the first time that a comprehensive course has been launched on Udemy focusing on a wide range of multi-criteria decision-making (MCDM) approaches. Therefore, we have launched a practical course in the domain of MCDM required for students, researchers and practitioners.
All in all, for any given MCDM approach, Firstly, we introduce the basic theory of that corresponding method, then it is implemented in Microsoft Excel, and finally, we will code the considered example using Matlab language programming.
In Summary, we will discuss the following points and MCDM approaches in detail:
1- Background of MCDMs
2- Simple Additive Weightage (SAW)
3- Analytic Hierarchy Process (AHP)
4- Analytic Network Process (ANP)
5- Technique for Order Preference and Similarity to Ideal Solution (TOPSIS)
6- Elimination Et Choice Translating Reality (ELECTRE)
7- Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE)
8- VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR)
9- Decision-Making Trial and Evaluation Laboratory (DEMATEL)
10- Grey Relational Analysis (GRA)
11- Multi-objective Optimization on the Basis of Ratio Analysis Method (MOORA)
12- Complex Proportion Assessment Method (COPRAS)
13- Additive Ratio Assessment Method (ARM-ARAS)
14- Weighted Aggregated Sum Product Assessment (WASPAS)
15- Stepwise Weight Assessment Ratio Analysis (SWARA)
16- COmbinative Distance-based ASsessment (CODAS)
17- Evaluation Based on Distance from Average Solution (EDAS)
18- Measurement Alternatives and Ranking according to COmpromise Solution (MARCOS)
19- CRiteria Importance Through IntercriteriaCorrelation (CRITIC)
20- Entropy Weighting Technique
21-Combined Compromise Solution (CoCoSo)
22- Fuzzy AHP

This course also includes a large number of coding videos to give you enough opportunity to practice the theory covered in the lecture.
By passing this course, you will become aware of how to use Excel and Matlab on a wide range of MCDM problems, and as a result, you will learn how to handle other MCDM approaches.
Please note that this course will be updated with new MCDM approaches.
Who this course is for:
Anyone who wants to learn Multi-Criteria Decision Making (MCDM) approaches
Anyone who wants to solve MCDM problms via Excel
Anyone who wants to code MCDM problms in Matlab

User Reviews

Rating

average 0

Total votes0

Focused display

My name is Reza Moghdani and I am super excited that you are here to read this section!I am a researcher with more than 7 years of experience in the field of operation research with extensive skill in using wide-range of quantitative approaches in this area.I am also proficient in coding with Matlab, GAMS and developing metaheuristic methods for different applications.I have several publications in the field of operation research problems using metaheuristic approaches and artificial intelligence.To Conclude, I am passionate about operation research and optimization applications in real-world problems and I really like to share my experience with you!

Udemy

View courses Udemy

Students take courses primarily to improve job-related skills.Some courses generate credit toward technical certification. Udemy has made a special effort to attract corporate trainers seeking to create coursework for employees of their company.