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

Unlock Powerful Decision-Making with Multi-Criteria Decision-Making (MCDM)

Are you ready to make better, more informed decisions? This comprehensive course introduces you to the world of Multi-Criteria Decision-Making (MCDM), a powerful set of tools used in operations research to objectively evaluate performance based on multiple criteria. Learn to navigate complex choices and find the optimal solution for a wide range of applications.

For the first time on Udemy, gain a practical understanding of MCDM methodologies, bridging the gap between theory and real-world application. This course is designed for students, researchers, and industry professionals looking to enhance their decision-making capabilities.

Our unique, phased approach ensures you master each method:

• Introduction to Theory: Grasp the fundamental principles behind each MCDM technique.
• Hands-on Implementation: Apply these methods using Microsoft Excel – build practical skills immediately.
• Coding with Matlab: Deepen your technical expertise by coding the methodologies in Matlab.

Course Highlights:

• Fundamentals of MCDM: Understand the core concepts and applications of multi-criteria decision analysis.
• Simple Additive Weightage (SAW): A straightforward method for prioritizing criteria.
• Analytic Hierarchy Process (AHP): A structured approach for hierarchical decision-making.
• Analytic Network Process (ANP): Handles complex interdependencies between criteria.
• Technique for Order Preference and Similarity to Ideal Solution (TOPSIS): A popular method for ranking alternatives.
• Elimination Et Choice Translating Reality (ELECTRE): A robust technique for evaluating alternatives based on preferences.
• Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE): A method for ranking alternatives based on preference profiles.
• VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR): A method for finding the best compromise solution.
• Decision-Making Trial and Evaluation Laboratory (DEMATEL): Identifies cause-and-effect relationships in decision problems.
• Grey Relational Analysis (GRA): Handles uncertainty and imprecise data.
• Multi-objective Optimization on the Basis of Ratio Analysis (MOORA): Optimizes solutions with multiple, often conflicting, objectives.
• Complex Proportion Assessment (COPRAS): A method for evaluating alternatives based on proportional assessments.
• Additive Ratio Assessment (ARM-ARAS): Another method for assessing alternatives using ratios.
• Weighted Aggregated Sum Product Assessment (WASPAS): Combines weighted summation and product methods.
• Stepwise Weight Assessment Ratio Analysis (SWARA): A method for determining weights based on ratios.
• COmbinative Distance-based ASsessment (CODAS): Uses distance measures for alternative assessment.
• Evaluation Based on Distance from Average Solution (EDAS): Evaluates alternatives based on their distance from the average solution.
• Measurement Alternatives and Ranking according to COmpromise Solution (MARCOS): A method for ranking alternatives based on compromise solutions.
• CRiteria Importance Through Intercriteria Correlation (CRITIC): Determines the importance of criteria based on correlations.
• Entropy Weighting Technique: Assigns weights to criteria based on uncertainty.

Enhance Your Skills with Coding Tutorials:

The course includes extensive coding tutorials to solidify your understanding and gain practical experience. Master Excel and Matlab for tackling diverse MCDM challenges.

What You'll Achieve:

By the end of this course, you will be able to:

• Confidently apply MCDM techniques to real-world problems.
• Effectively use Excel and Matlab for decision analysis.
• Develop a strong foundation in operations research and optimization.
• Make more informed and objective decisions.