Data Envelopment Analysis; DEA BBC & CCR in MATLAB for Multi-Objective and Multi-Attribute Decision Making

In modern business operations, Data Envelopment Analysis (DEA) serves as a critical tool for evaluating organizational efficiency and formulating optimal decisions. The BBC (Banker, Charnes, Cooper) and CCR (Charnes, Cooper, Rhodes) models represent two fundamental DEA methodologies that can be efficiently implemented using MATLAB. The implementation typically involves constructing linear programming formulations where decision variables represent efficiency scores, with BBC handling variable returns to scale and CCR addressing constant returns to scale scenarios. MATLAB's optimization toolbox provides essential functions like linprog for solving the underlying linear programming problems, while custom scripts can automate data normalization and efficiency frontier calculations. Furthermore, multi-objective decision making (MODM) and multi-attribute decision making (MADM) frameworks complement DEA by enabling comprehensive evaluation across conflicting criteria. These integrated approaches allow businesses to perform Pareto optimality analysis using weighted sum methods or evolutionary algorithms like NSGA-II, and implement attribute weighting techniques such as AHP or TOPSIS through MATLAB's matrix computation capabilities. Mastering these analytical skills with proper code implementation empowers organizations to achieve balanced decision-making and maintain competitive advantage in contemporary business environments.