multicriteriaanalys

Multicriteria analysis, often abbreviated as MCA, is a structured approach used to evaluate and rank a set of alternatives based on multiple, often conflicting, objectives or criteria. It is employed when decisions involve more than one attribute or dimension, and where a simple optimization of a single variable is insufficient. MCA provides a framework for systematically considering these diverse factors and their relative importance.

The process typically begins with identifying the decision problem and defining the objectives that need to be met. These objectives are then translated into measurable criteria. Alternatives are generated, and for each alternative, its performance against each criterion is assessed. This assessment can involve quantitative data or qualitative judgments.

A key step in MCA is assigning weights or priorities to the different criteria, reflecting their relative importance to the decision-maker. Various methods exist for this weighting process, such as direct assignment, pairwise comparisons, or analytical hierarchy process (AHP). Once weights are assigned, the performance scores of each alternative are combined with the criterion weights to produce an overall score or ranking for each alternative.

Different MCA methods exist, each with its own mathematical formulation and assumptions. Common methods include Simple Additive Weighting (SAW), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and Elimination and Choice Expressing Reality (ELECTRE). The choice of method depends on the specific problem, the nature of the data, and the preferences of the decision-maker. MCA aids in transparency and justification of complex decisions by making the trade-offs between different criteria explicit.