MCDA

Multi-Criteria Decision Analysis (MCDA) refers to a family of formal methods used to evaluate and compare alternatives across multiple criteria, often with trade-offs among conflicting objectives. MCDA seeks to produce a ranked order or choice that reflects stakeholder preferences and strategic goals rather than a single objective.

MCDA methods vary in approach, but many are grouped into value-based, outranking, and distance/compromise families. Prominent techniques include analytic hierarchy process (AHP), TOPSIS, ELECTRE, PROMETHEE, and various multi-attribute utility theory (MAUT) formulations. The choice of method depends on the decision context, data types, and whether explicit trade-offs are desired.

Typical MCDA process steps include: defining the decision problem and objectives; selecting relevant criteria; identifying alternatives; eliciting preferences and assigning weights or value functions; scoring each alternative against criteria; aggregating scores to obtain a final ranking; and performing sensitivity or robustness analyses.

Applications span environmental planning and impact assessment, healthcare policy and prioritization, energy and transportation planning, engineering design, and public sector decision making. MCDA supports transparent decision making by making trade-offs explicit and documenting assumptions.

Limitations include subjectivity in weighting and scoring, dependence on the quality and scale of data, potential compensation between criteria, and sensitivity to methodological choices. Effective MCDA typically combines methodological rigor with stakeholder involvement and clear documentation.