Glossary

Glossary

Multi-Criteria Decision Analysis (MCDA) a structured framework for supporting complex decision making, MCDA breaks various decision alternatives (options) into a series of decision criteria (factors) to make comparisons more consistent or logical. This type of model calculates a ranked set of decision alternatives based on decision maker preferences.
Decision Criteria Factors, attributes, or characteristics for consideration when making a complex decision (e.g. price, volume, spatial extent, rate of change).
Decision Alternatives Options, possibilities, or outcomes for consideration when making a decision (e.g. status quo, additional infrastructure investment, sell project). Different decision alternatives may perform differently under varying decision criteria.
Multi-Objective Genetic Algorithm (MOGA) A model developed to identify efficient or optimal scenarios, or combinations of possibilities (in this case, dams in a watershed), using an algorithm designed using genetic principles (parent generation 🡪 propagation 🡪 child generation 🡪 survival 🡪 new parent generation) and production possibility frontiers, where the scenarios that are Pareto-optimal identified as the final outcomes. In the MCDA-MOGA model developed as a part of the Dam Toolbox, Pareto-optimality is used as a guideline, and numerical user preference information drives the set of optimal scenarios.
Pareto optimality A situation in which no one value can increase without causing a decrease in another value. Pareto-optimal solutions are considered economically ‘efficient’, but perhaps not always equitable.