--- title: "Alternative (decision-making)" source: "https://systems-analysis.info/eng/Alternative_(decision-making)" wiki: "systems-analysis.info/eng" article: "Alternative_(decision-making)" language: "en" categories: - "Category:Decision theory" - "Category:Decision-making" - "Category:English" - "Category:Science" revision_id: 65 wiki_created_at: 2026-09-06T22:16:56Z wiki_modified_at: 2026-09-06T22:16:56Z downloaded_at: 2026-09-07T22:20:45Z --- # Alternative (decision-making) An **alternative** in the context of [Decision theory](https://systems-analysis.info/eng/Decision_theory "Decision theory") is one of the possible courses of action available to a decision-maker to achieve a goal or solve a problem. In other words, an alternative represents a distinct choice that can be selected from a given set. The existence of at least two alternatives is a necessary condition for a meaningful choice. ## Alternatives in Classical Decision Theory Classical [Decision theory](https://systems-analysis.info/eng/Decision_theory "Decision theory") is based on the assumption of fully rational choice. In this framework, a decision problem is formalized through a set of alternatives, from which a rational agent must choose the best one. Each alternative represents a specific action that the decision-maker can implement. Classical theory typically assumes that the set of alternatives is predefined and known to the decision-maker (DM), and that the DM is capable of **identifying all alternatives and evaluating the consequences of each option**. Under conditions of certainty, each alternative leads to a single, known outcome; under conditions of **uncertainty**, the result depends on external factors (states of nature). A rational strategy is based on optimality criteria: according to the maximum expected value criterion, the alternative with the highest expected value is chosen; a more sophisticated approach is the maximization of expected utility. ## Alternatives in Multi-Criteria Decision Analysis **Multi-criteria decision analysis** (MCDA) evaluates alternatives based on a set of criteria. Given a set of alternatives and criteria, the task is to rank the alternatives or select the best one. The foundation of MCDA is the **alternatives evaluation matrix**, where rows represent alternatives, columns represent criteria, and the cells contain the values Kj(ai). A key concept is **Pareto dominance**: alternative X dominates Y if it is no worse in all criteria and better in at least one. Dominated alternatives are eliminated from consideration. When criteria are in **conflict** (i.e., when an option is better on some metrics but worse on others), a set of Pareto-optimal solutions is formed. Methods for comparing multi-criteria alternatives include: - Constructing a single **utility function** (e.g., a weighted sum of scores) - **Pairwise comparisons** (Saaty's AHP method) - **Outranking methods** (ELECTRE, PROMETHEE) MCDA is often integrated with **handling uncertainty**, where criteria are probabilistic or evaluations are fuzzy, combining elements of decision-making under risk. ## Classification of Alternatives - **Discrete and continuous alternatives.** The set of alternatives can be finite and discrete or infinite (continuous). With continuous parameters, the problem becomes one of mathematical optimization. - **Mutually exclusive and compatible alternatives.** Typically, alternatives are mutually exclusive (only one can be chosen). Sometimes, selecting multiple options or their combinations is allowed, forming a higher-level alternative as a set of simpler ones. - **Dominant and dominated alternatives.** According to the principle of dominance, alternative A dominates B if A is no worse than B on all criteria and is strictly better on at least one. Dominated alternatives are excluded from consideration. Non-dominated alternatives are considered efficient and form the Pareto-optimal set. - **Static and dynamic alternatives.** In simple models, a one-time choice is made. In complex, multi-stage problems, alternatives are considered at each stage, often using a decision tree model. ## Methods for Representing and Comparing Alternatives The following tools are used for decision analysis: **Decision matrix** – a table where rows represent alternatives and columns represent evaluation factors. The main types are: - An 'alternatives × outcomes' matrix (payoff matrix) for problems under uncertainty - An 'alternatives × criteria' matrix for multi-criteria problems **Decision tree** – a graphical diagram of a sequence of decisions and events. It contains: decision nodes (squares) representing choices among alternatives, chance nodes (circles) representing random outcomes, and branches leading to final outcomes with their results. A decision tree allows for the calculation of the value of each strategy using the 'rollback' method, and is particularly useful for sequential decisions. **Preference and utility functions** assign a numerical value to each option, reflecting the degree of preference. They are used to: - Transform criteria with different units into a common scale - Mathematically optimize the choice - Rank alternatives and perform 'what-if' analysis Other tools include influence diagrams, efficiency frontiers, and interactive decision support systems. ## Bounded Rationality and Behavioral Aspects of Choice **Bounded rationality** (a concept by Herbert Simon) describes situations where there is a lack of resources to find the optimal solution. Instead of maximization, the **satisficing** strategy is employed—the search for a "good enough" solution, where an individual chooses the first satisfactory alternative they encounter without analyzing all possible options. **Heuristic choice strategies** show that people use simplified rules: - **Elimination by aspects**: sequentially eliminating alternatives based on important criteria - **Lexicographic choice**: preference is given to the alternative that is best on the most important criterion The **influence of context and the presentation of alternatives** is demonstrated by effects such as: - The **decoy effect**: adding a dominated alternative changes preferences between the main options - The **paradox of choice**: an excess of options makes decision-making more difficult - The **framing effect**: different presentations of the same alternative influence the choice ## See also - [Decision theory](https://systems-analysis.info/eng/Decision_theory "Decision theory") - [Choice (decision-making)](https://systems-analysis.info/eng/Choice_(decision-making) "Choice (decision-making)") - [Decision-making](https://systems-analysis.info/eng/Decision-making "Decision-making") - [Decision-making matrix model](https://systems-analysis.info/eng/Decision-making_matrix_model "Decision-making matrix model") - [Decision-making problem](https://systems-analysis.info/eng/Decision-making_problem "Decision-making problem")