MATHEMATICAL FOUNDATIONS OF DECISION MAKING

Lecture



As a result of studying this section, the student must: know

  • • the methods underlying decision theory;
  • • the systems of axioms on which measurement theory is based;
  • • the attributes, indicators and criteria for describing and assessing the state and forecasting the development of socio-economic systems;
  • • scales for measuring the characteristics of objects;
  • • various ways of modeling a problem situation;
  • • the general statement of the decision-making problem;
  • • the mathematical model of the decision-making problem;
  • • the construction of a system of preferences;
  • • choice functions;
  • • properties of criteria — completeness, non-redundancy, measurability;
  • • the concept of an indifference map and the aggregate criterion of a multi-criteria decision-making problem;
  • • solutions dominated in the Pareto sense;
  • • Pareto optimality;
  • • the axiom;
  • • the Pareto—Edgeworth set and the Pareto front;
  • • the angle of preference; be able to
  • • point out the differences and interrelation of the methodological foundations of scientific disciplines;
  • • correctly choose the type of scale for measuring the properties of the object, phenomenon or process under study;
  • • formulate and correctly choose ways of modeling a problem situation;
  • • formulate criteria for selecting alternative solutions;
  • • carry out the formation of a set of alternatives and decision-making criteria in a multi-criteria decision-making problem;
  • • formulate the general statement of the decision-making problem for many criteria;
  • • determine the values of the parameters of decision-making problems;
  • • identify classes of equivalence or indifference on the set of alternatives;
  • • construct preference relations, specify a utility function;
  • • construct a choice function;
  • • construct Pareto dominance relations;
  • • check the conditions for the existence of additive utility functions;
  • • find Pareto-dominated alternatives in real situations;
  • • construct the Pareto—Edgeworth set and the Pareto front;
  • • apply the «cost—effectiveness» method;
  • • find the most efficient numerical algorithms for finding the Pareto—Edgeworth set;
  • • assess the practical meaning of the Pareto—Edgeworth set and the Pareto front in decision-making;

master

  • • skills in determining admissible transformations for various types of measurement scales;
  • • ways of choosing methods of modeling a problem situation;
  • • methods for analyzing decision-making problems with many criteria when developing specific economic and organizational-managerial models;
  • • methods for forming and describing decision-making problems;
  • • skills in forming and describing the mathematical model of a decision-making problem in a specific situation;
  • • ways of constructing utility and risk functions for decision-making problems under conditions of probabilistic uncertainty;
  • • methods for constructing preference curves for additive utility functions;
  • • skills in applying the angle of preference and the cone of preference in real problems with two criteria;
  • • ways of finding sections of the boundary of the solution region that make up the Pareto—Edgeworth set in practical problems.

Key words

Decision theory; systems analysis; attribute; indicator; criterion; scale; problem situation; decision-making problem; set of admissible solutions; criterion space; multi-criteria problem; preferences; binary relation; choice function, decision rule; stochastic dominance; risk function; lexicographic preference relation; aggregate criterion; indifference curves; utility function; local rate of substitution; indifference map, additive utility function; optimality criteria; discrete set of alternatives; Pareto—Edgeworth set; Pareto front; angle of preference.

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Lectures and tutorial on "Decision theory"

Terms: Decision theory