Process (computing)

Engineering

Construct (python library)

Similarity (geometry)

Social psychology

Convergence (economics)

Closeness

Operating system

Economics

Data mining

Computer science

Management science

Organic chemistry

Distance measures

Psychology

Mathematics

Image (mathematics)

Group decision-making

Mathematical analysis

Operations management

Artificial intelligence

Chemistry

Programming language

Metric (unit)

Economic growth

Group (periodic table)

International Journal of Intelligent Systems

Decision situations in which several individual are involved are known as group decision-making (GDM) problems. In such problems, each member of the group, recognizing the existence of a common problem, tries to come to a collective decision. A high level of consensus among experts is needed before reaching a solution. It is customary to construct consensus measures by using similarity functions to quantify the closeness of experts preferences. The use of a metric that describes the distance between experts preferences allows the definition of similarity functions. Different distance functions have been proposed in order to implement consensus measures. This paper examines how the use of different aggregation operators affects the level of consensus achieved by experts through different distance functions, once the number of experts has been established in the GDM problem. In this situation, the experimental study performed establishes that the speed of the consensus process is significantly affected by the use of diverse aggregation operators and distance functions. Several decision support rules that can be useful in controlling the convergence speed of the consensus process are also derived.

A comparative study on consensus measures in group decision making