Discrete, Continuous, or Mixed Models

Optimization models can be classified as:

Discrete — Contain only discrete decision variables.
Continuous — Contain only continuous decision variables.
Mixed — Contain both discrete and continuous decision variables, or any of the other decision variable types: binary, category, or custom.

For more information on discrete and continuous decision variables, see Decision Variables.

Figure 68, Comparison of discrete and continuous decision variables shows that discrete variable distributions are a series of individual values while continuous variable distributions are an infinite range of values without distinctive bounds except the end points.

Figure 68. Comparison of discrete and continuous decision variables