1. Modeling
2. Optimizer
3. Glossary
Term Definition
Constraint A limit on a value, such as its maximum, minimum, or that the value can’t be negative.
Feasibility An alternative to optimality, this offers a possible solution to a problem with:
• no distinct objective
• a variable
• one or more constraints
Input data Values necessary for computing the solution, including any constraints.
Linear function A function with a polynomial of degree 0 or 1. Displays as a straight line on a graph.
Linear program The pursuit of a solution in the form of a real number, where the Objective Function and the constraints are linear.
Integer linear program A linear program where variables are constrained to integral values (whole numbers).
Mixed integer linear program A linear program where only some of the variables are constrained to integral values. Other variables can be real values (decimal numbers).
Objective An expression that guides the optimization engine while it determines which assignments best support the business goal or solution, such as maximum income or minimal expense.
Optimality An optimal solution to a problem with:
• an objective (such as lowest cost or highest profit)
• a decision variable
• one or more constraints
Time Out The number of seconds until an Optimizer action that is processing stops and abandons progress. This value must be set when creating an Optimizer action to prevent Optimizer running indefinitely if a problem is unsolvable.
Upper bound, Lower bound The maximum or minimum value for a variable.
Variable The value that represents the solution to the problem (sometimes called the decision variable).

Variable data type

(Variables must have a numeric data type)

Integer (whole number

Real (decimal, or floating point)

Binary (zero or one, can be referred to as Boolean)