Prescriptive Analytics

Limited resources are modeled in optimization problems as

constraints

The constraints of an LP model define the

feasible region.

When the objective function can increase without ever contacting a constraint, the LP model is said to be

unbounded.

When performing sensitivity analysis, which of the following assumptions must apply?

All other coefficients remain constant.

Which type of spreadsheet cell represents the left hand sides (LHS) formulas in an LP model?

Constraint cell

Which of the following actions would expand the feasible region of an LP model?

Loosening the constraints.

Which of the following is the type of model used throughout this textbook?

Mathematical Model.

Which type of spreadsheet cell represents the objective function in an LP model?

Objective cell

For a minimization problem, if a decision variable's final value is 0, and its reduced cost is negative, which of the following is true?

The variable has a non-negativity constraint.

What is the goal in optimization?

To find the decision variable values that result in the best objective function and satisfy all constraints.

A heuristic solution is

a rule-of-thumb for making decisions

Anchoring effects occur in decision-making problems when

a seemingly trivial factor serves as a starting point for estimations.

Models that are set up in an intuitively appealing, logical layout tend to be the most

auditable.

The slope of the level curve for the objective function value can be changed by

changing a coefficient in the objective function.

The sensitivity analysis provides information about all of the following except the impact of

constraints.

The goal of the modeling approach to problem solving is to

help individuals make good decisions.

Better decision making using a modeling process is achieved due to the

insight gained through the process.

A mathematical model is considered to be valid when

it accurately represents the relevant characteristics of the object or decision.

Microsoft Excel contains a built-in optimizer called

solvers.

A binding greater than or equal to (≥) constraint in a minimization problem means that

the minimum requirement for the constraint has just been met.