QUIZ BUMA

• Mathematical programming is a field of management science that finds the optimal, or most efficient way of using limited resources to achieve the objectives of an individual or a business.
• Applications of mathematical programming include determining product mix in manufacturing, routing and logistic, financial planning, and more.
• Characteristics of mathematical programming include decisions, constraints, objectives, and more.
• Decisions in mathematical programming are the variables that the decision maker is trying to determine.
• Constraints in mathematical programming are some function of the decision variables that must be less than or equal to, greater than or equal to, or equal to some specific value (represented by the letter b).
• Less than or equal to in mathematical programming ensures that the total labor used in producing a given number of products does not exceed the amount of available labor.
• Greater than or equal to in mathematical programming ensures that the total amount of money withdrawn from a person’s retirement accounts is at least the minimum amount required by the IRS.
• Objectives in mathematical programming are the function of the decision variables that the decision maker wants to either maximize or minimize.
• Linear programming involves creating and solving optimization problems with linear objective functions and linear constraints.
• Formulating the model in mathematical programming is the process of taking a practical problem and expressing it algebraically in the form of an LP model.
• Solving LP problems: an graphical approach in mathematical programming involves finding the optimal solution by enumerating the corner points.
• Feasible region in mathematical programming is the set of points or values that the decision variables can assume and simultaneously satisfy all the constraints in the problem.
• Line curves in mathematical programming are lines representing the two objective function values; represent different levels or values of the objective.
• Finding the optimal solution by enumerating the corner points in mathematical programming involves identifying extreme points of the feasible region.
• Special conditions in LP models in mathematical programming include alternate optimal solutions, redundant constraint, unbounded solutions, infeasibility, and more.
• Alternate optimal solutions in mathematical programming are other feasible points that maximize (or minimize) the value of the objective function.
• Redundant constraints in mathematical programming are constraints that play no role in determining the feasible region of the problem.
• Unbounded solutions in mathematical programming indicate that there is something wrong with the formulation of the LP model.
• Infeasibility in mathematical programming means that there is no way to simultaneously satisfy all the constraints in the problem.