Feasible Region and Optimal Solution
Introduction
To fully understand the feasible region and the optimal solution, you will change some of the constraints of
the linear programming model. The effect of these changes is considered. Changing some of the
co

Linear Models Special Situations
Introduction
After setting up and solving a linear programming model, one can notice that some of the constraints are
redundant due to more restrictive of other constraints. Also, one can notice that one or more constraint

Infeasibility
Introduction
When you are solving linear programming model, you are looking for a common area composed of all
overlapping areas satisfying the constraints. This task gets more difficult as the number of constraints
increases. If one or more

Finance
Introduction
Financial institutes, banks, brokers, insurance companies use linear programming model to solve the
financial packages they off customers from life insurance, health insurance, mortgage, and others. In this
node you will look at a fin

Impact of Changes RHS
The objective function is $3x + $5y. A change to a RHS constraint has changed the optimal solution from
(100, 120) to (110, 120), the profit is _. (choose 2)
increased by $10
increased by $30
$930
increased by $50
The optimal solutio

Linear Models Develop and Format
Introduction
In order to create and promote a well-designed and stable business is to manage it properly with the
available resources at hand. A good business can go sour if several bad decisions are made. A good
manager c

Alternative Formulations
Introduction
In most of the applications you are dealing with large scale numbers such as thousands, millions, or even
billions. Writing this large numbers can usually lead us to miss a digit or two. You are presenting an adjusted

Alternate Optimal Solutions
Introduction
Either there was feasible region with only one optimal solution at a corner or an infeasible region
with no optimal solution at all. However, there are cases that you will have a feasible region with
multiple optim

Blending
Introduction
Blending is another application of linear programming model. In this case, you can mix several items to
produce sometime product. You will consider a diet problem in this node. You see how you can mix
several different types of milk

Employee Staffing
Introduction
Linear programming model can also be used in labor related professions such as providing staff for a
bank, department store, restaurant, and others. In this mode, you will try to staff cooks for a large hotel
restaurant on a

Decision Modeling: Interpretation
Introduction
Typically, a solution to a problem will suggest a change in the way the organization is operating. Trusting
the solution without analysis and interpretation is not recommended.
Learning Materials
Interpretati

Allocation
Introduction
In some cases you can further improve our objective function if you can modify some of the constraints.
For example in the airline industry changing a Boeing 767 jet by a Boeing747 jet allows to carry more
passengers on a route or

Transportation
Introduction
Perhaps one of the professions using the linear programming model most is the transportation industry.
There are always different items to ship from a list of originations to different destinations. You will
consider a transpor

Types of Sensitivity Analysis
Introduction
Sensitivity analysis is not simply the analysis of a change to a single input value for a model. Realistically,
the profit level, selling price, and/or cost per unit could change. The change to any type of input

RSH
1
The slack for the number of units produced is 50, and the optimal solution is to produce 75 units. The
number of unit produced can increase by _ without changing the optimal solution. (choose 2)
50
75
more than 75
up to 50
The optimal solution for a

Problems in Decision Modeling
Learning Materials
Problems that Arise
In each step of the decision model process, problems can arise. In the formulation step of defining the
problem, there may be conflicting viewpoints between the analysts. For example, ag

Sensitivity: Graphs
Learning Materials
Sensitivity Analysis
Sensitivity analysis studies how sensitive an optimal solution is to the model assumptions and data
changes. Managers want answers in regards to the impact of changes in case a value was estimate

Sinking Fund
Introduction
Sinking fund is also another type of multiperiod linear programming modeling. In this case, you are
opening a sinking fund to accumulate money for future years. Retirement accounts and education
accounts for the children are the

Marketing
Introduction
Linear programming model can be used in marketing as well. Companies can expand their operations
from smaller size to larger size in volume or increase their stores in numbers by advertising their
reputations. The power of advertisi

Make-Buy Decision
Introduction
Sometimes it becomes either necessary or beneficial to outsource some of the demands to another
company. In this case you need to make a decision to how many of each order has to be done in house
(Make) and the remaining of

Multiperiod
Introduction
Multiperiod is the most challenging applications of linear programming modeling. You are considering the
optimal solution for several different periods. The difficulties are that decision made in earlier periods can
influence the

Manufacturing: Product Mix Problem
Introduction
In this section you consider a manufacturing example of linear programming modeling. You establish the
objective functions to maximize the profit subject to the available resources by stating the objective
f

Objective Function Coefficient
Objective function coefficients will not _ outside an assumed range.
elevate
increase
change
decrease
In the profit formula $4B + $6D, an OFC is _. (choose 2)
$6
$4B
$4
$6D
When an OFC increases, the optimal level profit lin

Modeling Applications
Introduction
Managements of small and large companies, governmental officials whether in local or federal level and
ordinary people are faced by many issues in their daily professional lives. Everyone has to make proper
decisions for