Title: Chapter 6 Supplement
1Chapter 6 Supplement
2Linear Programming
- Linear Programming (LP) deals with the problems
of allocating limited resources among competing
activities in the best possible way (optimal) - A linear program consist of a linear objective
function and a set of linear constraints
3Linear Programming Model
- Objective the goal of an LP model is
maximization or minimization - Decision variables amounts of either inputs or
outputs - Constraints limitations that restrict the
available alternatives - Parameters numerical values
4Linear Programming Assumptions
- Linearity the impact of decision variables is
linear in constraints and objective function - Divisibility noninteger values of decision
variables are acceptable - Certainty values of parameters are known and
constant - Nonnegativity negative values of decision
variables are unacceptable
5Linear Programming Application Procedure
- Parameter Estimation
- Problem Formulation
- Optimal Solution
- Graphical Method
- Simplex Method
- Computer Solution
- Other Methods
- Sensitivity Analysis
6Linear Programming Application Areas
- Production
- Inventory
- Financial
- Marketing
- Distribution
- Sports
- Agriculture
7Linear Programming Some Definitions
- Solution A solution is a set of values of the
decision variables - Feasible Solution A feasible solution is a
solution for which all the constraints are
satisfied - Optimal Solution An optimal solution is a
feasible solution which optimizes the objective
function
8Linear Programming Types of Solutions
- Single Optimal Solution
- Multiple Optimal Solutions
- No Optimal Solution
9Graphical Linear Programming
- Set up objective function and constraints in
mathematical format - Plot the constraints
- Identify the feasible solution space
- Plot the objective function
- Determine the optimum solution
10Graphical Linear Programming
- Maximize Z 4X1 5X2
- Subject to
- X1 3X2 lt 12 (constraint 1)
- 4X1 3X2 lt 24 (constraint 2)
- X1 gt 0
- X2 gt 0
11Linear Programming Example
Plot Constraint 1 X1 3X2 12
12Linear Programming Example
Add Constraint 2 4X1 3X2 24
Constraint 1 X1 3X2 12
Solution space
13Linear Programming Example
X2
Z 60
Z 40
Z 20
X1
14LP Formulation and Computer Solution Problem 1
15Linear Programming Problem 1 Formulation
- Let Xi be the number of units of product type i
to be produced per week, i 1, 2, 3 - Maximize Z 30X1 12X2 15X3
- Subject to
- 9X1 3X2 5X3 lt 500 (Milling)
- 5X1 4X2 lt 350 (Lathe)
- 3X1 2X3 lt 150 (Drill)
- X3 lt 20 (Sales Potential)
- X1 gt 0, X2 gt 0, X3 gt 0
16Slack and Surplus
- Binding constraint a constraint that forms the
optimal corner point of the feasible solution
space - Slack when the optimal values of decision
variables are substituted into a less than or
equal to constraint and the resulting value is
less than the right side value - Surplus when the optimal values of decision
variables are substituted into a greater than or
equal to constraint and the resulting value
exceeds the right side value
17Linear Programming Problem 1 Solution Using
LINGO Software
- Objective value 1742.857
- Variable Value Reduced Cost
- X1 26.19048 0.0000000
- X2 54.76190 0.0000000
- X3 20.00000 0.0000000
- Row Slack or Surplus Dual Price
- PROFIT 1742.857 1.000000
- MILLING 0.0000000 2.857143
- LATHE 0.0000000 0.8571429
- DRILL 31.42857 0.0000000
- SALESPOT 0.0000000 0.7142857
18Sensitivity Analysis
- Range of optimality the range of values for
which the solution quantities of the decision
variables remains the same - Range of feasibility the range of values for the
fight-hand side of a constraint over which the
shadow price (dual price) remains the same - Shadow prices negative values indicating how
much a one-unit decrease in the original amount
of a constraint would decrease the final value of
the objective function
19Linear Programming Problem 1 Solution Using
LINGO Software
- Ranges in which the basis is unchanged
- Objective Coefficient Ranges
- Current Allowable
Allowable - Variable Coefficient Increase
Decrease - X1 30.00000 0.7500000
15.00000 - X2 12.00000 12.00000
0.6000000 - X3 15.000 INFINITY
0.7142857 - Righthand Side Ranges
- Row Current Allowable
Allowable - RHS Increase
Decrease - MILLING 500.0000 55.00000 137.5000
- LATHE 350.0000 183.3333
73.33334 - DRILL 150.0000 INFINITY
31.42857 - SALESPOT 20.00000 27.50000 20.00000
20Linear Programming Problem 1 Solution Using
EXCEL (a)
21Linear Programming Problem 1 Solution Using
EXCEL Software (b)
22Linear Programming Problem 1 Solution Using
EXCEL Software (c)
23Linear Programming Problem 1 Solution Using
EXCEL Software (d)
24LP Formulation And Computer Solution Problem 2
25Linear Programming Problem 2 Formulation
- Let X1 X2 X3 be the kilograms of corn, tankage,
and alfalfa, respectively. - Minimize Z 21X1 18X2 15X3
- Subject to
- 90X1 20X2 40X3 gt 200 (Carbo)
- 30X1 80X2 60X3 gt 180 (Protein)
- 10X1 20X2 60X3 gt 150 (Vitamin)
- X1 gt 0, X2 gt 0, X3 gt 0
26Linear Programming Problem 2 Solution Using
LINGO Software
- Objective value 60.42857
- Variable Value Reduced Cost
- X1 1.142857 0.0000000
- X2 0.0000000 4.428571
- X3 2.428571 0.0000000
- Row Slack or Surplus Dual Price
- COST 60.42857 1.000000
- CARBOHY 0.0000000 -0.1928571
- PROTEIN 0.0000000 -0.1214286
- VITAMIN 7.142857 0.0000000
27Linear Programming Problem 2 Solution Using
LINGO Software
- Ranges in which the basis is unchanged
- Objective Coefficient Ranges
- Current Allowable
Allowable - Variable Coefficient Increase
Decrease - X1 21.00000 12.75000
9.299998 - X2 18.00000 INFINITY
4.428571 - X3 15.00000 2.818181
5.666667 - Righthand Side Ranges
- Row Current Allowable
Allowable - RHS Increase
Decrease - CARBOHY 200.0000 25.00000 80.00000
- PROTEIN 180.0000 120.0000
6.000000 - VITAMIN 150.0000 7.142857
INFINITY
28Linear Programming Problem 2 Solution Using
EXCEL Software (a)
29Linear Programming Problem 2 Solution Using
EXCEL Software (b)
30Linear Programming Problem 2 Solution Using
EXCEL Software (c)
31Linear Programming Problem 2 Solution Using
EXCEL Software (d)