simplex linear programming i. concept ii. model template iii. class example iv. procedure v....
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Simplex Linear ProgrammingSimplex Linear Programming
I. ConceptII. Model TemplateIII. Class ExampleIV. ProcedureV. Interpretation
MAXIMIZATIONMETHOD
Applied Management Science for Decision Making, 2e Applied Management Science for Decision Making, 2e © 2014 Pearson Learning Solutions Philip A. Vaccaro , PhD© 2014 Pearson Learning Solutions Philip A. Vaccaro , PhD
Resource Planning
and Allocation Management
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Simplex Linear ProgrammingSimplex Linear Programming
* * DECISION VARIABLES MIGHT BE PRODUCTS BEING CONSIDERED FOR PRODUCTION
Most real-life LP problems have more than twodecision variables*, and thus are too large for the
simple graphical solution procedure.
In simplex LP problems the optimal solution will lie at a corner point of a multi-sided, multi-
dimensional figure called an n - dimensional polyhedron that represents the feasible region.
THE FEASIBLE REGION WOULD BE SIMILARTO THE SURFACE OF A DIAMOND
Simplex Linear ProgrammingSimplex Linear Programming
The simplex method examines the corner points in a systematic fashion, using basic algebraic concepts. The same set of procedures is repeated time after time until an optimal solution is reached.
Each repetition, or iteration, increases the value of the objective function so that we are always moving closer to the optimal solution.
Simplex Linear ProgrammingSimplex Linear Programming
The simplex method yields valuable economic information in addition to the optimal solution.
The manual computations must be mastered in order to successfully employ the software pro- grams, and to interpret the computer printouts.
WHY LEARN THE MANUAL COMPUTATIONS?
Problem StatementProblem Statement
Black and White
Color
A firm produces two different types of television sets:
Three resources are required to produce those televisions:
Chassis 24 units
Labor 160 hours
Color Tubes 10 units
Problem StatementProblem Statement
TELEVISION RESOURCE REQUIREMENTSAND
PROFIT MARGINS
Television Chassis Labor Hours Color Tubes Unit ProfitBlack + White 1 5 0 $6.00
Color 1 10 1 $15.00
Simplex Linear ProgrammingSimplex Linear Programming
Let X1 = BLACK AND WHITE TELEVISIONSLet X2 = COLOR TELEVISIONS
Objective Function:
Maximize Z = 6X1 + 15X2
subject to: 1X1 + 1X2 =< 24 chassis 5X1 + 10X2 =< 160 labor hours 0X1 + 1X2 =< 10 color tubes
X1 , X2 => 0
THE MODELTHE MODEL
Simplex Linear ProgrammingSimplex Linear ProgrammingCONVERSION TO LINEAR EQUALITIESCONVERSION TO LINEAR EQUALITIES
1X1 + 1X2 + 1SS11 = 24 chassis
5X1 + 10X2 + 1SS22 = 160 labor hours
0X1 + 1X2 + 1SS33 = 10 color tubes
SLACK VARIABLES: : S1S1 = CHASSIS , , S2S2 = = LABOR HOURS , , S3S3 = COLOR TUBES = COLOR TUBES
ADDING A SLACK VARIABLE TO EACH CONSTRAINTAND SETTING IT EQUAL TO THE RIGHT – HAND SIDE
Simplex Linear ProgrammingSimplex Linear ProgrammingCONVERSION TO LINEAR EQUALITIES SUITABLE FORCONVERSION TO LINEAR EQUALITIES SUITABLE FOR
INCLUSION IN THE SIMPLEX MATRIXINCLUSION IN THE SIMPLEX MATRIX
1X1 + 1X2 + 1S1 + 00S2 + 00S3 = 24 chassis
5X1 + 10X2 + 00S1 + 1S2 + 00S3 = 160 labor hours
00X1 + 1X2 + 00S1 + 00S2 + 1S3 = 10 color tubes
REWRITE EACH CONSTRAINT TO REFLECT THE PRESENCEPRESENCE ORABSENCEABSENCE OF ALL VARIABLES IN THE PROBLEM
Simplex Linear ProgrammingSimplex Linear Programming11stst FEASIBLE SOLUTION FEASIBLE SOLUTION
TRADITIONALLY THE FIRST FEASIBLE SOLUTIONPRODUCES NO PRODUCT AND HAS ALL
RESOURCES INTACT
XX11BLACK AND
WHITE TVs 0
XX22 COLOR TVs 0
SS11 CHASSIS 24
SS22 LABOR HOURS 160
SS33 COLOR TUBES 10
The 1The 1stst Feasible Solution Feasible Solution
CjCj
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
SS11
SS22
SS33
ZjZj
Cj-ZjCj-Zj ----------
THE THE BASISBASIS OR OR MIX MIX COLUMNCOLUMN
SHOWS ALL VARIABLES GREATER THAN ZERO IN THE CURRENT SOLUTIONSHOWS ALL VARIABLES GREATER THAN ZERO IN THE CURRENT SOLUTION
Toward 1Toward 1stst Feasible Solution Feasible Solution
CjCj
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
SS11 2424 11 11 11 00 00
SS22 160160 55 1010 00 11 00
SS33 1010 00 11 00 00 11
ZjZj
Cj-ZjCj-Zj
INSERTING LINEAR EQUALITIES INTO THE MATRIXINSERTING LINEAR EQUALITIES INTO THE MATRIX
RIGHT-HANDRIGHT-HANDSIDES ARESIDES AREENTEREDENTEREDINTO THEINTO THEQUANTITYQUANTITYCOLUMNCOLUMN
Toward 1Toward 1stst Feasible Solution Feasible Solution
CjCj
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
S1S1 2424 11 11 11 00 00
ZjZj
Cj-ZjCj-Zj
INSERTING LINEAR EQUALITIES INTO THE MATRIXINSERTING LINEAR EQUALITIES INTO THE MATRIX
1X1X11 + 1X + 1X22 + 1S + 1S11 + 0S + 0S22 + 0S + 0S33 = 24 = 24
Toward 1Toward 1stst Feasible Solution Feasible Solution
CjCj
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
S2S2 160160 55 1010 00 11 00
ZjZj
Cj-ZjCj-Zj
INSERTING LINEAR EQUALITIES INTO THE MATRIXINSERTING LINEAR EQUALITIES INTO THE MATRIX
5X5X11 + 10X + 10X22 + 0S + 0S11 + 1S + 1S22 + 0S + 0S33 = 160 = 160
Toward 1Toward 1stst Feasible Solution Feasible Solution
CjCj
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
S3S3 1010 00 11 00 00 11
ZjZj
Cj-ZjCj-Zj
INSERTING LINEAR EQUALITIES INTO THE MATRIXINSERTING LINEAR EQUALITIES INTO THE MATRIX
0X0X11 + 1X + 1X22 + 0S + 0S1 1 + 0S+ 0S22 + 1S + 1S33 = 10 = 10
Toward 1Toward 1stst Feasible Solution Feasible Solution
CjCj
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
SS11 2424 11 11 11 00 00
SS22 160160 55 1010 00 11 00
SS33 1010 00 11 00 00 11
ZjZj
Cj-ZjCj-Zj
INSERTING LINEAR EQUALITIES INTO THE MATRIXINSERTING LINEAR EQUALITIES INTO THE MATRIX
The 1The 1stst Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$0.$0. SS33 1010 00 11 00 00 11
ZjZj
Cj-ZjCj-Zj ----------
THE THE ““Cj”Cj” oror CONTRIBUTION MARGINCONTRIBUTION MARGIN
THE GROSS PROFIT PER UNIT FOR ALL VARIABLES IN THE PROBLEM.THE GROSS PROFIT PER UNIT FOR ALL VARIABLES IN THE PROBLEM.SURPLUSSURPLUS AND AND SLACKSLACK VARIABLES HAVE $0.00 Cj’s BY DEFINITION. VARIABLES HAVE $0.00 Cj’s BY DEFINITION.
Toward 1Toward 1stst Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$0.$0. SS33 1010 00 11 00 00 11
ZjZj
Cj-ZjCj-Zj
Toward 1Toward 1stst Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$0.$0. SS33 1010 00 11 00 00 11
ZjZj $0.$0.
Cj-ZjCj-Zj
COMPUTING THE Zj ROWCOMPUTING THE Zj ROW
$0.$0.
$0.$0.
$0.$0.
MULTIPLY EACH SLACK VARIABLE’S Cj BY ITS QUANTITY AND ADD THE RESULTSMULTIPLY EACH SLACK VARIABLE’S Cj BY ITS QUANTITY AND ADD THE RESULTS
Toward 1Toward 1stst Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$0.$0. SS33 1010 00 11 00 00 11
ZjZj $0.$0. $0.$0.
Cj-ZjCj-Zj
COMPUTING THE Zj ROWCOMPUTING THE Zj ROW
$0.$0.
$0.$0.
$0.$0.
THEN MULTIPLY EACH SLACK VARIABLE’S Cj BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTSTHEN MULTIPLY EACH SLACK VARIABLE’S Cj BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTS
Toward 1Toward 1stst Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$0.$0. SS33 1010 00 11 00 00 11
ZjZj $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj
COMPUTING THE Zj ROWCOMPUTING THE Zj ROW
$0.$0.
$0.$0.
$0.$0.
THEN MULTIPLY EACH SLACK VARIABLE’S Cj BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTSTHEN MULTIPLY EACH SLACK VARIABLE’S Cj BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTS
Toward 1Toward 1stst Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 X2X2 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$0.$0. SS33 1010 00 11 00 00 11
ZjZj $0.$0. $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj
COMPUTING THE Zj ROWCOMPUTING THE Zj ROW
$0.$0.
$0.$0.
$0.$0.
THEN MULTIPLY EACH SLACK VARIABLE’S Cj BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTSTHEN MULTIPLY EACH SLACK VARIABLE’S Cj BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTS
Toward 1Toward 1stst Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 SS22 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$0.$0. SS33 1010 00 11 00 00 11
ZjZj $0.$0. $0.$0. $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj
COMPUTING THE Zj ROWCOMPUTING THE Zj ROW
$0.$0.
$0.$0.
$0.$0.
THEN MULTIPLY EACH SLACK VARIABLE’S Cj BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTSTHEN MULTIPLY EACH SLACK VARIABLE’S Cj BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTS
Toward 1Toward 1stst Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 0 00
$0.$0. SS22 160160 55 1010 00 1 00
$0.$0. SS33 1010 00 11 00 0 11
ZjZj $0.$0. $0.$0. $0.$0. $0.$0. $0. $0.$0.
Cj-ZjCj-Zj
COMPUTING THE Zj ROWCOMPUTING THE Zj ROW
$0.$0.
$0.$0.
$0.$0.
THEN MULTIPLY EACH SLACK VARIABLE’S Cj BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTSTHEN MULTIPLY EACH SLACK VARIABLE’S Cj BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTS
Toward 1Toward 1stst Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$0.$0. SS33 1010 00 11 00 00 11
ZjZj $0.$0. $0.$0. $0.$0. $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj
THE COMPUTED Zj ROWTHE COMPUTED Zj ROW
Toward 1Toward 1stst Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$0.$0. SS33 1010 00 11 00 00 11
ZjZj $0.$0. $0.$0. $0.$0. $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj
Toward 1Toward 1stst Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$0.$0. SS33 1010 00 11 00 00 11
ZjZj $0.$0. $0.$0. $0.$0. $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj ---------- $6.$6.
COMPUTING THE Cj – Zj ROWCOMPUTING THE Cj – Zj ROW
ON A COLUMN BY COLUMN BASIS, SUBTRACT Zj FROM Cj ON A COLUMN BY COLUMN BASIS, SUBTRACT Zj FROM Cj
Toward 1Toward 1stst Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$0.$0. SS33 1010 00 11 00 00 11
ZjZj $0.$0. $0.$0. $0.$0. $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj ---------- $6.$6. $15.$15.
COMPUTING THE Cj – Zj ROWCOMPUTING THE Cj – Zj ROW
ON A COLUMN BY COLUMN BASIS, SUBTRACT Zj FROM CjON A COLUMN BY COLUMN BASIS, SUBTRACT Zj FROM Cj
Toward 1Toward 1stst Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$0.$0. SS33 1010 00 11 00 00 11
ZjZj $0.$0. $0.$0. $0.$0. $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj ---------- $6.$6. $15.$15. $0.$0.
COMPUTING THE Cj – Zj ROWCOMPUTING THE Cj – Zj ROW
Toward 1Toward 1stst Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$0.$0. SS33 1010 00 11 00 00 11
ZjZj $0.$0. $0.$0. $0.$0. $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj ---------- $6.$6. $15.$15. $0.$0. $0.$0.
COMPUTING THE Cj – Zj ROWCOMPUTING THE Cj – Zj ROW
Toward 1Toward 1stst Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$0.$0. SS33 1010 00 11 00 00 11
ZjZj $0.$0. $0.$0. $0.$0. $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj ---------- $6.$6. $15.$15. $0.$0. $0.$0. $0.$0.
COMPUTING THE Cj – Zj ROWCOMPUTING THE Cj – Zj ROW
The 1The 1stst Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$0.$0. SS33 1010 00 11 00 00 11
ZjZj $0.$0. $0.$0. $0.$0. $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj ---------- $6.$6. $15.$15. $0.$0. $0.$0. $0.$0.
THE COMPLETED Cj - Zj ROWTHE COMPLETED Cj - Zj ROW
The 1The 1stst Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$0.$0. SS33 1010 00 11 00 00 11
ZjZj $0.$0. $0.$0. $0.$0. $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj ---------- $6.$6. $15.$15. $0.$0. $0.$0. $0.$0.
Simplex Linear ProgrammingSimplex Linear Programming1st FEASIBLE SOLUTION
TRADITIONALLY THE FIRST FEASIBLE SOLUTIONPRODUCES NO PRODUCT AND HAS ALL
RESOURCES INTACT
XX11BLACK AND
WHITE TVs 00
XX22 COLOR TVs 0
SS11 CHASSIS 24
SS22 LABOR HOURS 160
SS33 COLOR TUBES 10
Simplex Linear ProgrammingSimplex Linear Programming
X1 ( B+W TVs ) = 0NOT IN THE BASISNOT IN THE BASIS
X2 ( Color TVs ) = 0NOT IN THE BASISNOT IN THE BASIS
Z ( Profit ) = $0.00SINCE XSINCE X11 AND X AND X2 2 = 0= 0
1st FEASIBLE SOLUTION
Toward 2nd Feasible SolutionToward 2nd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$0.$0. SS33 1010 00 11 00 00 11
ZjZj $0.$0. $0.$0. $0.$0. $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj ---------- $6.$6. $15.$15. $0.$0. $0.$0. $0.$0.
WE BRING THE MOST PROFITABLE TELEVISION ( X2 ) INTO THE SOLUTIONWE BRING THE MOST PROFITABLE TELEVISION ( X2 ) INTO THE SOLUTION
X2 BECOMES THE PIVOT COLUMNX2 BECOMES THE PIVOT COLUMN
Toward 2nd Feasible SolutionToward 2nd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$0.$0. SS33 1010 00 11 00 00 11
ZjZj $0.$0. $0.$0. $0.$0. $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj ---------- $6.$6. $15.$15. $0.$0. $0.$0. $0.$0.
WE COMPUTE EACH ROW’S RATIO OF QUANTITY DIVIDED BY ITS PIVOT COLUMN COEFFICIENTWE COMPUTE EACH ROW’S RATIO OF QUANTITY DIVIDED BY ITS PIVOT COLUMN COEFFICIENT
PIVOT COLUMNPIVOT COLUMN
2424
1616
1010
Toward 2nd Feasible SolutionToward 2nd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$0.$0. SS33 1010 00 11 00 00 11
ZjZj $0.$0. $0.$0. $0.$0. $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj ---------- $6.$6. $15.$15. $0.$0. $0.$0. $0.$0.
THE LOWEST POSITIVE RATIO DENOTES THE PIVOT ROWTHE LOWEST POSITIVE RATIO DENOTES THE PIVOT ROW
PIVOT COLUMNPIVOT COLUMN
2424
1616
1010
PPIIVVOOTT
RROOWW
MEANS WE CANONLY PRODUCETEN COLOR TVs
THIS IS THELIMITED RESOURCE
Toward 2nd Feasible SolutionToward 2nd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $0.$0. $0.$0. $0.$0. $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj ---------- $6.$6. $15.$15. $0.$0. $0.$0. $0.$0.
REAL VARIABLE X2 REPLACES SLACK VARIABLE S3 IN THE BASISREAL VARIABLE X2 REPLACES SLACK VARIABLE S3 IN THE BASIS
PIVOT COLUMNPIVOT COLUMN
PPIIVVOOTT
RROOWW
TO PRODUCETEN COLOR TVs
MEANS THATALL COLOR
TUBES MUSTBE CONSUMED,MAKING S3 = 0,AND FORCING IT TO LEAVE THE BASIS
Toward 2nd Feasible SolutionToward 2nd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $0.$0. $0.$0. $0.$0. $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj ---------- $6.$6. $15.$15. $0.$0. $0.$0. $0.$0.
THE PIVOT NUMBER IS LOCATED AT THE INTERSECTION OF THE PIVOT ROW AND PIVOT COLUMNTHE PIVOT NUMBER IS LOCATED AT THE INTERSECTION OF THE PIVOT ROW AND PIVOT COLUMN
PIVOT COLUMNPIVOT COLUMN
PPIIVVOOTT
RROOWW
Toward 2nd Feasible SolutionToward 2nd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 2424 11 11 11 00 00
$0.$0. SS22 160160 55 1010 00 11 00
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $0.$0. $0.$0. $0.$0. $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj ---------- $6.$6. $15.$15. $0.$0. $0.$0. $0.$0.
PIVOT COLUMNPIVOT COLUMN
PPIIVVOOTT
RROOWW
THE PIVOTNUMBER
MUSTALWAYS
BE“1”
When the Pivot Number is Not “1”When the Pivot Number is Not “1”
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 S1S1 S2 S3S3
$0.$0. 11
$0.$0. 1010
$15.$15. XX22 6060 1010 55 00 00 -10-10
ZjZj $0.$0. $0.$0. $0.$0. $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj ---------- $15.$15.
PIVOT COLUMNPIVOT COLUMN
PPIIVVOOTT
RROOWW
EXAMPLEEXAMPLE
THE ENTIRE PIVOTROW MUST BE DIVIDEDBY WHATEVER NUMBER
NEEDED T0 FORCE AVALUE OF “1” FOR THE
PIVOT NUMBER
When the Pivot Number is Not “1”When the Pivot Number is Not “1”
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. 11
$0.$0. 1010
$15.$15. XX22 1212 22 11 00 00 - 2- 2
ZjZj $0.$0. $0.$0. $0.$0. $0.$0. $0.$0. $0.$0.
Cj-ZjCj-Zj ---------- $15.$15.
PIVOT COLUMNPIVOT COLUMN
PPIIVVOOTT
RROOWW
EXAMPLEEXAMPLE
Toward 2Toward 2ndnd Feasible Solution Feasible SolutionROW TRANSFORMATIONROW TRANSFORMATION
Old 1st Row S1 24 1 1 1 0 0
Pivot Row S3 10 0 1 0 0 1
New 1st Row S1 14 1 0 1 0 -1
We subtract the pivot row from all other rows in the matrix ( except “Zj” and “Cj - Zj” ) in such a way as to force a “0” coefficient in the column above or below the pivot number.
SUBTRACT THE PIVOT ROW ( S3 ) FROM THE FIRST ROW ( S1 )
PivotNumber
Toward 2Toward 2ndnd Feasible Solution Feasible SolutionROW TRANSFORMATIONROW TRANSFORMATION
Old 2nd Row S2 160 5 10 0 1 0
Pivot Row S3 10 0 1 0 0 1
New 2nd Row S2 0
SUBTRACT THE PIVOT ROW ( S3 ) FROM THE SECOND ROW ( S2 )
HERE, THE PIVOT ROW MUST BE MULTIPLIED BY “10” IN ORDER TO FORCE THE REQUIRED ZERO COEFFICIENT IN THE NEW ROW
PivotNumber
Toward 2Toward 2ndnd Feasible Solution Feasible SolutionROW TRANSFORMATIONROW TRANSFORMATION
Old 2nd Row S2 160 5 10 0 1 0
Pivot Row S3 100 0 10 0 0 10
New 2nd Row S2 60 5 0 0 1 -10
SUBTRACT THE PIVOT ROW ( S3 ) FROM THE SECOND ROW ( S2 )
HERE, THE PIVOT ROW WAS MULTIPLIED BY “10” IN ORDER TO FORCE THE REQUIREDZERO COEFFICIENT IN THE NEW ROW
PivotNumber
Toward 2Toward 2ndnd Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. SS22 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj
Cj-ZjCj-Zj
INSERTING THE TRANSFORMED ROWS INTO THE MATRIXINSERTING THE TRANSFORMED ROWS INTO THE MATRIX
Toward 2Toward 2ndnd Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. SS22 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150.
Cj-ZjCj-Zj
COMPUTING THE Zj ROWCOMPUTING THE Zj ROW
$0.$0.
$0.$0.
$150.$150.
MULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS QUANTITY AND ADD THE RESULTSMULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS QUANTITY AND ADD THE RESULTS
Toward 2Toward 2ndnd Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. SS22 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0.
Cj-ZjCj-Zj
COMPUTING THE Zj ROWCOMPUTING THE Zj ROW
$0.$0.
$0.$0.
$0.$0.
MULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTSMULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTS
Toward 2Toward 2ndnd Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. SS22 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15.
Cj-ZjCj-Zj
COMPUTING THE Zj ROWCOMPUTING THE Zj ROW
$0.$0.
$0.$0.
$15.$15.
MULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTSMULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTS
Toward 2Toward 2ndnd Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. S2S2 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj
COMPUTING THE Zj ROWCOMPUTING THE Zj ROW
$0.$0.
$0.$0.
MULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTSMULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTS
$0.$0.
Toward 2Toward 2ndnd Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 SS22 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. SS22 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj
COMPUTING THE Zj ROWCOMPUTING THE Zj ROW
$0.$0.
$0.$0.
$0.$0.
MULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTSMULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTS
Toward 2Toward 2ndnd Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. SS22 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj
COMPUTING THE Zj ROWCOMPUTING THE Zj ROW
$0.$0.
$0.$0.
$15.$15.
MULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTSMULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTS
Toward 2Toward 2ndnd Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. SS22 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj
THE COMPLETED Zj ROWTHE COMPLETED Zj ROW
Toward 2Toward 2ndnd Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. SS22 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj
Toward 2Toward 2ndnd Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. SS22 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj ------ $6.$6.
COMPUTING THE Cj - Zj ROWCOMPUTING THE Cj - Zj ROW
ON A COLUMN BY COLUMN BASIS, SUBTRACT Zj FROM CjON A COLUMN BY COLUMN BASIS, SUBTRACT Zj FROM Cj
Toward 2Toward 2ndnd Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. SS22 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj ------ $6.$6. $0.$0.
COMPUTING THE Cj - Zj ROWCOMPUTING THE Cj - Zj ROW
ON A COLUMN BY COLUMN BASIS, SUBTRACT Zj FROM CjON A COLUMN BY COLUMN BASIS, SUBTRACT Zj FROM Cj
Toward 2Toward 2ndnd Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. SS22 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj ------ $6.$6. $0.$0. $0.$0.
COMPUTING THE Cj - Zj ROWCOMPUTING THE Cj - Zj ROW
Toward 2Toward 2ndnd Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. SS22 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj ------ $6.$6. $0.$0. $0.$0. $0.$0.
COMPUTING THE Cj - Zj ROWCOMPUTING THE Cj - Zj ROW
Toward 2Toward 2ndnd Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.$0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. SS22 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj ------ $6.$6. $0.$0. $0.$0. $0.$0. -$15.-$15.
COMPUTING THE Cj - Zj ROWCOMPUTING THE Cj - Zj ROW
The 2The 2ndnd Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. SS22 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj ------ $6.$6. $0.$0. $0.$0. $0.$0. -$15.-$15.
THE COMPLETED Cj – Zj ROWTHE COMPLETED Cj – Zj ROW
The 2The 2ndnd Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. SS22 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj ------ $6.$6. $0.$0. $0.$0. $0.$0. -$15.-$15.
The 2The 2ndnd Feasible Solution Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. SS22 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj ------ $6.$6. $0.$0. $0.$0. $0.$0. -$15.-$15.
Simplex Linear ProgrammingSimplex Linear Programming22ndnd FEASIBLE SOLUTION FEASIBLE SOLUTION
XX11BLACK AND
WHITE TVs 0
XX22 COLOR TVs 10
SS11 CHASSIS 14
SS22 LABOR HOURSLABOR HOURS 60
SS33 COLOR TUBESCOLOR TUBES 0 TOTAL PROFIT = $150.00
Simplex Linear ProgrammingSimplex Linear Programming22ndnd FEASIBLE SOLUTION FEASIBLE SOLUTION
Z ( total profit ) = $150.00
X1 ( B + W TVs ) = 0NOT IN THE BASISNOT IN THE BASIS
S3 ( Color Tubes ) = 0NOT IN THE BASISNOT IN THE BASIS
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. SS22 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj ------ $6.$6. $0.$0. $0.$0. $0.$0. -$15.-$15.
WE BRING BLACK + WHITE TELEVISIONS (X1) INTO THE SOLUTIONWE BRING BLACK + WHITE TELEVISIONS (X1) INTO THE SOLUTION
X1X1 BECOMES THE PIVOT COLUMNBECOMES THE PIVOT COLUMN
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. SS22 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj ------ $6.$6. $0.$0. $0.$0. $0.$0. -$15.-$15.
WE COMPUTE EACH ROW’S RATIO OF QUANTITY DIVIDED BY ITS PIVOT COLUMN COEFFICIENTWE COMPUTE EACH ROW’S RATIO OF QUANTITY DIVIDED BY ITS PIVOT COLUMN COEFFICIENT
THE PIVOT COLUMNTHE PIVOT COLUMN
1414
1212
00
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$0.$0. SS22 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj ------ $6.$6. $0.$0. $0.$0. $0.$0. -$15.-$15.
THE LOWEST POSITIVE RATIO DENOTES THE PIVOT ROWTHE LOWEST POSITIVE RATIO DENOTES THE PIVOT ROW
THE PIVOT COLUMNTHE PIVOT COLUMN
1414
1212
00
PPIIVVOOT T
RROOWW
MEANS WE CANONLY PRODUCE
12 B+W TVsTHIS IS THE
LIMITED RESOURCE
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$6.$6. XX11 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj ------ $6.$6. $0.$0. $0.$0. $0.$0. -$15.-$15.
REAL VARIABLE X1 REPLACES SLACK VARIABLE S2 IN THE BASISREAL VARIABLE X1 REPLACES SLACK VARIABLE S2 IN THE BASIS
THE PIVOT COLUMNTHE PIVOT COLUMN
PPIIVVOOT T
RROOWW
TO PRODUCE12 B+W TVs
MEANS THATALL REMAINING LABOR HOURS
MUST BECONSUMED,
MAKING S2 = 0, AND FORCING IT TO LEAVE THE BASIS
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$6.$6. XX11 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj ------ $6.$6. $0.$0. $0.$0. $0.$0. -$15.-$15.
THE PIVOT NUMBER IS LOCATED AT THE INTERSECTION OF THE PIVOT ROW AND PIVOT COLUMNTHE PIVOT NUMBER IS LOCATED AT THE INTERSECTION OF THE PIVOT ROW AND PIVOT COLUMN
THE PIVOT COLUMNTHE PIVOT COLUMN
PPIIVVOOT T
RROOWW
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$6.$6. XX11 6060 55 00 00 11 -10-10
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj ------ $6.$6. $0.$0. $0.$0. $0.$0. -$15.-$15.THE PIVOT COLUMNTHE PIVOT COLUMN
PPIIVVOOT T
RROOWW
THE PIVOT
NUMBERMUST
ALWAYSBE“1”
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 1414 11 00 11 00 -1-1
$6.$6. XX11 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $150.$150. $0.$0. $15.$15. $0.$0. $0.$0. $15.$15.
Cj-ZjCj-Zj ------ $6.$6. $0.$0. $0.$0. $0.$0. -$15.-$15.
THE PIVOT COLUMNTHE PIVOT COLUMN
PPIIVVOOT T
RROOWW
DIVIDETHE
ENTIREPIVOT ROW
BY“5”
Toward 3Toward 3rdrd Feasible Solution Feasible SolutionROW TRANSFORMATIONROW TRANSFORMATION
Old 1st Row S1 14 1 0 1 0 -1
Pivot Row X1 12 1 0 0 .2 - 2.0
New 1st Row S1 2 0 0 1 -.2 1
SUBTRACT THE PIVOT ROW ( X1 ) FROM THE FIRST ROW ( S1 )
HERE, THERE WAS NO NEED TO MULTIPLY THE PIVOT ROW BY ANY NUMBER IN ORDER TO FORCE A ZERO COEFFICIENT BELOW THE PIVOT NUMBER
PivotNumber
Toward 3Toward 3rdrd Feasible Solution Feasible SolutionROW TRANSFORMATIONROW TRANSFORMATION
Old 3rd Row X2 10 0 1 0 0 1
Pivot Row X1 12 1 0 0 .2 - 2.0
New 3rd Row X2 10 0 1 0 0 1
SUBTRACT THE PIVOT ROW ( X1 ) FROM THE THIRD ROW ( X2 )
HERE, THERE WAS NO NEED TO TRANSFORM ROW “3” BECAUSE IT ALREADY HAD A ZERO COEFFICIENT BELOW THE PIVOT NUMBER
PivotNumber
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 22 00 00 11 -.2-.2 11
$6.$6. XX11 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj
Cj-ZjCj-Zj
INSERTING THE TRANSFORMED ROWS INTO THE MATRIXINSERTING THE TRANSFORMED ROWS INTO THE MATRIX
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 22 00 00 11 -.2-.2 11
$6.$6. XX11 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $222.$222.
Cj-ZjCj-Zj
COMPUTING THE Zj ROWCOMPUTING THE Zj ROW
$0.$0.
$72.$72.
$150.$150.
MULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS QUANTITY AND ADD THE RESULTSMULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS QUANTITY AND ADD THE RESULTS
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 22 00 00 11 -.2-.2 11
$6.$6. XX11 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $222.$222. $6.$6.
Cj-ZjCj-Zj
COMPUTING THE Zj ROWCOMPUTING THE Zj ROW
$0.$0.
$6.$6.
$0.$0.
MULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTSMULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTS
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. S1S1 22 00 00 11 -.2-.2 11
$6.$6. X1X1 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $222.$222. $6.$6. $15.$15.
Cj-ZjCj-Zj
COMPUTING THE Zj ROWCOMPUTING THE Zj ROW
$0.$0.
$0.$0.
$15.$15.
MULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTSMULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTS
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 22 00 00 11 -.2-.2 11
$6.$6. XX11 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $222.$222. $6.$6. $15.$15. $0.$0.
Cj-ZjCj-Zj
COMPUTING THE Zj ROWCOMPUTING THE Zj ROW
$0.$0.
$0.$0.
$0.$0.
MULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTSMULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTS
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 SS22 SS33
$0.$0. SS11 22 00 00 11 -.2-.2 11
$6.$6. XX11 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $222.$222. $6.$6. $15.$15. $0.$0. $1.2$1.2
Cj-ZjCj-Zj
COMPUTING THE Zj ROWCOMPUTING THE Zj ROW
$0.$0.
$1.2$1.2
$0.$0.
MULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTSMULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTS
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 22 00 00 11 -.2-.2 11
$6.$6. XX11 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $222.$222. $6.$6. $15.$15. $0.$0. $1.2$1.2 $3.0$3.0
Cj-ZjCj-Zj
COMPUTING THE Zj ROWCOMPUTING THE Zj ROW
$0.$0.
$15.$15.
MULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTSMULTIPLY EACH BASIS VARIABLE’S “Cj” BY ITS VARIABLE COEFFICIENTS AND ADD THE RESULTS
-$12.-$12.
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 22 00 00 11 -.2-.2 11
$6.$6. XX11 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $222.$222. $6.$6. $15.$15. $0.$0. $1.2$1.2 $3.0$3.0
Cj-ZjCj-Zj
THE COMPLETED Zj ROWTHE COMPLETED Zj ROW
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 22 00 00 11 -.2-.2 11
$6.$6. XX11 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $222.$222. $6.$6. $15.$15. $0.$0. $1.2$1.2 $3.0$3.0
Cj-ZjCj-Zj
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 22 00 00 11 -.2-.2 11
$6.$6. XX11 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $222.$222. $6.$6. $15.$15. $0.$0. $1.2$1.2 $3.0$3.0
Cj-ZjCj-Zj $0.$0.
COMPUTING THE Cj – Zj ROWCOMPUTING THE Cj – Zj ROW
ON A COLUMN BY COLUMN BASIS, SUBTRACT Zj FROM CjON A COLUMN BY COLUMN BASIS, SUBTRACT Zj FROM Cj
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 22 00 00 11 -.2-.2 11
$6.$6. XX11 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $222.$222. $6.$6. $15.$15. $0.$0. $1.2$1.2 $3.0$3.0
Cj-ZjCj-Zj $0.$0. $0.$0.
COMPUTING THE Cj – Zj ROWCOMPUTING THE Cj – Zj ROW
ON A COLUMN BY COLUMN BASIS, SUBTRACT Zj FROM CjON A COLUMN BY COLUMN BASIS, SUBTRACT Zj FROM Cj
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 22 00 00 11 -.2-.2 11
$6.$6. XX11 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $222.$222. $6.$6. $15.$15. $0.$0. $1.2$1.2 $3.0$3.0
Cj-ZjCj-Zj $0.$0. $0.$0. $0.$0.
COMPUTING THE Cj – Zj ROWCOMPUTING THE Cj – Zj ROW
ON A COLUMN BY COLUMN BASIS, SUBTRACT Zj FROM CjON A COLUMN BY COLUMN BASIS, SUBTRACT Zj FROM Cj
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 22 00 00 11 -.2-.2 11
$6.$6. XX11 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $222.$222. $6.$6. $15.$15. $0.$0. $1.2$1.2 $3.0$3.0
Cj-ZjCj-Zj $0.$0. $0.$0. $0.$0. -$1.2-$1.2
COMPUTING THE Cj – Zj ROWCOMPUTING THE Cj – Zj ROW
ON A COLUMN BY COLUMN BASIS, SUBTRACT Zj FROM CjON A COLUMN BY COLUMN BASIS, SUBTRACT Zj FROM Cj
Toward 3rd Feasible SolutionToward 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 22 00 00 11 -.2-.2 11
$6.$6. XX11 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $222.$222. $6.$6. $15.$15. $0.$0. $1.2$1.2 $3.0$3.0
Cj-ZjCj-Zj $0.$0. $0.$0. $0.$0. -$1.2-$1.2 -$3.0-$3.0
COMPUTING THE Cj – Zj ROWCOMPUTING THE Cj – Zj ROW
ON A COLUMN BY COLUMN BASIS, SUBTRACT Zj FROM CjON A COLUMN BY COLUMN BASIS, SUBTRACT Zj FROM Cj
The 3rd Feasible SolutionThe 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 22 00 00 11 -.2-.2 11
$6.$6. XX11 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $222.$222. $6.$6. $15.$15. $0.$0. $1.2$1.2 $3.0$3.0
Cj-ZjCj-Zj $0.$0. $0.$0. $0.$0. -$1.2-$1.2 -$3.0-$3.0
THE COMPLETED Cj – Zj ROWTHE COMPLETED Cj – Zj ROW
The 3rd Feasible SolutionThe 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 22 00 00 11 -.2-.2 11
$6.$6. XX11 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $222.$222. $6.$6. $15.$15. $0.$0. $1.2$1.2 $3.0$3.0
Cj-ZjCj-Zj $0.$0. $0.$0. $0.$0. -$1.2-$1.2 -$3.0-$3.0
The 3rd Feasible SolutionThe 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 22 00 00 11 -.2-.2 11
$6.$6. XX11 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $222.$222. $6.$6. $15.$15. $0.$0. $1.2$1.2 $3.0$3.0
Cj-ZjCj-Zj $0.$0. $0.$0. $0.$0. -$1.2-$1.2 -$3.0-$3.0
The 3rd Feasible SolutionThe 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 S2 SS33
$0.$0. SS11 22 00 00 11 -.2-.2 11
$6.$6. XX11 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $222.$222. $6.$6. $15.$15. $0.$0. $1.2$1.2 $3.0$3.0
Cj-ZjCj-Zj $0.$0. $0.$0. $0.$0. -$1.2-$1.2 -$3.0-$3.0
THERE ARE NO POSITIVE NUMBERS IN THE Cj – Zj ROWTHERE ARE NO POSITIVE NUMBERS IN THE Cj – Zj ROW
THETHEOPTIMALOPTIMAL
SOLUTIONSOLUTION
Simplex Linear ProgrammingSimplex Linear Programming33rdrd AND OPTIMAL FEASIBLE SOLUTION AND OPTIMAL FEASIBLE SOLUTION
X1 = 12X2 = 10
S1 = 2S2 = 0S3 = 0
Z = $222.00
Produce twelvetwelve black and whitetelevisionsProduce tenten color televisions
There are twotwo chassis left overThere are nono labor hours left overThere are nono color tubes left over
Total profit realized is $222.00$222.00
A RECORD SHOULD BE KEPT OF WHAT EACH VARIABLE REPRESENTS
The 3rd Feasible SolutionThe 3rd Feasible Solution
CjCj $6.$6. $15.$15. $0.$0. $0.$0. $0.
BasisBasis QtyQty XX11 XX22 SS11 SS22 SS33
$0.$0. SS11 22 00 00 11 -.2-.2 11
$6.$6. XX11 1212 11 00 00 .2.2 -2.0-2.0
$15.$15. XX22 1010 00 11 00 00 11
ZjZj $222.$222. $6.$6. $15.$15. $0.$0. $1.2$1.2 $3.0$3.0
Cj-ZjCj-Zj $0.$0. $0.$0. $0.$0. -$1.2-$1.2 -$3.0-$3.0
THE SLACK VARIABLE SHADOW PRICESTHE SLACK VARIABLE SHADOW PRICES
ALWAYS FOUND IN THE Cj – Zj ROWALWAYS FOUND IN THE Cj – Zj ROW
Simplex Linear ProgrammingSimplex Linear Programming33rdrd AND OPTIMAL FEASIBLE SOLUTION SHADOW PRICES AND OPTIMAL FEASIBLE SOLUTION SHADOW PRICES
S1 = $0.00
S2 = - $1.20
S3 = - $3.00
WE WOULD BE WILLING TO PAYWILLING TO PAYUP TO ZERO DOLLARSZERO DOLLARS FOR ADDITIONAL CHASSIS
WE WOULD BE WILLING TO PAYWOULD BE WILLING TO PAYUP TO $1.20$1.20 FOR ADDITIONALLABOR HOURS
WE WOULD BE WILLING TO PAYUP TO $3.00$3.00 FOR ADDITIONALCOLOR TUBES
THIS PARTICULAR SIMPLEX METHOD DISPLAYS NEGATIVE VALUES FOR POSITIVESHADOW PRICES. THIS IS CALLED THE “MIRROR EFFECT”.