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Corso MAE Metodi Quantitativi per il Management Quantitative methods for Management. Prof. Gianni Di Pillo Prof. Laura Palagi Dipartimento di Informatica e Sistemistica Universita` di Roma “La Sapienza”. Roma, 18 settembre - 24 ottobre 2003. Reports Answer Sensitivity Limits.

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slide1

Corso MAE

Metodi Quantitativi per il Management

Quantitative methods for Management

Prof. Gianni Di Pillo

Prof. Laura Palagi

Dipartimento di Informatica e Sistemistica

Universita` di Roma “La Sapienza”

Roma, 18 settembre - 24 ottobre 2003

solver reports

Reports Answer Sensitivity Limits

Solver reports

LP software packages provide more information than the optimal values of decision variables and of the objective function

This information can be required right after Solver has found an optimal solution

the production problem of factory a

The grinding and polishing times in hours for a unit of each type of product of factory A are

Each unit of product yields the following profit

Factory A has a grinding capacities of 80 hours per week and polishing capacity of 60 hours per week

The production problem of factory A

Factory A makes two products: standard and deluxe

Each product requires 4 Kg of raw material Factory A is allocated 75 Kg of raw material

mathematical model for factory a

At the optimal solution they may be satisfied as

= binding constraint

< nonbinding constraint

Right hand side (r.h.s)

Left hand side (l.h.s.)

Mathematical model for factory A

Constraints are inequalities

max 10x1 + 15 x2

4x1 + 4 x2 <= 75

4x1 + 2 x2 <= 80

2x1 + 5 x2 <= 60

x1 , x2 >= 0

When the constraint is nonbinding the difference between the two sides is called slack

geometric interpretation

x2

45

40

40

35

30

25

20

In particular it is not binding in the optimal solution

15

10

5

x1

5

10

15

20

25

30

35

40

40

45

Geometric interpretation

constitutes the set of the feasible solution for factory A

All non negative points

The constraint 4 x1 + 2 x2 <= 80 does not play any role in defining the feasible region

Any point in F is such that4 x1 + 2 x2 < 80

4 x1 + 2 x2 = 80

The grinding constraint 4 x1 + 2 x2 <= 80 is always nonbinding

F

This is not true in general

excel s answer report details

Target cell (max)

Initial guess

Final value

name

Adjustable cells

Excel’s Answer report: details
excel s answer report details1
Excel’s Answer report: details

italian

english

The information on binding and nonbinding constraint is of most interest when it pertains scarse resources.

use excel s answer report
Use Excel’s Answer report

From the table above, we see that the raw material and the polishing constraints are binding, but there are 20 unit (hours) of slack in the grinding constraint.

This information can be used together with the other Solver reports

excel s sensitivity report italian
Excel’s Sensitivity report (italian)

Excel produces also an optional sensitivity report

excel s sensitivity report top part
Excel’s Sensitivity report (top part)

In the top part there is a separate line for each changing cell (i.e. for each decision variable)

If a decision variable is positive (an activity is being performed at a positve level), then the columns of allowable increase and decrease indicate how much more or less profitable this activity would have to be before the current optimal solution would no longer be optimal

geometric interpretation for factory a

Actual objective function

max 10x1 + 15 x2

x2

45

40

40

35

15x1 + 15 x2

30

25

6x1 + 15 x2

20

15

Actual optimal solution

10

5

x1

5

10

15

20

25

30

35

40

40

45

Geometric interpretation for factory A

If the coefficient of x1 = standard stays between

Allowable increase

+ 5 = 15

10

Allowable decrease

- 4 = 6

It is a “rotation” around the optimal point

10x1 + 15 x2

F

The same happens changing coefficient x2

reduced costs in excel s sensitivity report
Reduced costs in Excel’s Sensitivity report

If a decision variable is zero, the it is evidently not profitable to include this activity in the optimal mix

The reduced cost (or dual value)of an activity indicates how much more profitable each unit of this activity would have to be before it would be optimal to include in the optimal mix

In this case, variables are positive, and the corresponding reduced costs are zero !

excel s sensitivity report botton part

In the bottom part, there is a line for each constraint (not including simple lower or bound on the decision variables)

Excel’s Sensitivity report (botton part)

If a constraint is binding, then the company has used all the available resource and it might consider buying more of it

How much the company will be willing to pay for each extra unit of material ?

shadow prices in excel s sensitivity report
Shadow prices in Excel’s Sensitivity report

The shadow prices indicates how much extra unit of resource is worth in terms of increasing the total profit

The shadow price is the change in the objective value for unit change in the availability of the resource

In Factory A problem, the shadow price for the raw material is 1.6. This means that each extra unit (kg) of raw material (on top of the 75 available) would add 1.6 Euro to the total profit.

shadow prices in excel s sensitivity report1

Add 1 unit to polishing availability

Add 1.66 to the profit

Shadow prices in Excel’s Sensitivity report

In Factory A problem, the shadow price for the polishing hours is 1.6. This means that each extra unit (hour) of polishing resource (on top of the 60 available) would add 1.6 Euro to the total profit.

economic interpretation of shadow prices
Economic interpretation of shadow prices

The shadow prices for non binding constraints are always equal to zero. This makes economic sense: if the company already has more unit of a resources then it is using , the it certain is not willing to pay for more units.

In Factory A problem, the grinding availability is not saturated (the constraint is non binding) and the shadow price for the grinding constraint is zero.

shadow prices are always valid
Shadow prices are always valid ?

Shadow prices analysis is valid only within certain ranges of changes in the resources. These ranges are given in Excel Sensitivity report (allowable increase and decrease)

The allowable increase and decrease indicate the range in which the shadow price is relevant. Within the range every extra/loss of unit produce extra/loss profit (given by the corresponding shadow price)

Beyond this range, it is difficult to say what will happen

shadow prices are always valid1
Shadow prices are always valid ?

Actually if we increase raw material up to 100 (>75+15) we gain only 50 Euro, that means that each extra unit is worth less than 1.66 (actually is 1)

The only way to find out how much less or more profitable is to change the amount and rerun the Solver

ranges for non binding constraint

In the case of non binding constraint (the shadow prices are zero), the allowable increase is infinity because the shadow price remains zero no matter how many more units of resources are available.

The allowable decrease is finite and it is exactly the amount of the slack (surplus) for the resource.

Ranges for non binding constraint
ranges for non binding constraint1
Ranges for non binding constraint

For Factory A, the slack for the grinding constraint is 20: if the company has less than 20 unit of grinding hours, the current solution will no longer be optimal and the shadow price will change (becoming positive) to indicate that that resource is now a scarse one.

To understand what will happen you need to run again the Solver

verifying with the solver1

Solution change (worst !)

And also the shadow price !

Verifying with the Solver

Decrease the grinding availability more than 20 (e.g. 80-25=55)

careful use of excel s sensitivity report
Careful use of Excel’s Sensitivity Report

All the analysis are valid only if we change only one input at time

When we make a statement about an input, we are assuming that all the other are held constant.

To see what happens when more than one input at time changes, you need to rerun the Solver.

mathematical model for factory b

Right hand side (r.h.s)

Left hand side (l.h.s.)

Mathematical model for factory B

Let analyze Factory B production problem

max 10x3 + 15 x3

4x3 + 4 x3 <= 45

5x3 + 3 x4 <= 60

5x3 + 6 x4 <= 75

x3, x3 >= 0

geometric interpretation1

x4

50

40

30

20

15

10

5

x3

5

10

15

20

30

40

50

Geometric interpretation

constitutes the set of the feasible solution for factory B

All non negative points

Two constraints 5 x3 + 6 x4 <= 75and 5 x3 + 3 x4 <= 60 do not play any role in defining the feasible region

5 x3 + 3 x4 = 60

Any point in F is such that5 x3 + 6 x4 < 75and 5 x3 + 3 x4 < 60

The grinding and polishing constraintsare always nonbinding

4 x3 + 4 x4 = 45

5 x3 + 6 x4 = 75

reduced costs in excel s sensitivity report1
Reduced costs in Excel’s Sensitivity report

Factory B optimal mix does not include standard product

The reduced cost of standard product is –5: the unit profit of thestandard product must be increase of 5 unit up to 15 before standard product will be worth producing

geometric view

x4

15x3 + 15 x4

50

40

All the points in the segment from

to

are optimal solution with the same value of PTOT

30

20

15

10

5

x3

5

10

20

30

40

50

Geometric view

Change the equation of the profit

PTOT = 10x3 + 15 x4

Actual optimal solution

shadow prices in excel s sensitivity report2
Shadow prices in Excel’s Sensitivity report

Grinding and polishing are non binding: the corresponding shadow prices are zero

Raw material is a scarce resource: the shadow price is positive and the allowable increase and decrease stay in a finite range

mathematical model for the multi plant
Mathematical model for the multi plant

max10x1 + 15 x2 +10x3 + 15 x4

4x1 + 2 x2 <= 80

5x3 + 3 x4 <= 60

2 x1 + 5 x2 <= 60

5 x3 + 6 x4 <= 75

4 x1 + 4 x2 + 4x3 + 4 x4 <= 120

x1 , x2,x3 , x4>= 0

More than two variables: we can solve it with the Solver

excel s answer report2
Excel’s Answer report

Vincolante = binding

references
References

H.P. Williams, Model building in mathematical programming, John Wiley, 1999

W. L Winston and S. C. Albright, Practical Management Science, Duxbury Press, 1997

L. Palagi, Electronic version of the lectures (2004) http://www.dis.uniroma1.it/~palagi