The quantity $($RHS Value$)($Final Value$)$ of a constraint will give you:

Devon$$s Baked Goods would like to maximize its profit from the production of its cookies. Devon produces two types of cookies, Chocolate Chip and Vanilla Sprinkle. Each production line at Devon$$s has three employees and one oven working an $8-$hour shift. Tori, the Operations Manager, has developed the linear program shown below to maximize the profit.

Chocolate Chip

Vanilla Sprinkle

Solution

$80$

$240$

LHS

Profit $/$ Cupcake

$$0\mathrm{.}50$

$$0\mathrm{.}40$

$xxx$.$xx

Sign

RHS

Oven Hours

$0\mathrm{.}04$

$0\mathrm{.}02$

$8$

$<=$

$8$

Labor Hours

$0\mathrm{.}06$

$0\mathrm{.}08$

$24$

$<=$

$24$

Variable Cells

Cell

Name

Final Value

Reduced Cost

Objective Coefficient

Allowable Increase

Allowable Decrease

$B$$4$

Optimal Solution Chocolate Chip

$80$

$0$

$0\mathrm{.}5$

$0\mathrm{.}3$

$0\mathrm{.}2$

$C$$4$

Optimal Solution Vanilla Sprinkle

$240$

$0$

$0\mathrm{.}4$

$0\mathrm{.}266666667$

$0\mathrm{.}15$

Constraints

Cell

Name

Final Value

Shadow Price

Constraint R$.$H$.$ Side

Allowable Increase

Allowable Decrease

$D$$7$

Oven Hours LHS

$8$

$8$

$8$

$8$

$2$

$D$$8$

Labor Hours LHS

$24$

$3$

$24$

$8$

$12$

The quantity $($RHS Value$)($Final Value$)$ of a constraint will give you:

Reduced Cost

Shadow Price

Slack or surplus

The feasibility of the model

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