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ounces. W = jars o f Western Foods Salsa M = jars o f Mexico City Salsa leads to the formulation ( units for constraints

ounces.
W= jars of Western Foods Salsa
M= jars of Mexico City Salsa
leads to the formulation (units for constraints are ounces):
Max1W+1.25M
s.t.
5W+7M4,400ozof whole tomatoes
3W+1M2,400ozof tomato sauce
2W+2M1,600ozof tomato paste
W,M0
The computer solution is shown below.
Optinal Objective Value =850.00000
Variable Value Reduced Cost
w ,600.00000,0.00000
M,200.00000,0.00000
Constraint slack/Surplus Dual Value
0.00000,0.12500
1,0.00000,0.12500
2,400.00000,0.00000
30.00000,0.18750
Variable objective Allowable allowale
Coefficient
alowabl
ncrease
0.25000
Allowable
0.10714
Constraint
RHS Allowable
Increase
Allowable
Decrease
400.00000
400.00000
342.85714
(a) What is the optimal solution, and what are the optimal production quantities?
(b) Specify the objective function ranges. (Round your answers to five decimal places.)
Western Foods Salsa
Mexico City Salsa
(c) What are the dual values for each constraint? Interpret each.
constraint 1
One additional ounce of whole tomatoes will improve profits by $0.188.
One additional ounce of whole tomatoes will improve profits by $400.00.
One additional ounce of whole tomatoes will improve profits by $0.125.
Additional ounces of whole tomatoes will not improve profits.
constraint 2
One additional ounce of tomato sauce will improve profits by $0.188.
One additional ounce of tomato sauce will improve profits by $400.00.
One additional ounce of tomato sauce will improve profits by $0.125.
Additional ounces of tomato sauce will not improve profits.
constraint 3
One additional ounce of tomato paste will improve profits by $0.188.
One additional ounce of tomato paste will improve profits by $400.00.
One additional ounce of tomato paste will improve profits by $0.125.
Additional ounces of tomato paste will not improve profits.
(d) Identify each of the right-hand-side ranges. (Round your answers to two decimal places. If there is no upper or lower limit, enter No LIMIT.)
constraint 1
to
constraint 2
to NO LIMIT
constraint 3
to
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