Linear Programming Model Calculations
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Question 14 only.
Figure E.10 Solution
Variable Variable Original coefficient
Label Value Coefficient Sensitivity
x1 3.125 7 0
x2 28.125 5 0
x3 0 2 0.75
Constraint Original Slack or Shadow
label RHV Surplus Price
MachineA 150 0 0.25
MachineB 100 0 1.25
MachineC 160 100.625 0
Objective Function Value: 162.5
Sensitivity Analysis and Ranges
Objective Function Coefficients
Variable Lower Original Upper
Label Limit Coefficient limit
x1 5.2857 7 8.3333
x2 4.2 5 11.6667
x3 no limit 2 2.75
Right-Hand Side Values
Right Hand Side Values
constraint Lower Original Upper
label limit Value Limit
Extrusion 60 150 166.6667
Packaging 90 100 250
Additive 59.375 160 no limit
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Solution Summary
Linear programming model calculations are investigated.
Education
- BSc , Wuhan Univ. China
- MA, Shandong Univ.
Recent Feedback
- "Your solution, looks excellent. I recognize things from previous chapters. I have seen the standard deviation formula you used to get 5.154. I do understand the Central Limit Theorem needs the sample size (n) to be greater than 30, we have 100. I do understand the sample mean(s) of the population will follow a normal distribution, and that CLT states the sample mean of population is the population (mean), we have 143.74. But when and WHY do we use the standard deviation formula where you got 5.154. WHEN & Why use standard deviation of the sample mean. I don't understand, why don't we simply use the "100" I understand that standard deviation is the square root of variance. I do understand that the variance is the square of the differences of each sample data value minus the mean. But somehow, why not use 100, why use standard deviation of sample mean? Please help explain."
- "excellent work"
- "Thank you so much for all of your help!!! I will be posting another assignment. Please let me know (once posted), if the credits I'm offering is enough or you ! Thanks again!"
- "Thank you"
- "Thank you very much for your valuable time and assistance!"
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