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Interpreting LINDO Output in Linear Programming Optimization

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Based on the attached file, please anwer:

a. Give the complete optimal solution
b. What constraints are binding?
c. What would happen if the coefficient of X1 is increased by 6?
d. What would happen if the right-hand-side value of constraint 1 decreased by 10?
e. Which right-hand-side would you be most interested in increasing? Why?

The attached file (.JPG) format is a study question that is used as a "Do it on your own" type of exercise. I'm learning how to use the LINDO software right now.
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The answers I came up with were as follows:
a. 30(0)+25(66)+22(0)+20(42)=0+1650+0+840=2490
b. not sure-- how can I tell?
c. The solution would have to be recalculated because the allowable increase for coefficient of X1 is limited to 5.5. (But I don't know if that's a complete answer???)
d. There would be no effect on the optimal solution because the allowable decrease for the right-side range is infinity. (But I don't know if that is a complete answer???)
e. I'm not sure... how can I tell?

If you would please provide the correct answers, it would help my studies. Thank you. It should be an easy interpretation for anyone who is familiar with the software.

Thank you,

-T

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Solution Summary

LINDO output is interpreted.

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  • 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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