Optimal solution of lp problem

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The forum discussion focuses on solving a linear programming (LP) problem defined by the objective function maximize f(x,y)=x+y, subject to the constraints sx+ty<=1 and x,y>=0. The user identified specific values for s and t that lead to different scenarios: s=-1 and t=-1 for infeasibility, and s=2 and t=-4 for unboundedness. The user struggled to find optimal solution values using fractions like 1/4 and 1/2, which did not satisfy the constraint sx-ty<=1.

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Equation: maximize f(x,y)=x+y
Subject to
sx+ty<=1
x,y>=0



So the question asks for values of s and t that make the problem infeasible, unbounded, and have an optimal solution. I completed the infeasible with values s=-1 and t=-1. unbounded I got s=2 and t=-4. for the optimal solution I tried using fractions like 1/4 and 1/2 but it does not satisfy sx-ty<=1. Thanks for help!
 
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jagbrar said:
Equation: maximize f(x,y)=x+y
Subject to
sx+ty<=1
x,y>=0

So the question asks for values of s and t that make the problem infeasible, unbounded, and have an optimal solution. I completed the infeasible with values s=-1 and t=-1. unbounded I got s=2 and t=-4. for the optimal solution I tried using fractions like 1/4 and 1/2 but it does not satisfy sx-ty<=1. Thanks for help!

You claim that (1/4)*x + (1/2)*y <= 1 is not satisfied. This statement only makes sense if it holds for ALL x and y >= 0. Is that the case?

RGV
 

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