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12-15-2016 01:04 AM

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Can Linear Programming Simplex Method VI solve the optimization problem with real value variables (x>=0 or x<0)? If yes, how?

Solved! Go to Solution.

12-15-2016 09:57 PM

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12-15-2016 11:03 PM

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Solution

Accepted by topic author ZDX

12-16-2016 06:02 AM

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Assuming your (potentially) negative variables have constraints (say -1000) you can offest them accordingly and adapt your input data correspondingly.

replace x0 >= -1000 with X0 = (x0 + 1000) >= 0

Don't use negative constraints unnecesseraly big as it may results in numerical issues.

Solution

Accepted by topic author ZDX

12-16-2016 10:22 AM

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I've created a quick example (Lv2014) that finds the minimax solution for three equations with two variables.

The solution has both variables negative so using the raw algorithm returns {0, 0}. If you increase the variables offset parameter, the actual solution { -4.86. -0.49} is found for any offset value >= 4.87.

I hope this works for you!

12-19-2016 02:52 AM

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Thanks for your help. It works for me!