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I have a "linear" equation set as follows, with nonlinear optimization goal.

P(0) + P(1) = 1

P(0, 0) + P(0,1) = P(0)

P(0) < 1

P(1) < 1

P(0,0) > 0

P(0,1) > 0

P(1) > 0

The goal to optimize is

$P(0,1)\log{P(0,1)} + P(1)\log{P(1)} - (P(1)+P(0,1))\log{((P(1)+P(0,1)))}$

I know nonlinear optimization could be hard, but is there quick technique dor solving this special kind of nonlinear optimization problem?

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    It looks like you did not give all information needed. What is your optimization variable? Is it some kind of funktion $p$? Or is it just the values $P(0)$, $P(1)$,...? Anyway: Your objective function is convex, the constraints are linear, so a lot of theory applies here...2012-02-05
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    Sorry for confusion here. P(0) is a variable; in here, 0 is rather a label for the variable, not input for the function..2012-02-05
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    And what are $P(0,0)$ and $P(0,1)$?2012-02-06
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    P(0,1) and P(0,0) are optimization variables too.2012-02-07

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