# Optimization without knowing function's form or derivative

I understand that this question may not have a corresponding answer.

We are developing a control algorithm using dynamic programming. Effectively we are change one input variable and then plot the results to generate a system operating curve (SOC). Because of the complicated nature of the system and DP, the DP part is a "black box" and we can not analytically predicate the results of the DP solution. The DP solution has over a possible 54 million states and is used in a large fast-time Monte-Carlo simulation of millions of simulations. These two factors make it impossible to know the analytic form of the function.

Right now we are just trying a couple of reasonable points and seeing what happens. I like to take this a step further and introduce a level of optimization. However we don't know the form of the function and its subsequent derivative.

We do have a specific result we are striving for however. Suppose the DP solution is defined q|x where x is the tunable DP input. q|x is used as an input into function, f, where we want f(q|x) = y

f(q|x) = y


I have written up a simple 1D bisection in Matlab. Note for testing, I just picked an arbitrary function, f(x) = x, it can be whatever you want. Just remember that when I run this for real, I will not know the function form. Can I do something better than this simple implementation?

%% INPUTS
clc; clear all;
% Initial costs
costLow = 1e-9;
costHigh = .5;
costGuess = .1;

% Result goal
resultGoal = 0.001;

% Search conditions
maxIterations = 20;
tol = 0.0001;

f = @(x)(x);

%% CALCULATE
isConverge = false;
numIterations = 0;

% Calculate initial points
resultLow = f(costLow);
resultHigh = f(costHigh);

while numIterations < maxIterations && ~isConverge
disp(costGuess);
resultGuess = f(costGuess);

% Test if result converged
if abs(resultGuess - resultGoal) < tol
isConverge = true;
break;
end

% If not converged, set new guess
if resultGuess > resultGoal
costHigh = costGuess;
else
costLow = costGuess;
end
%costGuess =  mean([costHigh costLow]);
costGuess = exp(mean(log([costHigh costLow])));

% Loop housekeeping
numIterations = numIterations + 1;
end

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Why can't you just use fzero? –  Xodarap Jun 21 '11 at 17:37
@Xodarap, A builtin Matlab function is a possibility but due to the complexity of the problem and simulation framework, I would prefer to avoid it. I also like like to fully understand the optimization problem, hence another reason why I asked this question. –  Elpezmuerto Jun 21 '11 at 18:11