Preallocation within an optimization loop

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Barend Kok
Barend Kok el 24 de Nov. de 2020
Comentada: Barend Kok el 24 de Nov. de 2020
Hi everyone,
Bear with me, since I am new to Matlab. But I am doing some monte carlo analysis of an (economic) optimization problem. Which looks as follows:
runs = 1000;
nsamples = 1:runs;
for i = 1:length(nsamples)
% Distributions
price_B = random(dist_price_B);
yield_B = random(dist_yield_B);
seedc_B = random(dist_seedc_B);
fertc_B = random(dist_fertc_B);
herbc_B = random(dist_herbc_B);
prot_cont_B = random(dist_prot_cont_B);
yield_CD = random(dist_yield_CD);
% Intermediates profit function
benefitkg_B = price_B + nit_fix_B;
benefitha_B = yield_B * benefitkg_B + subs_B;
costha_B = seedc_B + fertc_B + herbc_B;
benefitl_CD = price_CD;
benefitha_CD = yield_CD * density_C * benefitl_CD;
benefitkg_CM = price_CM;
benefitha_CM = yield_CM * density_C * benefitkg_CM;
benefitha_C = benefitha_CD + benefitha_CM;
costcow_C = initialc_C + feedc_C + operatc_C;
costha_C = costcow_C * density_C;
% Intermediates protein supply
prot_supply_B = yield_B * prot_cont_B;
prot_supply_C = density_C * (yield_CD * prot_cont_CD + yield_CM * prot_cont_CM);
prot_supply = @(x)(x(1) * prot_supply_B + x(2) * prot_supply_C);
% Profit function, minimizing this is the objective.
Total_Profit = @(x)(-1 * (x(1) * (benefitha_B - costha_B) + x(2) * (benefitha_C - costha_C)));
% Inputs for fmincon.
Guess = [1 0];
LB = [0, 0];
UB = [1, 1];
A = [-prot_supply_B, -prot_supply_C]; % A*x <= b --> protein_supply >= protein_demand --> -protein_supply <= -protein_demand
b = -1000; % -(x(1) * prot_supply_B + x(2) * prot_supply_C) <= b
Aeq = [1, 1]; % x(1) + x(2) = 1
beq = 1;
% Minimization
xopt (i, :) = fmincon(Total_Profit,Guess,A,b,Aeq,beq,LB,UB,[],options);
% Create the value for total profit over the years and plot
Total_Private_Profit (i, :) = - Total_Profit (xopt);
The code runs perfectly and gives me the output I need (I left the plotting of histograms and other non-important stuff out).
A warning tells me to pre-allocate both 'xopt' and 'Total_Private_Profit' to save time. But as I am trying to do so, the outcomes change and become unreasonable.
My question is therefore: How should I preallocate 'xopt' and 'Total_Private_Profit' properly without screwing the outcomes?
Thank you in advance.
Barend

Respuesta aceptada

Matt J
Matt J el 24 de Nov. de 2020
Editada: Matt J el 24 de Nov. de 2020
xopt=nan(runs,2); %Pre-allocate
Total_Private_Profit=nan(runs,2); %Pre-allocate
for i = 1:length(nsamples)
...
xopt(i, :) = fmincon(Total_Profit,Guess,A,b,Aeq,beq,LB,UB,[],options);
% Create the value for total profit over the years and plot
Total_Private_Profit(i, :) = -Total_Profit (xopt);
end
  3 comentarios
Matt J
Matt J el 24 de Nov. de 2020
Editada: Matt J el 24 de Nov. de 2020
zeros and ones would work, too. I prefer nans because there can be no confusion that they represent anything but missing data.
Barend Kok
Barend Kok el 24 de Nov. de 2020
Thank you!

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