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Vectorizing interdependent nested 4-for loop

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ingstalam
ingstalam on 12 Jan 2015
Edited: ingstalam on 12 Jan 2015
How to speed up this piece of code? How to vectorise this code? Is no other way possible?
for i1=1:num_agents % for all i
for rows=1:num_tasks*num_parts-1 % for all m_i,n_i in E_i
for ell=1:gL-G(rows,rows+1,i1) % for all ell
for i2=1:num_agents
xtemp = clearer;
% half-sum 1st part
for s = ell:gL%-G(rows,rows+1,i1)
if mod(rows,num_tasks)~=0
xtemp(i1,ceil(rows/num_tasks),mod(rows,num_tasks),s) = 1;
elseif mod(rows,num_tasks)==0
xtemp(i1,ceil(rows/num_tasks),num_tasks,s) = 1;
end
end
% half-sum 2nd part
for s = 1:ell+G(rows,rows+1,i1)-1
if s <= gL
if mod(rows,num_tasks)~=0
xtemp(i2,ceil(rows/num_tasks),mod(rows,num_tasks)+1,s) = 1;
elseif mod(rows,num_tasks)==0
xtemp(i2,ceil(rows/num_tasks)+1,1,s) = 1;
end
end
end
xtemp = xtemp(:);
Aineq(counter,:) = xtemp';
bineq(counter) = 1;
counter = counter + 1;
end
end
end
end

Answers (1)

Rick Rosson
Rick Rosson on 12 Jan 2015
  1. Did you pre-allocate Aineq prior to the loop?
  2. Did you pre-allocate bineq prior to the loop?
  2 Comments
ingstalam
ingstalam on 12 Jan 2015
Yup.
Aineq = spalloc(J*K+J*K+I*ELL+I*I*gL*(J*K-1),matwid,3*I*J*K*ELL+I*I*gL*(J*K-1)*(G_max)); % Allocate Aineq
bineq = zeros(J*K+J*K+I*ELL+I*I*gL*(J*K-1),1); % Allocate bineq
ingstalam
ingstalam on 12 Jan 2015
Edited: ingstalam on 12 Jan 2015
In fact i used sparse matrix allocation to speed up the results.

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