I am trying to simplify a nested for-loop. Any suggestions would be highly appreciated!
The structure of the problem in its crudest form is the follows:
comb=zeros(1,N); %where N is a large number like 100 comb(1)=1; for m2=1:N2 %where N2 is some predetermined number comb(2)=IX(m2,2); %where IX is some pre-determined matrix if consistent(comb) %where consistent(x) is a pre-specified fcn for m3=1:N3 comb(3)=IX(m3,3); if consistent(comb) for m4=1:N4 comb(4)=IX(m4,4); if consistent(comb) ...... %this needs to be continued in exactly the same fashion until I reach the (N-1)th nested loop for mN=1:NN comb(N)=IX(mN,N); if consistent(comb) tot_dist=min(tot_dist(comb),tot_dist) %where tot_dist(x) is a pre-specified fcn else end end ...... else end end else end end else end end
The basic problem is conceptually the same as this: start from a vector comb=(1,0,...0). Select a number out of N2 numbers to fill the comb(2) if that selection satisfies some consistency condition. Do this for each of the remaining N-2 entries in comb, but the consistency condition is path dependent in the sense that your selection for comb(2) affects the consistency of a proposed selection for comb(3). Finally i need to select among all legitimate comb's the one that minimizes some total distance criterion.
Is there a way to handle this type of problems? Thank you very much in advance!
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It sounds like a recursive problem to me.
What about something like
function comb = looper(comb, IX, n, N) if n > length(comb) return; end
for m = 1:N(n) comb(n)=IX(m,n); if consistent(comb) comb = looper(comb, IX, n+1, N); end end end
You could call it with something like:
N = [N1, N2, N3, ..., Nn]; comb = looper(0, IX, 1, N); tot_dist = min(tot_dist(comb), tot_dist);
The code for the small example incorporating Daniel's suggestion:
clear all clc global best_comb_d min_d result i D=[1 3 -1; 0 1 2; 0 0 1]; IX=[1 1 2; 0 2 3]; N=[1 2 2]; % D=[1 -1 2; % 0 1 3; % 0 0 1]; % IX=[1 2 1; % 0 0 2; % 0 0 3]; % N=[1 1 3]; a=2; min_d=a*sum(sum(abs(D))); best_comb_d=[1:3 min_d]; n=2; comb_d=[1 0 0 0]; %============== %Check intermediate steps i=1; result=zeros(10,4); %================ comb_d=looper(comb_d,IX,a,n,N,D); function comb_d=looper(comb_d,IX,a,n,N,D) global best_comb_d min_d result i if n>length(comb_d)-1 result(i,:)=comb_d; i=i+1; best_comb_d=comb_d*(comb_d(length(comb_d))<min_d)+best_comb_d*(comb_d(length(comb_d))>=min_d); min_d=min(min_d,comb_d(length(comb_d))); if comb_d(length(comb_d)-1)==IX(N(length(N)),length(IX(1,:))) comb_d(length(comb_d))=0; else comb_d(length(comb_d))=comb_d(length(comb_d))-D(comb_d(n-1),n-1); end return; end D_max=max(max(D)); for m=1:N(n) comb_d(n)=IX(m,n); if D(comb_d(comb_d(n)),n)>=0 d=(m~=N(n))*D(comb_d(n),n)+(m==N(n))*a*D_max; comb_d(length(comb_d))=comb_d(length(comb_d))+d; comb_d=looper(comb_d,IX,a,n+1,N,D); end end end
I hope this will extends well to cases with large N.
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