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Listing possible combinations of integers, given constraints (Gear Ratio Related)

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Terence Ng
Terence Ng on 13 Sep 2018
Commented: Terence Ng on 13 Sep 2018
The problem:
Let Gear Ratio = ( 1 + N3/N1 )/( 1 - ( ( N3*N4 )/( N5*N2) ) ), where N1, N2, ..., N5 must be integers. I'm looking to list combinations of N1, N2, ..., N5 that make the gear ratio fall within a specified range (i.e. 50 - 60), with upper limits to what the values of N1, N2, ..., N5 can be (i.e. 150).
I've done it using a for loop then and listing / filtering values that are within the given constraints, but am looking for a more efficient solution given that the for loop takes forever to finish.
I looked into using ndgrid from the following example: https://www.mathworks.com/matlabcentral/answers/308775-integer-division-problem-gear-ratio-related
But the arrays created would be much too large.
Any ideas / hints would be appreciated!

  2 Comments

Walter Roberson
Walter Roberson on 13 Sep 2018
How does the equation distinguish between N2 and N5? Exchanging them does not change anything. You could create
[p, q] = ndgrid(1:150);
N25 = unique(p.*q);
And use N25 in calculation of the basic ratios, later substituting all N2 N5 pairs that multiply to that particular value.
Terence Ng
Terence Ng on 13 Sep 2018
Based on the equation, you're correct that N2 and N5 can be combined and substituted afterwards.
As Aquatris mentioned below, assuming I went with a "brute force" method I'd still be 4 for loops deep.
More than likely I'll revisit the problem and apply more constraints to reduce the number of solution sets.

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Answers (1)

Aquatris
Aquatris on 13 Sep 2018
Edited: Aquatris on 13 Sep 2018
One possibility is using an optimization. Here is a simple code for it using OPTI toolbox;
clear all,clc
% round() is used to enforce integer value
gr = @(N) (1+round(N(3))/round(N(1)))/(1- round(N(3))*round(N(4))/round(N(5))/round(N(2))));
% initial guess
x0 = [1 2 3 7 11]';
% lower and upper bounds for N = [N1 N2 N3 N4 N5]'
lb = zeros(5,1);
ub = ones(5,1)*150;
% Nonlinear Constraints for desired gear ratio range(cl <= nlcon(x) <= cu)
nlcon = @(x) gr(x);
cl = [50];
cu = [90]; % upper is chosen 90 cause initial guess give 88
% formulate the problem in OPTI toolbox
Opt = opti('fun',gr,'bounds',lb,ub,'x0',x0,'nl',nlcon,cl,cu)
[x,fval,exitflag,info] = solve(Opt); % this will try to minimize the
% gr function and since the lower
% limit is defined as 50, it will
% give a gear ratio close to 50
% if optimization is succesful
N_solution = round(x) % the necessary [N1 N2 N3 N4 N5]' = [2 2 3 7 11]'
gear_ratio = gr(N_solution) % achieved gear ratio = 55
The problem can be formulated in a similar manner for built-in Matlab function as well.

  3 Comments

Terence Ng
Terence Ng on 13 Sep 2018
Thank you for the input.
This is similar to what I had originally started out with (with the exception that I was using fmincon). The issue I had with formatting the problem as an optimization problem was that it would solve for a single solution when I was looking for the entire solution set, given that the problem has multiple solutions.
I found a page regarding multiple solutions for a global optimization problem https://www.mathworks.com/help/gads/multiple-solutions.html, that might be interesting to look into (though I don't have access to that toolbox).
I'll have to give it some more thought...
Aquatris
Aquatris on 13 Sep 2018
An alternative method would be a brute-force search as;
sol = [];
for n1 = 1:150
for n2 = 1:150
for n3 = 1:150
for n4 = 1:150
for n5 = 1:150
e = gr([n1 n2 n3 n4 n5]);
if(e < 60 & e > 50)
sol = [sol;n1 n2 n3 n4 n5];
end
end
end
end
end
end
where gr is the function from the answer I gave and each row of sol variable is a combination that would achieve desired gear ratio.
I ran the above code for 240 sec. and terminated it. It did not even reach n1 = 2 (it was at n1=1,n2=13,n3=21,n4=47,n5=134) but was able to find 150k possible combinations. So I do not think it is feasible to find all the combinations of n1 n2 n3 n4 n5 that give the desired gear ratio for your problem since I think there are billions of possible combinations.
Terence Ng
Terence Ng on 13 Sep 2018
This is currently the method I have. (I also gave up way before n1 was able to iterate once)
I agree with your statement that it doesn't seem feasible to find all the combinations, likely I'll have to apply more constraints to reduce the number of possible solutions.

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