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Thread Subject:
Lagrangian Relaxation

Subject: Lagrangian Relaxation

From: Ozge Taskan

Date: 11 Apr, 2010 15:50:04

Message: 1 of 1

Hi,
I am pretty new at Matlab.
I am dealing with a problem with has one constraint and I try to solve the problem by using lagrangian relaxation method. However at first I try to get a result for my subproblem.

My model is (not in matlab form):
Min over i (sum(h(i).s(i)))
over i (sum(m(i)/sum(m))* beta(si)) >= beta0
0<=s

I try to solve this with
function f = myfun(s)
h=[100 200 300];
m=[1 2 3];
u=[100 100 100];
beta0=0.98;
s0=[0 0 0];
f =sum(h.*s)+sum(u.*(beta0-sum((m.*poisscdf(s-1,100))./sum(m(1:3)))));

>>lb=[0 0 0];
>>A=[];
>>b=[];
>>Aeq=[];
>>beq=[];
>>s = fmincon(@myfun,s0,A,b,Aeq,beq,lb,ub)

however I cannot get a solution other than zeros. However I expect that it should assign values to s to minimize.

If you help me, I would be very glad.
Best regards,
Ozge

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