Using Sqrt or Pow in Objective function

[Eamonn Maguire]

Hi there,

Thanks for the great work! I'm a little stuck on one part of m objective function. I'm minimising the distances between the product of a set of features multiplied by learned weights and another given value. 

However, in my loss function, I'd like to do this 

obj_exp = LpAffineExpression()   
    
for doc_idx, doc in enumerate(documents):
        exp_doc = LpAffineExpression()       
        for f_idx,feature in enumerate(doc):
            exp_doc += weights[f_idx] * feature
    
        obj_exp +=  math.pow((1-lpSum(exp_doc)) - market_effects[doc_idx],2))

Is there any way to do this in Pulp?

Thanks! 

[Stuart Mitchell]

Sorry pulp can't handle non-linear expressions.

The gurobi solver can though

Stu

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Stuart Mitchell

PhD Engineering Science

Extraordinary Freelance Programmer and Optimisation Guru

www.stuartmitchell.com

[Yaron Kretchmer]

sqrt/pow and non-linear. But you can approximate them using MILP, maybe that'll work for you