# Maximizing the product of a set of dot products

So suppose we have a set of vectors $$X$$ and we want to approximate the maximum of the following:

$$\prod_{x \in X} b \cdot x$$

where the components of $$b$$ sum to $$1$$

If it matters the components of each $$x$$ sum to $$1$$ as well.

What algorithm would you use to do this?

Sorry if this belongs on the mathematics exchange, I was stuck between the two

• Are you familiar with linear programming? – Pål GD Mar 30 at 21:43
• Yes. But this objective function is nonlinear isn't it? – Justin Perez Mar 30 at 23:56
• Interesting problem! The mention that you want to approximate the maximum makes me think you might be asking from a practical perspective. If so, can you share any information about typical problem parameters (e.g., number of dimensions, size of the set $X$)? Have you considered trying some generic method like gradient descent or Newton's method? – D.W. Mar 31 at 17:26
• Thanks! The size of $X$ in my application is around 10, and the dimensions of the vectors are around 500. I had not considered gradient descent since I was both unsure of how to calculate the derivative of a function like this where the size of set of vectors is not known before hand, and also because I was not sure that there was guaranteed to be only one local maximum. I had not considered newton's method since I thought that method was designed to find roots not maxima. I was leaning towards was some kind of Monte Carlo approximation of the maximum, but I was unsure of how to go about this. – Justin Perez Mar 31 at 20:22