I just joined the Boost community in order to begin a discussion of the merits of creating a library for function optimization. As a result, I discovered this thread on statistical distributions and mathematical special functions. This library has a single function minimization algorithm: Brent's one-dimensional parabolic interpolation. For my own work, I have implemented two other function optimization methods, neither of which are limited to one-dimensional problems and both of which are suitable for either minimization or maximization (or any other arbitrary ordering, for that matter).. The existing Brent's algorithm could be similarly generalized to handle orderings other than minimization. In addition, there are many other algorithms that could be included within an optimization library. This leads me to a general question about the library under discussion and the bit that I have been working on. Does it make sense to factor out the Brent's algorithm code and add it with mine into a new optimization library, or is it preferable to integrate my algorithms into the larger library? Given the early stage of development of optimization within the current library (compared. for example, with the diversity of statistical and mathematical functions), which is the best pathway to follow? As a new member of the Boost community, I appreciate your guidance. Thanks. Cheers, Brook