This paper surveys the machine learning literature and presents in an optimization
framework several commonly used machine learning approaches. Particularly …

A wide range of problems can be modeled as Mixed Integer Linear Programming (MIP)
problems using standard formulation techniques. However, in some cases the resulting MIP …

We study the modeling of nonconvex piecewise-linear functions as mixed-integer
programming (MIP) problems. We review several new and existing MIP formulations for …

In this chapter we want to demonstrate that in certain cases general mixed integer nonlinear
programs (MINLPs) can be solved by just applying purely techniques from the mixed integer …

Backbone represents a highly adaptable energy systems modelling framework, which can
be utilised to create models for studying the design and operation of energy systems, both …

We consider the problem of fitting a continuous piecewise linear function to a finite set of
data points, modeled as a mathematical program with convex objective. We review some …

We present novel mixed-integer programming (MIP) formulations for optimization over
nonconvex piecewise linear functions. We exploit recent advances in the systematic …

For univariate functions, we compute optimal breakpoint systems subject to the condition
that the piecewise linear approximator, under-, and over-estimator never deviate more than …

We propose mixed-integer programming models for fitting univariate discrete data points
with continuous piecewise linear (PWL) functions. The number of approximating function …

In general, to formulate a fuzzy-linear-programming problem with n S-shaped utility
(membership) functions, traditional methods require n or more extra binary variables …