In this paper, we present a review of deterministic software for solving convex MINLP
problems as well as a comprehensive comparison of a large selection of commonly …

This article provides a systematic review of recent progress in optimization-based process
synthesis. First, we discuss multiscale modeling frameworks featuring targeting approaches …

Decision trees usefully represent sparse, high-dimensional, and noisy data. Having learned
a function from these data, we may want to thereafter integrate the function into a larger …

This paper investigates the problem of target assignment and trajectory optimization in multi-
missile multi-target engagement scenarios. To avoid complex mixed-integer nonlinear …

In this paper, an open-source solver for mixed-integer nonlinear programming (MINLP)
problems is presented. The Supporting Hyperplane Optimization Toolkit (SHOT) combines a …

Generating polyhedral outer approximations and solving mixed-integer linear relaxations
remains one of the main approaches for solving convex mixed-integer nonlinear …

We consider convex constrained optimization problems that also include a cardinality
constraint. In general, optimization problems with cardinality constraints are difficult …

Nonlinear discrete optimization problems arise in many different disciplines, given the
modeling versatility associated with nonlinear constraints and discrete decision variables. In …

Nonlinear discrete optimization problems arise in many different disciplines, given the
modeling versatility associated with nonlinear constraints and discrete decision variables. In …

Decision-making optimisation problems can include discrete selections, eg selecting a
route, arranging non-overlap** items or designing a network of items. Branch-and-bound …