Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex …

How to develop effective algorithms for nonlinear discrete/continuous? How to improve relaxation? How to solve nonconvex GDP problems to global optimality?

Mixed Integer Nonlinear Programming (MINLP) Mixed integer programming problems are defined as those where some or all of the decision variables are only allowed to be integers.

Mixed-integer non-linear programming (MINLP) is defined as a method for solving non-linear optimization problems that involve both continuous and discrete decision variables, often used …

It uses a technique called "Outer Approximation", which proceeds as follows: take a solution to the "relaxed" problem (i.e., one where the integer constraints are allowed to take on continuous …

Oct 14, 2024 · Mixed-integer nonlinear programs (MINLPs) arise in domains as diverse as energy systems and transportation, but are notoriously difficult to solve, particularly at scale.

Find a good feasible solution, i.e., an upper bound. Iteratively improve upper and lower bounds. 1. Nonlinear branch and bound. Solve a continuous nonlinear relaxation at each node. Nonlinear …