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1536. Latest developments for mixed-integer nonlinear programming in Artelys Knitro

Invited abstract in session MC-30: Continuous Solvers, stream Software for Optimization.

Monday, 12:30-14:00
Room: 064 (building: 208)

Authors (first author is the speaker)

1. Maxime Dufour
Artelys
2. Florian Fontan
Artelys
3. Hugo Chareyre
Artelys

Abstract

1 Introduction

Artelys Knitro is a mathematical programming solver for nonlinear and mixed-integer nonlinear problems. As input, it accepts linear structures, quadratic structures and black-box functions, with if possible, their first and second-order derivatives. Knitro relies on derivative-based algorithms to find locally optimal solutions. Knitro finds the global optimum for convex problems. For non-convex problems, Knitro converges to a first order stationary point (e.g. local optimum) for continuous models and is a heuristic for mixed-integer problems.

2 Recent improvements for MINLP applications

In this talk, we will present the algorithms implemented in Artelys Knitro for mixed-integer nonlinear problems in Knitro 14.0, and detail the recent developments for the nonlinear branch-and-bound algorithms. Since Artelys Knitro 13.0, the nonlinear branch-and-bound has been fully rewritten as parallel and deterministic. The algorithm has been greatly improved by adapting the ideas developed for mixed-integer linear programming. Those features include specific presolve operations and cuts for nonlinear applications, a heuristic portfolio to provide effort effective search improved better branching strategies and a restart procedure. It opens several perspectives for future developments and extensions for nonlinear models that we will present during this talk. We will show the improvements on the classical datasets for mixed-integer nonlinear problems.

Keywords

Status: accepted

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