GAMS - An Introduction

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Organizer: Frederik Fiand, Lutz Westermann
Location: Room 1e. Berlin
Date: 2018-09-11 (15:00 - 17:00)
Get ready to learn the basics of GAMS to develop algebraic models and solve them using state-of-the-art algorithms. In this workshop, the key concepts of GAMS and the fundamentals of the language (e.g. sets, data, variables, equations) will be introduced. The main part will consist of a demonstration, where we are going to build a simple optimization based decision support application from scratch. We show how GAMS supports an easy growth path to larger and more sophisticated models, promotes speed and reliability during the development phase of optimization models, and provides access to all of the most powerful solver packages. Along the way we will look at some of the data management tools included in the GAMS system and show how to analyze and debug large problems using the various tools available within GAMS. This introduction assumes no familiarity with GAMS. There will be time for questions both during and at the end of this workshop.

Nonlinear Programming with Artelys Knitro

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Organizer: Jean-Hubert Hours
Location: Room 1f. Brussels
Date: 2018-09-11 (15:00 - 17:00)
Artelys Knitro is a state-of-the-art nonlinear solver and is widely considered as the most advanced of its kind. It offers a large applicability as well as cutting-edge performance on nonlinear continuous models. In this workshop, we cover all Knitro algorithms into details both from a theoretical and a more user-oriented perspective. The new release of Artelys Knitro introduces a novel solver for nonlinear optimization problems with conic constraints. It is a first of its kind because it is a specialized interior-point algorithm for second-order cone programs (SOCPs) which also allows for general nonlinear non-convex constraints. Knitro 11.0 features a new C API, enabling users to build complex optimization models piece by piece and to provide structural information about their problems, such as linear, quadratic or conic constraints structures. Finally, several other numerical improvements on convex programs as well as ill-conditioned problems have been introduced with this release and will be presented.