AMPL Optimization LLC
900 Sierra Pl. SE
Albuquerque, NM 87108-3379
AMPL Optimization LLC develops and supports the AMPL modeling language, the most powerful and natural tool for working with the large, complex linear and nonlinear optimization problems that arise in diverse applications. The AMPL language is notable for its convenient support of extended problem formulations and advanced algorithmic features. AMPL Optimization distributes AMPL and large-scale solvers including CONOPT, Gurobi, KNITRO, MINOS and SNOPT. AMPL is also distributed by solver developers Gurobi, IBM, Mosek and Ziena to complement their products. Over 30 other solvers work with AMPL, as do OptiRisk Systems' AMPL Studio and COM objects, and TOMLAB's MATLAB interface.
901 Marquette Ave., Ste. 3200
Minneapolis, MN 55402
FICO combines optimization with world-class predictive analytics and decision management tools to help businesses make connected, optimal and forward-looking decisions. We offer the FICO Xpress Optimization Suite - developed by Dash Optimization, and acquired by FICO two years ago. With its unique Mosel modeling language, FICO Xpress leverages 25+ years of experience in optimization to give you unprecedented flexibility and power. Come see why many OR leaders -including Edelman Winner American Airlines, which recently chose Xpress over all competitors for an Enterprise License - are calling the FICO Xpress Optimization Suite the new leader in optimization.
926 Incline Way, #100
Incline Village, NV 89451
IBM is a leader in the field of operations research, and specifically in the discipline of optimization. We offer some of the world's most advanced optimization technologies for solving tough business and research problems - longer than anyone. Our award-winning tools and engines speak for our high standards and belief in innovation. And we're always thinking of something new. See for yourself why more than 1,000 universities use IBM ILOG Optimization for research and teaching, and more than 1,000 commercial customers, including over 160 of the Global 500, use IBM ILOG Optimization in some of their most important planning and scheduling applications.
FICO - Building Optimization Applications in FICO Xpress
Sunday-SC19, 2:30pm-3:15pm, Room 383
This tutorial will focus on developing and deploying complete optimization applications using FICO’s array of mathematical modeling and optimization tools. These tools can be used for modeling, solving, analyzing and visualizing optimization problems, and integrating them seamlessly in business applications. During this tutorial, we will explain how Xpress-Mosel, Xpress-IVE and Xpress-Application Developer can decrease development time for new optimization applications and enable you and your customers to make smarter decisions. The proven technologies offered by FICO can be used in range of applications such as supply chain management, transportation, finance, energy, manufacturing, retail, insurance and manufacturing industries, to name a few.
IBM ILOG CPLEX Optimization Studio 12.2
Sunday-SD03, 4:30-5:15pm, Room 361
IBM ILOG CPLEX Optimization Studio supports the rapid development and deployment of both mathematical programming and constraint programming models, from a powerful integrated development environment using the Optimization Programming Language (OPL), through programmatic APIs or using 3rd party modeling interfaces. In this tutorial we will explore the comprehensive capabilities now offered in a single product offering, spanning the development, tuning, analysis and deployment of optimization models. We will review IBM's machine/platform-independent keyless licensing policies, and highlight key features of the latest release, including performance improvements in the IBM ILOG CPLEX Optimizers and Gantt charts for reviewing and debugging scheduling models in the CPLEX Studio IDE.
AMPL-Attacking Hard Mixed-integer Optimization Problems Through the AMPL Modeling Language
Tuesday-TB04, 11:30am, Salón Azul
There are many tricks for formulating complex optimization models by use of integer variables, but what’s to be done when even the most advanced solvers can’t produce results in reasonable time? A series of examples show how substantial improvements in performance can be achieved through carefully focused troubleshooting and experimentation facilitated by the power and flexibility of the AMPL modeling language and its solver interfaces.