Analytic Solver
Analytic Solver Optimization - 100% upward compatible from the Excel Solver - handles every type and size of the conventional optimization problem (without uncertainty). Unlike other optimization software, it algebraically analyzes your model structure and maximally exploits multiple cores in your PC. You can solve nonlinear models 10 times larger, and linear models 40 times larger than the Excel Solver, get solutions much faster – and plug-in Solver Engines to handle up to millions of variables! Analytic Solver Simulation gives you easy-to-use, powerful Monte Carlo simulation and risk analysis, decision trees, and simulation optimization using Frontline’s advanced Evolutionary Solver. With 60 probability distributions plus compound distributions, automatic distribution fitting, rank-order and copula-based correlation, 80 statistics, risk measures and Six Sigma functions, multiple parameterized simulations and more.
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Artelys Knitro
Artelys Knitro is a leading solver for large-scale nonlinear optimization problems, offering a suite of advanced algorithms and features to address complex challenges across various industries. It provides four state-of-the-art algorithms: two interior-point/barrier methods and two active-set/sequential quadratic programming methods, enabling efficient and robust solutions for a wide range of optimization problems. Additionally, Knitro includes three algorithms specifically designed for mixed-integer nonlinear programming, incorporating heuristics, cutting planes, and branching rules to effectively handle discrete variables. Key features of Knitro encompass parallel multi-start capabilities for global optimization, automatic and parallel tuning of option settings, and smart initialization strategies for rapid infeasibility detection. The solver supports various interfaces, including object-oriented APIs for C++, C#, Java, and Python.
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Solver SDK
Use optimization and simulation models in your desktop, Web or mobile application. Use the same high-level objects (like Problem, Solver, Variable and Function), collections, properties and methods across different programming languages. The same object-oriented API is exposed "over the wire" through Web Services WS-* standards to remote clients in PHP, JavaScript, C# and other languages. Procedural languages can use conventional calls that correspond naturally to the properties and methods of the Object-Oriented API. Linear and quadratic programming, mixed-integer programming, smooth nonlinear optimization, global optimization, and non-smooth evolutionary and tabu search are all included. The world's best optimizers, from Gurobi™, XPRESS™ and MOSEK™ for linear, quadratic and conic models to KNITRO™, SQP and GRG methods for nonlinear models "plug into" Solver SDK. Easily create a sparse DoubleMatrix object with 1 million rows and columns.
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Model Predictive Control Toolbox
Model Predictive Control Toolbox™ provides functions, an app, Simulink® blocks, and reference examples for developing model predictive control (MPC). For linear problems, the toolbox supports the design of implicit, explicit, adaptive, and gain-scheduled MPC. For nonlinear problems, you can implement single- and multi-stage nonlinear MPC. The toolbox provides deployable optimization solvers and also enables you to use a custom solver. You can evaluate controller performance in MATLAB® and Simulink by running closed-loop simulations. For automated driving, you can also use the provided MISRA C®- and ISO 26262-compliant blocks and examples to quickly get started with lane keep assist, path planning, path following, and adaptive cruise control applications. Design implicit, gain-scheduled, and adaptive MPC controllers that solve a quadratic programming (QP) problem. Generate an explicit MPC controller from an implicit design. Use discrete control set MPC for mixed-integer QP problems.
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