Analytica Optimizer

Optimizer is the highest edition level of Analytica. In includes all Enterprise features, plus the addition of powerful solver engines. It discovers decision values that minimize or maximize any quantified objective, subject to constraints. Or, in cases where an objective quantity is not present, it finds feasible solutions within constraint boundaries. It handles Linear Programming, Quadratic Programming, and general Non-Linear Programming, and automatically distinguishes among all of them. Decision variables can be continuous, semi-continuous, discrete (Integer or Boolean), or mixed. Best of all, Analytica optimizer seamlessly integrates optimization capability with all of Analytica's core features including Monte Carlo simulation and Intelligent Arrays, simplifying model structure and improving visual accessibility. It's a complete decision solution that combines solving power, scalability, and ease of use like no other optimization platform can.

Many features described below are part of the Structured Optimization feature set, new in Analytica Optimizer 4.3. For more details see What's New in Analytica 4.3

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Optimization models should be simple, especially when they're complex

Should optimization models be intuitively represented, transparent, scalable, and easy to build? We think they should. But traditional optimization interfaces fail to meet all of these goals.

Spreadsheet optimizations are suitable for smaller problems, but they are inherently two-dimensional and difficult to scale.
Algebraic modeling languages are much better than the straight programming notation that preceded them, but their lack of visual context can still make complex models inscrutable to anyone but the model designer.

Analytica makes optimization modeling as simple and intuitive as it should be at all levels of complexity. Influence diagrams and Intelligent Arrays keep the entire analysis path accessible, from modeling to decision making. It accomplishes this in several ways:

Keeping model structure and assumptions in plain view at all times
Combining optimization with sensitivity analysis to identify the inputs that have the most immediate influence on your objective value
Allowing you to add new scenarios for separate optimizations, simply by adding a scenario dimension to any input array
Adding Constraint nodes to allow you to specify arrays of constraints using simple inequality expressions
Allowing you to scale existing models easily using Intelligent Arrays

Full integration with Uncertainty, Dynamic equations, and Intelligent Arrays

Analytica’s core features including Monte Carlo sampling, Intelligent Arrays, and Dynamic definitions are all compatible with optimization. This allows you to implement advanced methods in the same intuitive manner as with all Analytica models:

Perform Stochastic Optimization by simply defining the objective as the expected value (mean) or fractile percentage threshold of a sampled distribution result.
Optimize Monte Carlo samples individually using Intelligent Array logic. It is easy to create a distribution of optimization results.
Define constraints using dynamic expressions for models with recursive dependency.

Power and scalability from state-of-the-art solver engines

Analytica Optimizer comes standard with Frontline’s Premium Solver package of solver engines to handle all types of optimization problem: Linear (LP), Quadratic (QP), and Non-Linear (NLP). It supports Continuous as well as Mixed-Integer and Semi-Continuous variable domains. (Semi-continuous variables can take on values within a bounded range or be zero.) The standard engine package supports up to 8,000 variables and 8,000 constraints for LP and convex QP problems, or 500 variables and 250 constraints for NLP problems.

For faster performance with extended or unlimited variables and constraints, you can also use premium engines including XPRESS, Gurobi, Mosek, KNITRO and OptQuest. See detail page for more information on premium solver engines.

...and much more

Additional features include:

Efficient internal representation of sparse matrices for large LP and QP optimizations
Easy identification of feasible subsets of constraints for LPs.
Genetic algorithms for non-smooth NLPs
User access to all internal engine settings and status flags
Automatic identification of problem type and optimization engine, or adherence to user overrides
Modular model design, allowing you to share portions of models and distribute modeling activities among individuals and teams.
Multiple starting points for NLP searches, determined automatically or specified by user as an array of initial guess vectors.

To purchase or Free trial

To purchase, complete our online order form here, or call us at (650) 212-1212 or email us at sales@lumina.com.

Or sign up for a free 30-day trial of Analytica Optimizer. Instruction and examples are provided in the Optimizer Guide, accessible from the Help menu.