Analytica Optimizer

What is Analytica Optimizer?

Optimizer is the highest editing level of Analytica. It includes all the company's features, plus the addition of powerful resolution mechanisms. It discovers decision values that minimize or maximize any quantified goal, subject to restrictions. Or, in cases where an objective quantity is not present, it finds viable solutions within the limits of the restriction. It handles Linear Programming, Quadratic Programming, and general Nonlinear Programming and automatically distinguishes between all of them. Decision variables can be continuous, semi-continuous, discrete (Whole or Boolean) or mixed. Best of all, Analytica Optimizer seamlessly integrates optimization capability with all of Analytica's key features, including: Monte Carlo simulation and smart arrays, simplifying model structure and improving visual accessibility.

Optimization models should be simple, especially when they are complex

Should optimization models be intuitively represented, transparent, scalable, and easy to build? We think they should.

But traditional optimization interfaces fail to achieve all of these goals.

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

Analytica makes optimization modeling as simple and intuitive as it should be at all levels of complexity. Influence diagrams and smart matrices keep the entire path from accessible analysis, from modeling to decision making. This is accomplished in several ways:

• Keeps the structure and assumptions of the model always in sight;
• Combines optimization with sensitivity analysis to identify inputs that have the most immediate influence on their objective value;
• Allows you to add new scenarios for separate optimizations by simply adding a scenario dimension to any input array;
• Adds constraint nodes to allow you to specify constraint arrays using simple expressions of inequality;
• Allows you to easily scale existing models using Smart Arrays.

Full integration with uncertainty, dynamic equations and smart matrices

Analytica's key features, including Monte Carlo sampling, smart arrays, and dynamic definitions, are compatible with optimization. This allows you to implement advanced methods in the same way intuitively as in all Analytica models:

• Perform systematic optimization by simply defining the objective as the expected value (mean) or the fragile percentage limit 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 of state-of-the-art resolution mechanisms

Analytica Optimizer uses Frontline Software's Premium Solver Solution package of resolution mechanisms to handle all kinds of optimization problems: Linear (LP), Quadratic (QP), and NonLinear (NLP). This package contains three mechanisms:

1.     LP / Quadratic

2.     NonLinear GRG

3.     Evolutionary

Analytica Optimizer can automatically choose the solver engine to match the problem, detecting whether it is linear, quadratic, or more complex. It supports continuous variable domains as well as mixed and semi-continuous integers. (Semi-continuous variables can assume values within a limited range or be zero.) The standard engine package supports up to 8,000 variables and 8,000 constraints for LP and convex QP issues, or 500 variables and 250 restrictions for NLP problems.

For faster performance or a larger number of variables and constraints, you can add premium engines including FICO's XPRESS, Gurobi, Mosek, KNITRO, and OptQuest. These are some of the most powerful resolution mechanisms available in the world. They are connected directly to Analytica Optimizer with full integration of all features, including uncertainty, dynamic simulation, and smart arrays. In fact, if you're already using one of these solvers with your algebraic pattern, try a more visual and flexible way to define and run optimization issues with Analytica. See details and how to get the best resolution mechanisms.

System requirements

Run on Windows computers, including Windows 10, Windows 8, Windows 7, and current Windows Server 2012. Each edition needs at least 1 GB of RAM. We recommend 3 or 4 GB of RAM to run large models.