Analytica Optimizer Guide

Introduction

This Guide explains how to use the Analytica Optimizer, which enhances Analytica 4.6 with powerful functions for finding optimal decisions and solving difficult equations.

It provides a Quick Start Tutorial in Chapter 1 and an introduction to the basic concepts of optimization, including linear, quadratic, and nonlinear programming in Chapter 2. Special topics for NLPs are also covered in Chapter 4. But, it's not a complete textbook on optimization. You might find it useful, especially for more challenging applications, to consult one of the many good textbooks on optimization.

If you're new to Analytica

You will find it easier if you first learn the essentials of Analytica before learning the Analytica Optimizer described here. Start with the Analytica Tutorial to learn the basics of interacting with Analytica and its modeling language, especially Chapter 5, Working with Arrays. It's important to have a good understanding of Intelligent Arrays to make good use of the Optimizer.

If you're new to the Analytica Optimizer

We suggest you start with Chapter 1, Quick Start, an introductory tutorial that takes you through the key steps to create a simple optimization. Then you should go on to Chapter 2, Optimization characteristics, which explains the general principles of optimization and the types of optimization, including Linear Programming (LP), Quadratic Programming (QP), and Non-Linear Programming (NLP). We also recommend Chapter 3, Optimizing with Arrays to master optimization with parametric analysis. Chapter 4 explains how to use optimization in models having dynamic influences and Monte Carlo-based uncertainties.

If you've used Analytica Optimizer 4.2 or earlier

The 4.3 release of Analytica introduced Structured Optimization, a new set of features that eliminates many difficult steps previously required for structuring optimizations in Analytica. For example, it can use a set of decision variables of varying dimensions, instead of requiring you to combine and flatten them manually. It introduces Constraints as a new object class. It can discover automatically whether your objective is linear, quadratic, or nonlinear, and apply the appropriate solver engine --and a whole lot more. So if you’ve used the Optimizer before, we strongly recommend that you learn about these new features so you can take full advantage of them and then read Chapter 1, Quick Start, and Chapter 4, Optimizing with Intelligent Arrays (at least). Even though Analytica 4.4 still supports functions from releases 4.2 and earlier of Optimizer for backward compatibility, you will likely want to learn and use the new functions instead.