Optimization - General-purpose optimization methods in ASAP
Updated: Apr 13, 2015
Author(s): Breault Research Organization
This technical publication describes enhanced optimization capabilities and the process for effectively using them in the Advanced Systems Analysis Program (ASAP®) from Breault Research Organization (BRO). New capabilities for optimization are in ASAP 2009, in addition to pre-existing optimization capabilities in ASAP.
The process of optimization, or minimization, in optical system design takes a set of the system’s defining parameters, such as surface curvatures, conics, optical properties, and so on, and systematically varies their values to reach a desired result, usually measured in terms of the distribution of energy at specified locations within the system. The system parameters that are adjusted are called variables, and the description of the desired system performance is referred to as the merit function.
The optimal solution, called the global minimum, consists of the set of variable values that locate the system that has the smallest value for the merit function that can be attained. Most systems have a range of potential solutions called local minima. Any system can have only one global minimum. In many situations, it is not possible to determine that a given solution is the global minimum. However, in most instances it is only necessary to locate a solution that meets the system requirements within some specified range.
ASAP provides the structure for enhanced optimization capabilities. Included in ASAP are three general-purpose optimization methods:
Each method is effective in finding optimal solutions for many different imaging and illumination systems.
Summary of document changes
This revision reflects a change in the user interface in ASAP 2009 V2R1. The Optimize menu now uses "Save System Under Evaluation" instead of "Save SUE". (Aug 26, 2009)
Content for the Optimization State File (OSF), a new feature in ASAP 2009, was added to this document. The OSF lets you save the current state of your optimization in a text file. It contains information identifying design variables with values, constraints, and any other user-specified limit; design objectives with target, weight and enabled state; objective constraints and associated penalty functions; selected exit criteria; as well as the applied optimization method with associated parameter values. Graphic files were also updated as needed. (Apr 23, 2009)