‎ Optimization Overview

 

The optimization capability in Detect3D is a powerful way to automate the positioning of flame detectors. Using Genetic Algorithms, Detect3D “evolves” an optimized layout over time based on the user-defined locations, target coverage, and restrictions. This task can still be performed manually if required – optimization is not always necessary, especially in cases where the detector setup is relatively obvious.

 

The algorithm is powerful enough to calculate the minimum number of detectors required to achieve the target criteria, by adjusting the detector count automatically. However, the setup of the algorithm is very flexible, and requires some understanding of the available options to fully realize the potential of optimization.

 

Results from the optimization should never be blindly accepted and should always be given a “reality check” to see whether the resulting layout is sensible. The result from the optimization is very rarely a single layout – multiple layouts are provided that all achieve the target coverage criteria, so that the final decision is always made by the user. It’s also possible to edit the optimized layout once it has been added to the project.

 

Optimization is a powerful tool, but it must be used wisely.