Released: May 15, 2018
- dprepro was completely re-written and has many new features, including the ability to execute arbitrary Python scripting in templates
- Dakota's graphical user interface (GUI) was updated with many new features and bugfixes
- Dakota now includes a suite of gradient-based optimization algorithms from the SNL-developed Rapid Optimization Library (ROL).
- Bayesian calibration capabilities received several enhancements, including improved concurrency in evaluating optimal experimental designs
Comprehensive release notes are available at Dakota 6.8 Release Notes