Published March 29, 2026
| Version v1.4.1
Software
Open
Tunny: The Grasshopper optimization tool
Authors/Creators
Description
Changed
- Hide the Expert tab in MainWindow UI
- Updated default preset button names in multi-objective sampler settings from product/tool-specific labels to behavior-based labels:
Exploitation DefaultExploration Default- Applied to HypE, NSGA-II, and SPEA-II settings pages
- Updated initial/default selection values in HypE, NSGA-II, SPEA-II, MOEA/D, and NSGA-III settings to make crossover/mutation behavior more explicit and consistent
Fixed
- Optuna-Dashboard Rhino3dm visualization error
v1.4.0 update info
Added
- Check agreement to Terms of Use on startup
- User must agree before the UI opens
- NEW sampler support
- Swarm Intelligence
- PSO (Particle Swarm Optimization)
- PSO sampler can use community mode
- GreyWolf (Grey Wolf Optimization)
- Whale (Whale Optimization Algorithm)
- PSO (Particle Swarm Optimization)
- Bayesian Optimization
- TuRBO (Bayesian Optimization with Trust Regions)
- CARBO (Constrained robust Bayesian optimization of expensive noisy black-box functions with guaranteed regret bounds)
- Robust GP (Robust Bayesian Optimization under Input Noise)
- Evolution Algorithm
- SPEA-II (Strength Pareto Evolutionary Algorithm II)
- HypE (Hypervolume Estimation Algorithm)
- These 2 samplers can use community mode
- Swarm Intelligence
- Sampler variable type handling
- Verified whether the sampler supports continuous or categorical variables and provided appropriate variable suggestions
- Show Confirmation whether to save optimization results for InMemory mode
- When using InMemory mode, a confirmation dialog appears to ask whether to save the results after optimization is complete
- Support for local license
- This is particularly useful for users in environments with restricted internet access or for those who prefer to manage their licenses locally.
Changed
- Disable the second Live Chart when there is only one objective function
- The second chart's checkbox is unchecked by default when single-objective optimization is used
- Made it clear that the UI's Timeout corresponds to the Study's Timeout
- The display category for samplers like Random has changed from Misc to Exploration in the UI
- HEBO supports multi-objective optimization and Human-in-the-loop optimization
- Significantly improved Python environment performance
- By implementing a singleton pattern and eliminating the need to repeatedly launch Python environments, performance has been dramatically enhanced
- Including optunahub's samplers
- Eliminated the need for git or internet connectivity, improving performance.
- Removed ForceReload option
Fixed
- Null exception when handling large numbers of attributes
- Race condition in AttributeManager, ObjectiveManager, and ArtifactManager where values could become stale or empty due to concurrent access from the UI thread and worker thread during optimization
- Cached manager results so worker thread reads from cache instead of accessing Grasshopper UI objects directly
- Added IsNewSolutionCompleted flag to GrasshopperManager to ensure worker thread waits for all GetValues to complete after recalculation
- Fixed SolutionManager.RecalculateAsync to subscribe to SolutionEnd event before triggering NewSolution, preventing a potential deadlock when the solution completes synchronously
- When the rhp license check encounters a load error, an exception occurs that prevents the Tunny UI from launching
- To address this, the behavior has been modified to skip the license check and instead launch in Community Edition
- To avoid cases where the objective function value cannot be obtained under race conditions, we implemented a retry mechanism if the value is null.
Notes
Files
Tunny-gh/Tunny-v1-v1.4.1.zip
Files
(348.4 kB)
| Name | Size | Download all |
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md5:fe5b554347201d4908fed605ca431c75
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Additional details
Related works
- Is supplement to
- Software: https://github.com/Tunny-gh/Tunny-v1/tree/v1.4.1 (URL)
Software
- Repository URL
- https://github.com/Tunny-gh/Tunny-v1