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Published March 29, 2026 | Version v1.4.1

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 Default
    • Exploration 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)
    • 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
  • 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

If you use this software, please cite it as below.

Files

Tunny-gh/Tunny-v1-v1.4.1.zip

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