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.

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