Install-Package OPTANO.Algorithm.Tuner -Version
dotnet add package OPTANO.Algorithm.Tuner --version
<PackageReference Include="OPTANO.Algorithm.Tuner" Version="" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add OPTANO.Algorithm.Tuner --version
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#r "nuget: OPTANO.Algorithm.Tuner,"
#r directive can be used in F# Interactive, C# scripting and .NET Interactive. Copy this into the interactive tool or source code of the script to reference the package.
// Install OPTANO.Algorithm.Tuner as a Cake Addin
#addin nuget:?package=OPTANO.Algorithm.Tuner&version=

// Install OPTANO.Algorithm.Tuner as a Cake Tool
#tool nuget:?package=OPTANO.Algorithm.Tuner&version=
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Version 2.1.0 (2021-11-12)


  • Feature: Introduce addFinalIncumbentGeneration parameter to control a potential final incumbent generation.
    • By using a random subset of instances per generation, the current incumbent genome does not need to be stricly better than its predecessor. For example, the current incumbent genome may outperform its predecessor on the current instance set, but perform worse on all provided training instances.
    • While using a random subset of instances per generation to avoid overfitting is still recommended, adding a final incumbent generation ensures that OPTANO Algorithm Tuner always returns the fittest incumbent genome.
    • If the final incumbent generation is enabled, the last regular generation is followed by a generation, in which all incumbent genomes get evaluated on all provided training instances within a single mini tournament. The number of additional evaluations is kept low by caching previous results and applying racing, if enabled.
  • Feature: Rename addDefaultGenome parameter to addDefaultGenomeToFirstGeneration and introduce addDefaultGenomeToFinalIncumbentGeneration parameter to differentiate the potential insertion of a default genome into the corresponding generation.
  • Feature: Introduce RacingRunEvaluatorBase to support the implementation of custom racing strategies.
  • Feature: Introduce --tertiaryTuneCriterion parameter in exemplary Gurobi adapter to flexibly control the adapter's tuning metric. Valid criterions are MipGap, BestObjective, BestObjectiveBound and None, disabling the tertiary tune criterion.
  • Documentation: Add prepared Excel file to documentation to estimate a rough upper bound for the overall tuning runtime.
  • Improvement: Extend logging information by date in addition to time.

NuGet packages

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Version Downloads Last updated 95 11/12/2021 112 5/4/2021 137 3/25/2021 258 10/16/2020 269 5/29/2020