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.github/workflows/ant.yml

Funz algorithm: EGO

  • Efficient Global Optimization (EGO)
  • tags: optimization; sparse
  • author: yann.richet@irsn.fr; DiceKriging authors
  • require: DiceDesign; DiceKriging; DiceView; pso; jsonlite
  • options: search_ymin='true'; initBatchSize='4'; batchSize='4'; iterations='10'; initBatchBounds='true'; trend='y~1'; covtype='matern3_2'; knots='0'; liar='upper95'; seed='1'
  • options.help: search_ymin=minimization or maximisation; initBatchSize=Initial batch size; batchSize=iterations batch size; iterations=number of iterations; initBatchBounds=add input variables bounding values (2^d combinations); trend=(Universal) kriging trend; covtype=Kriging covariance kernel; knots=number of non-stationary points for each Xi; liar=liar value for in-batch loop (when batchsize>1); seed=random seed
  • input: x=list(min=0,max=1)
  • output: y=0.99

Funz algorithm: ECEGO

  • Efficient Global Optimization (EGO) algorithm with equality constraints.
  • tags: optimization; sparse; contraints
  • author: yann.richet@irsn.fr; DiceKriging authors
  • require: DiceDesign; DiceKriging; DiceView; pso; jsonlite
  • options: search_ymin='true'; initBatchSize='4'; batchSize='4'; iterations='10'; initBatchBounds='true'; trend='y1'; covtype='matern3_2'; knots='0'; liar='upper95'; trend_constr='y1'; covtype_constr='matern3_2'; liar_constr='upper95'; seed='1'
  • options.help: search_ymin=minimization or maximisation; initBatchSize=Initial batch size; batchSize=iterations batch size; iterations=number of iterations; initBatchBounds=add input variables bounding values (2^d combinations); trend=(Universal) kriging trend; covtype=Kriging covariance kernel; knots=number of non-stationary points for each Xi; liar=liar value for in-batch loop (when batchsize>1); seed=random seed
  • input: x=list(min=0,max=1)
  • output: y=0.99

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