RunGPareto: Sequential multi-objective Expected Improvement Optimization

In gerwathome/runOPM: Runs and Examines Reservoir Simulation Models with OPM

Description

This is a wrapper for GPareto::GParetoptim. It assumes input of a list of kriged models of error for the chosen well/group name and keyword combination. The GPareto vignette is very useful for understanding how to use this function: GPareto: An R Package for Gaussian-Process Based Multi-Objective Optimization and Analysis

Usage

RunGPareto(kmodels = NULL, method = "genoud", basedir = "tmp",
  nsteps = 10, ...)

Arguments

kmodels	A list of kriged models of class km. There should one model for each of the objectives that are to be included in the multi-objective optimization.
method	The chosen optimization method. Currently only genoud is supported. Note that by default genoud seeks a maximum. For a kriged model of error, Max = FALSE is necessary, which is assumed in this wrapper.
basedir	The path to the base directory of a simulation project. The default is a subdirectory of the current directory called "tmp". This is necessary for saving the results.
nsteps	an integer representing the desired number of iterations.
...	Additional arguments which may be passed to GParetoptim

Details

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Value

A list with components: par: a data frame representing the additional points visited during the algorithm, values: a data frame representing the response values at the points given in par, nsteps: an integer representing the desired number of iterations (given in argument), lastmodel: a list of objects of class km corresponding to the last kriging models fitted. If a problem occurs during either model updates or criterion maximization, the last working model and corresponding values are returned.

gerwathome/runOPM documentation built on May 20, 2019, 4:05 p.m.