benchmark_algorithm {IOHexperimenter}

Base procedure for benchmarking a custom algorithm

Description

Base procedure for benchmarking a custom algorithm

Usage

benchmark_algorithm(user_alg, suite = "PBO", functions = c(1, 2),
  instances = c(1, 2), dimensions = 16, data.dir = NULL,
  algorithm.info = " ", algorithm.name = " ", params.track = NULL,
  repetitions = 5)

Arguments

user_alg

Function defining the custom algorithm. Needs to accept one paramter: an IOHproblem object, which has the following properties:

• dimension

• function_id

• instance

• suite (Currently 'BBOB' or 'PBO')

And the following functions:

• obj_func

• target_hit

• set_parameters

suite

Which suite to test on

functions

Which function to test on

instances

Which instances to test on

dimensions

Which dimensions to test on

data.dir

Where the data should be stored (defaults to "./data" when not provided)

algorithm.info

Additional information about the algorithm you plan on running

algorithm.name

The name of the algorithm you plan on running

params.track

Which parameters to track. Should be a vector of strings, containing no spaces or commas

repetitions

How many independent runs of the algorithm to do for each problem instance

Examples

benchmark_algorithm(IOH_two_rate_GA, params.track = 'Mutation_rate', data.dir = './data')