MaOEA-package: Many-Objective Evolutionary Algorithm

In MaOEA: Many Objective Evolutionary Algorithm

Description

MaOEA contains several algorithms for solving many-objective optimization problems. The algorithms are provided as a sequence of operators used in a single iteration. For example, the SMSEMOA function calls the recombination (SBX) and mutation operator (polynomial mutation) to produce 1 offspring, and perform the S-metric selection. The function then returns a list containing the population and population objective after the procedure is conducted once. The purpose of only doing a single iteration is to support users if they wish to formulate hybrid algorithms.

Details

Alternatively, users can use the optimMaOEA function to solve an optimization problem with their chosen algorithm. This function is a simple wrapper to call the algorithms listed above for several iterations. Using this function, users can simply supply the initial population, objective function, the chosen algorithm, and the number of iterations. If number of iteration is not supplied, then only a single iteration is conducted.

Note: This package uses column-major ordering, i.e. an individual should be contained in a single column, each row represents different variable. All optimization variable should be scaled to 0-1.

Package:	MaOEA
Type:	Package
Version:	0.4.1
Date:	2019-07-12
License:	GPL (>= 2)
LazyLoad:	yes

Acknowledgments

This work is funded by the European Commission's H2020 programme through the UTOPIAE Marie Curie Innovative Training Network, H2020-MSCA-ITN-2016, under Grant Agreement No. 722734 as well as through the Twinning project SYNERGY under Grant Agreement No. 692286.

Maintainer

Dani Irawan [e-mail]

Author(s)

Dani Irawan [e-mail]

See Also

Main interface function is optimMaOEA.

MaOEA documentation built on Aug. 31, 2020, 5:07 p.m.