Package: emoa 0.5-3

emoa: Evolutionary Multiobjective Optimization Algorithms

Collection of building blocks for the design and analysis of evolutionary multiobjective optimization algorithms.

Authors:Olaf Mersmann [aut, cre]

# Install 'emoa' in R:

install.packages('emoa', repos = c('https://olafmersmann.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

On CRAN:

Last updated 3 months agofrom:76922804bd. Checks:OK: 9. Indexed: yes.

Dependencies:

Help page	Topics
The EMOA package	emoa-package
CEC 2007 multiobjective optimization competition results	cec2007
Return first non null argument.	coalesce
Crowding Distance	crowding_distance
Calculate the dominance matrix of a set of points	dominance_matrix
Dominated Hypervolume calculation	dominated_hypervolume hypervolume_contribution
console logger	emoa_console_logger
Basic EMOA control parameters.	emoa_control
generic logger factory	emoa_logger
null logger	emoa_null_logger
Binary quality indicators	epsilon_indicator hypervolume_indicator r1_indicator r2_indicator r3_indicator
Clip value to a given range	inbounds
Pareto dominance checks.	is_dominated is_maximally_dominated
Selection strategies	nds_cd_selection nds_hv_selection
Nondominated sorting ranks	nds_rank nondominated_ordering
Nondominated points	nondominated_points
Scale point cloud	normalize_points
Polynomial muation (PM) control parameters	pm_control
Polynomial mutation operator	pm_operator
Simulated binary crossover (SBX) control parameters	sbx_control
Simulated binary crossover operator	sbx_operator
Steady state EMOA parameters	steady_state_emoa_control
Functions from the CEC 2007 EMOA competition.	sympart
Functions from the CEC 2009 EMOA competition.	UF1 UF10 UF2 UF3 UF4 UF5 UF6 UF7 UF8 UF9
Unary R2 indicator	unary_r2_indicator
Determine which points are on the edge of a Pareto-front approximation.	which_points_on_edge