calc_norm_pref_distance: Calculate Normalized Preference Distance Computes the...
In benitezfj/rmoo: Multi-Objective Optimization in R
View source: R/modified_crowding_distance.R
calc_norm_pref_distance R Documentation
Calculate Normalized Preference Distance
Computes the weighted normalized Euclidean distance between a set of fitness
vectors and a set of reference points.
Description
Calculate Normalized Preference Distance
Computes the weighted normalized Euclidean distance between a set of fitness
vectors and a set of reference points.
Usage
calc_norm_pref_distance(fitness, ref_points, weight, ideal_point, nadir_point)
Arguments
fitness
A matrix of fitness values.
ref_points
A matrix of reference points.
weight
A numeric vector of weights for each objective.
ideal_point
A numeric vector of ideal point values.
nadir_point
A numeric vector of nadir point values.
Value
A matrix of distances where element (i, j) is the distance from
fitness to ref_points.
benitezfj/rmoo documentation built on July 16, 2025, 11:07 p.m.
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View source: R/modified_crowding_distance.R
| calc_norm_pref_distance | R Documentation |
Calculate Normalized Preference Distance Computes the weighted normalized Euclidean distance between a set of fitness vectors and a set of reference points.
Description
Calculate Normalized Preference Distance Computes the weighted normalized Euclidean distance between a set of fitness vectors and a set of reference points.
Usage
calc_norm_pref_distance(fitness, ref_points, weight, ideal_point, nadir_point)
Arguments
fitness |
A matrix of fitness values. |
ref_points |
A matrix of reference points. |
weight |
A numeric vector of weights for each objective. |
ideal_point |
A numeric vector of ideal point values. |
nadir_point |
A numeric vector of nadir point values. |
Value
A matrix of distances where element (i, j) is the distance from fitness to ref_points.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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