List Of Algorithms¶
Algorithm 
Class 
Convenience 
Objective(s) 
Constraints 
Description 

GA 
ga 
single 
x 
A modular implementation of a genetic algorithm. It can be easily customized with different evolutionary operators and applies to a broad category of problems. 

DE 
de 
single 
x 
Different variants of differential evolution which is a wellknown concept for in continuous optimization especially for global optimization. 

BRKGA 
brkga 
single 
x 
Mostly used for combinatorial optimization where instead of custom evolutionary operators the complexity is put into an advanced variable encoding. 

NelderMead 
neldermead 
single 
x 
A pointbypoint based algorithm which keeps track of a simplex with is either extended reflected or shrunk. 

PatternSearch 
patternsearch 
single 
x 
Iterative approach where the search direction is estimated by forming a specific exploration pattern around the current best solution. 

CMAES 
cmaes 
single 
Wellknown modelbased algorithm sampling from a dynamically updated normal distribution in each iteration. 

ES 
es 
single 
The evolutionary strategy algorithm proposed for realvalued optimization problems. 

SRES 
sres 
single 
x 
An evolutionary strategy with constrained handling using stochastic ranking. 

ISRES 
isres 
single 
x 
An improved version of SRES being able to deal dependent variables efficiently. 

NSGA2 
nsga2 
multi 
x 
Wellknown multiobjective optimization algorithm based on nondominated sorting and crowding. 

RNSGA2 
rnsga2 
multi 
x 
An extension of NSGAII where reference/aspiration points can be provided by the user. 

NSGA3 
nsga3 
many 
x 
An improvement of NSGAII developed for multiobjective optimization problems with more than two objectives. 

UNSGA3 
unsga3 
many 
x 
A generalization of NSGAIII to be more efficient for single and biobjective optimization problems. 

RNSGA3 
rnsga3 
many 
x 
Allows defining aspiration points for NSGAIII to incorporate the user’s preference. 

MOEAD 
moead 
many 
Another wellknown multiobjective optimization algorithm based on decomposition. 

AGEMOEA 
agemoea 
many 
Similar to NSGAII but estimates the shape of the Paretofront to compute a score replacing the crowding distance. 

CTAEA 
ctaea 
many 
x 
An algorithm with a more sophisticated constrainthandling for manyobjective optimization algoritms. 