Algorithms

The general overview of algorithms is presented in this section, although for more usage details we suggest referring to usage page.

DE

Differential Evolution for single-objective problems proposed by Storn & Price [3]. Other features later implemented are also present, such as dither, jitter, selection variants, and crossover strategies. For details see Price et al. [4].

GDE3

Generalized Differential Evolution 3, a multi-objective algorithm that combines DE mutation and crossover operators to NSGA-II [5] survival with a hybrid type survival strategy. In this algorithm, individuals might be removed in a one-to-one comparison before truncating the population by the multi-objective survival operator. It was proposed by Kukkonen, S. & Lampinen, J. [6]. Variants with M-Nearest Neighbors and 2-Nearest Neighbors survival [7] are also available.

NSDE

Non-dominated Sorting Differential Evolution, a multi-objective algorithm that combines DE mutation and crossover operators to NSGA-II [5] survival.

NSDE-R

Non-dominated Sorting Differential Evolution based on Reference directions [8]. It is an algorithm for many-objective problems that works as an extension of NSDE using NSGA-III [9] [10] survival strategy.