TY - JOUR
T1 - Two Improved Differential Evolution Schemes for Faster Global Search
AU - Das, Swagatam
AU - Konar, Amit
AU - Chakraborty, Uday Kumar
PY - 2005/6/25
Y1 - 2005/6/25
N2 - Differential evolution (DE) is well known as a simple and efficient scheme for global optimization over continuous spaces. In this paper we present two new, improved variants of DE. Performance comparisons of the two proposed methods are provided against (a) the original DE, (b) the canonical particle swarm optimization (PSO), and (c) two PSO-variants. The new DE-variants are shown to be statistically significantly better on a seven-function test bed for the following performance measures: solution quality, time to find the solution, frequency of finding the solution, and scalability.
AB - Differential evolution (DE) is well known as a simple and efficient scheme for global optimization over continuous spaces. In this paper we present two new, improved variants of DE. Performance comparisons of the two proposed methods are provided against (a) the original DE, (b) the canonical particle swarm optimization (PSO), and (c) two PSO-variants. The new DE-variants are shown to be statistically significantly better on a seven-function test bed for the following performance measures: solution quality, time to find the solution, frequency of finding the solution, and scalability.
UR - https://static.aminer.org/pdf/PDF/000/225/765/two_improved_differential_evolution_schemes_for_faster_global_search.pdf
U2 - 10.1145/1068009.1068177
DO - 10.1145/1068009.1068177
M3 - Article
JO - Genetic and Evolutionary Computation Conference
JF - Genetic and Evolutionary Computation Conference
ER -