Specifications

539 Metals Corrosion and Protection; Metal Plating - 547.2 Rare Earth Metals
DOI: 10.1063/1.4795265
Database: Compendex
Compilation and indexing terms, © 2013 Elsevier Inc.
6.
Accession number: 20131216137586
Title: Cloud droplets evolutionary algorithm on reciprocity mechanism for function optimization
Authors: Wang, Lei1 ; Li, Wei1 ; Fei, Rong1 ; Hei, Xinghong1/王磊;李伟;费蓉;黑新红
Author affiliation: 1 Faculty of Computer Science and Engineering, Xi'an University of
Technology, China
Corresponding author: Wang, L. ([e-mail])
Source title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial
Intelligence and Lecture Notes in Bioinformatics)
Abbreviated source title: Lect. Notes Comput. Sci.
Volume: 7331 LNCS
Issue: PART 1
Monograph title: Advances in Swarm Intelligence - Third International Conference, ICSI 2012,
Proceedings
Issue date: 2012
Publication year: 2012
Pages: 268-275
Language: English
ISSN: 03029743
E-ISSN: 16113349
ISBN-13: 9783642309755
Document type: Conference article (CA)
Conference name: 3rd International Conference on Swarm Intelligence, ICSI 2012
Conference date: June 17, 2012 - June 20, 2012
Conference location: Shenzhen, China
Conference code: 96080
Sponsor: Shenzhen University; Peking University; Xi'an Jiaotong-Liverpool University
Publisher: Springer Verlag, Tiergartenstrasse 17, Heidelberg, D-69121, Germany
Abstract: For the problems of solving difficult problems in evolutionary algorithms such as
easily falling into local optimum, premature convergence because of selective pressure, a
complex and larger calculation and a lower accuracy of the solution, this paper proposes cloud
droplets evolutionary model on reciprocity mechanism (CDER). The main idea of CDER is to
simulate the phase transition of the cloud in nature which has vapor state, liquid state and solid
state, and to combine the basic ideas of evolutionary computation to realize the population
evolution. The condensation growth and collision growth of cloud droplets correspond to the
competitive evolution and reciprocal evolution of species in nature. Experiments on solving the
function optimization problems show that this model can enhance the individual competition
and survival ability, guarantee the population diversity, accelerate the convergence speed and
improve the solution precision through the iterative process of competition mechanism and
reciprocity mechanism. © 2012 Springer-Verlag.