Result: An extended mind evolutionary computation model for optimizations

Title:
An extended mind evolutionary computation model for optimizations
Authors:
JING JIE, JIANCHAO ZENG, CHONGZHAO HAN
Source:
Special issue on intelligent computing theory and methodologyApplied mathematics and computation. 185(2):1038-1049
Publisher Information:
New York, NY: Elsevier, 2007.
Publication Year:
2007
Physical Description:
print, 18 ref
Original Material:
INIST-CNRS
Subject Terms:
Control theory, operational research, Automatique, recherche opérationnelle, Computer science, Informatique, Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Analyse mathématique, Mathematical analysis, Calcul des variations et contrôle optimal, Calculus of variations and optimal control, Analyse numérique. Calcul scientifique, Numerical analysis. Scientific computation, Analyse numérique, Numerical analysis, Méthodes numériques en programmation mathématique, optimisation et calcul variationnel, Numerical methods in mathematical programming, optimization and calculus of variations, Algorithme, Algorithm, Algoritmo, Analyse mécanisme, Mechanism analysis, Análisis mecánismo, Analyse numérique, Numerical analysis, Análisis numérico, Benchmark, Benchmarks, Comportement, Behavior, Conducta, Convergence, Convergencia, Coopération, Cooperation, Cooperación, Espace, Space, Espacio, Mathématiques appliquées, Applied mathematics, Matemáticas aplicadas, Méthode optimisation, Optimization method, Método optimización, Performance, Rendimiento, Programmation mathématique, Mathematical programming, Programación matemática, Recuit simulé, Simulated annealing, Recocido simulado, Résultat expérimental, Experimental result, Resultado experimental, Superficie, Area, 49XX, 65Kxx, Modèle calcul, Optimisation globale, Dissimilation, Global optimization, Mind evolutionary computation, Similar-taxis
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
School of Electronic and Information Engineering, Xi'an Jiaotong University, 710049 Xi'an City, China
Division of System Simulation and Computer Application, Taiyuan University of Science and Technology, 030024 Taiyuan City, China
ISSN:
0096-3003
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=18637810
Rights:
Copyright 2007 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Mathematics
Accession Number:
edscal.18637810
Database:
PASCAL Archive

Further Information

The paper makes an analysis on the simulated mechanisms of mind evolutionary computation (MEC) firstly and proposes an extended computation model for MEC (EMEC). EMEC manipulates the search based on the behavior space and the information space. All operations in the behavior space are processed based on groups that symbolize the solution area, while the operations in the information space are done based on the billboards that are used to record the evolutionary information. All components of EMEC are formulated in details, including the similar-taxis operation, the cooperation operation, and a simulated-annealing-based dissimilation operation (SADO). EMEC emphasizes on the share and the guide of the information in the search, and gets a performance superior to the simple MEC. The proposed EMEC was performed on some well-known benchmark problems. The experimental results show EMEC is a robust global optimization algorithm and can alleviate the premature convergence validly.