Treffer: Multiobjective genetic search for spanning tree problem
Title:
Multiobjective genetic search for spanning tree problem
Authors:
Source:
Neural information processing (Calcutta, 22-25 November 2004)Lecture notes in computer science. :218-223
Publisher Information:
Berlin: Springer, 2004.
Publication Year:
2004
Physical Description:
print, 13 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Recherche operationnelle. Gestion, Operational research. Management science, Recherche opérationnelle et modèles formalisés de gestion, Operational research and scientific management, Flots dans les réseaux. Problèmes combinatoires, Flows in networks. Combinatorial problems, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Intelligence artificielle, Artificial intelligence, Connexionnisme. Réseaux neuronaux, Connectionism. Neural networks, Algorithme génétique, Genetic algorithm, Algoritmo genético, Algorithme évolutionniste, Evolutionary algorithm, Algoritmo evoluciónista, Arbre maximal, Spanning tree, Arbol máximo, Arbre recherche, Search tree, Arbol investigación, Problème recherche, Search problem, Problema investigación, Programmation mathématique, Mathematical programming, Programación matemática, Programmation multiobjectif, Multiobjective programming, Programación multiobjetivo, Algorithme évolutionniste convergent Pareto
Document Type:
Konferenz
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, WB 721 302, India
ISSN:
0302-9743
Rights:
Copyright 2005 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
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:
Computer science; theoretical automation; systems
Operational research. Management
Operational research. Management
Accession Number:
edscal.16442641
Database:
PASCAL Archive
Weitere Informationen
A major challenge to solving multiobjective optimization problems is to capture possibly all the (representative) equivalent and diverse solutions at convergence. In this paper, we attempt to solve the generic multi-objective spanning tree (MOST) problem using an evolutionary algorithm (EA). We consider, without loss of generality, edge-cost and tree-diameter as the two objectives, and use a multiobjective evolutionary algorithm (MOEA) that produces diverse solutions without needing a priori knowledge of the solution space. We test this approach for generating (near-) optimal spanning trees, and compare the solutions obtained from other conventional approaches.