Result: Floorplan design using improved genetic Algorithm

Title:
Floorplan design using improved genetic Algorithm
Authors:
IDA, Kenichi, KIMURA, Yosuke
Source:
Foundations of intelligent systems (Maebashi City, 28-31 October 2003)Lecture notes in computer science. :531-538
Publisher Information:
Berlin: Springer, 2003.
Publication Year:
2003
Physical Description:
print, 10 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, Apprentissage et systèmes adaptatifs, Learning and adaptive systems, Algorithme génétique, Genetic algorithm, Algoritmo genético, Information incomplète, Incomplete information, Información incompleta, Méthode combinatoire, Combinatorial method, Método combinatorio, Méthode optimisation, Optimization method, Método optimización, Optimisation combinatoire, Combinatorial optimization, Optimización combinatoria, Plan masse, Layout plan, Plano masa, Problème remplissage, Bin packing problem, Problema relleno, Solution optimale, Optimal solution, Solución óptima, Temps réel, Real time, Tiempo real, Tranchage, Slicing, Chapeado, Vitesse convergence, Convergence speed, Velocidad convergencia
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Department of Systems and Information Engineering, Maebashi Institute of Technology, Maebashi, 371-0816, Japan
ISSN:
0302-9743
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=15509276
Rights:
Copyright 2004 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
Accession Number:
edscal.15509276
Database:
PASCAL Archive

Further Information

Genetic Algorithm (GA) which is a part of soft computing is attracting attention as an approximation method to combinatorial optimization problems. The floorplan design problem (FDP) belongs to the category of these kinds of problems; it is difficult to find a true optimal solution in real time. A floorplan design problem is classified into the slicing structure and the non-slicing structure, from the arrangement structure. Recently, we proposed the new immune algorithm for the floorplan design with slicing structure, which was an application of GA. In this paper, we propose an improved genetic algorithm (pIGA) combining the advantage of our proposed immune algorithm to the floorplan design with non-slicing structure. pIGA is improved aiming at the further improvement in the convergence speed and the accuracy of a solution. Moreover, we apply pIGA to the MCNC benchmark problem. The experimental results show that the proposed pIGA has better performance than the existing methods.