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Result: Designing an efficient method for tandem AGV network design problem using tabu search

Title:
Designing an efficient method for tandem AGV network design problem using tabu search
Authors:
LAPORTE, Gilbert, REZA ZANJIRANI FARAHANI, MIANDOABCHI, Elnaz
Source:
Applied mathematics and computation. 183(2):1410-1421
Publisher Information:
New York, NY: Elsevier, 2006.
Publication Year:
2006
Physical Description:
print, 43 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, Combinatoire. Structures ordonnées, Combinatorics. Ordered structures, Combinatoire, Combinatorics, Plans d'expériences et configurations, Designs and configurations, Probabilités et statistiques, Probability and statistics, Statistiques, Statistics, Analyse multivariable, Multivariate analysis, 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, Sciences appliquees, Applied sciences, Recherche operationnelle. Gestion, Operational research. Management science, Recherche opérationnelle et modèles formalisés de gestion, Operational research and scientific management, Optimisation. Problèmes de recherche, Optimization. Search problems, Algorithme recherche, Search algorithm, Algoritmo búsqueda, Analyse donnée, Data analysis, Análisis datos, Analyse numérique, Numerical analysis, Análisis numérico, Charge travail, Workload, Carga trabajo, Mathématiques appliquées, Applied mathematics, Matemáticas aplicadas, Méthode partition, Partition method, Método partición, Problème recherche, Search problem, Problema investigación, Recherche tabou, Tabu search, Búsqueda tabú, AGV, Algorithme partitionnement, Conception algorithme, Configuration tandem, Tandem configuration, Non chevauchement, Plan recherche, Search design
Document Type:
Academic journal Article
File Description:
text
Language:
English
Author Affiliations:
Canada Research Chair in Distribution Management and GERAD, HEC Montréal, 3000 chemin de la Côte -Sainte -Catherine, Montreal, H3T 2A7, Canada
Department of Industrial Engineering, Amir Kabir University of Technology, Tehran, Iran, Islamic Republic of
Supply Chain Management Research Group, Tehran, Iran, Islamic Republic of
ISSN:
0096-3003
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=18442291
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

Operational research. Management
Accession Number:
edscal.18442291
Database:
PASCAL Archive

Further Information

A tandem AGV configuration connects all cells of a manufacturing area by means of non-overlapping, single-vehicle closed loops. Each loop has at least one additional P/D station, provided as interface between adjacent loops. This study describes the development of a tabu search algorithm for the design of tandem AGV systems. Starting from an initial partition generated by a k-means clustering method, the tabu search algorithm partitions the stations into loops by minimizing the maximum workload of the system, without allowing the paths of loops to cross each other. The new algorithm and the partitioning algorithm presented by Bozer and Srinivasan are compared on, randomly generated problems. Results show that in large scale problems, the partitioning algorithm often leads to infeasible configurations with crossed loops in spite of its shorter running time. However the newly developed algorithm avoids infeasible configurations and often yields better objective function values.