Result: A simulation based multi-criteria scheduling approach of dual-resource constrained manufacturing systems with neural networks

Title:
A simulation based multi-criteria scheduling approach of dual-resource constrained manufacturing systems with neural networks
Authors:
ARAZ, Ozlem Uzun
Source:
AI 2005 (advances in artificial intelligence)Lecture notes in computer science. :1047-1052
Publisher Information:
Berlin: Springer, 2005.
Publication Year:
2005
Physical Description:
print, 10 ref 1
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Intelligence artificielle, Artificial intelligence, Aide décision, Decision aid, Ayuda decisión, Algorithme rétropropagation, Backpropagation algorithm, Algoritmo retropropagación, Analyse multicritère, Multicriteria analysis, Análisis multicriterio, Evaluation performance, Performance evaluation, Evaluación prestación, Gestion ressources, Resource management, Gestión recursos, Intelligence artificielle, Artificial intelligence, Inteligencia artificial, Ordonnancement, Scheduling, Reglamento, Problème livraison, Dispatching problem, Problema reparto, Règle décision, Decision rule, Regla decisión, Réseau neuronal, Neural network, Red neuronal, Système production, Production system, Sistema producción
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Dokuz Eylul University, Department of Industrial Engineering, 35100, Izmir, Turkey
ISSN:
0302-9743
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=17345143
Rights:
Copyright 2006 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
Accession Number:
edscal.17345143
Database:
PASCAL Archive

Further Information

This paper presents a multicriteria DRC scheduler in order to select appropriate dispatching rules. This scheduler integrates several tools, namely; a simulation model, a backpropagation neural network (BPNN) and a Multicriteria decision aid (MCDA) method. Simulation is used to collect predefined performance measures corresponding to decision rule set and system state variables. Because of the time consuming nature of simulation, BPNN is used to obtain the performance measures for each alternative schedule. In order to compare the system performance between all alternatives, the evaluation of each alternative is performed by PROMETHEE, which is a well-known MCDA method. By means of a realistic numerical example, the proposed methodology is proved to be an effective method in a DRC manufacturing system.