Treffer: Solving the multi-objective flowline manufacturing cell scheduling problem by hybrid harmony search

Title:
Solving the multi-objective flowline manufacturing cell scheduling problem by hybrid harmony search
Authors:
YAZHI LI, XIAOPING LI, GUPTA, Jatinder N. D
Source:
Expert systems with applications. 42(3):1409-1417
Publisher Information:
Amsterdam: Elsevier, 2015.
Publication Year:
2015
Physical Description:
print, 1/2 p
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, Théorie de la décision. Théorie de l'utilité, Decision theory. Utility theory, Ordonnancement, Scheduling, sequencing, Gestion des stocks, gestion de la production. Distribution, Inventory control, production control. Distribution, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Informatique théorique, Theoretical computing, Algorithmique. Calculabilité. Arithmétique ordinateur, Algorithmics. Computability. Computer arithmetics, Algorithme génétique, Genetic algorithm, Algoritmo genético, Algorithme recherche, Search algorithm, Algoritmo búsqueda, Algorithme évolutionniste, Evolutionary algorithm, Algoritmo evoluciónista, Composition, Composicion, Diversification, Diversificación, Ensemble dominant, Dominating set, Conjunto dominando, Fabrication cellulaire, Cellular manufacturing, Fabricacíon celular, Minimisation, Minimization, Minimización, Modèle hybride, Hybrid model, Modelo híbrido, Modélisation, Modeling, Modelización, Métamodèle, Metamodel, Metamodelo, Méthode heuristique, Heuristic method, Método heurístico, Méthode itérative, Iterative method, Método iterativo, Optimum Pareto, Pareto optimum, Optimo Pareto, Ordonnancement, Scheduling, Reglamento, Problème recherche, Search problem, Problema investigación, Programmation multiobjectif, Multiobjective programming, Programación multiobjetivo, Recherche locale, Local search, Busca local, Retard, Delay, Retraso, Résultat expérimental, Experimental result, Resultado experimental, Temps mise en route, Setup time, Tiempo iniciacion, Recherche de l'harmonie, Harmony search, Búsqueda armónica, Cellular manufacturing system, Flowline scheduling, Meta-heuristic, Pareto front
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
School of Computer Science & Engineering, Southeast University, Nanjing 211189, China
Key Laboratory of Computer Network and Information Integration, Southeast University, Nanjing 211189, China
College of Business Administration, University of Alabama in Huntsville, Huntsville, AL 35899, United States
ISSN:
0957-4174
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=28928463
Rights:
Copyright 2015 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.28928463
Database:
PASCAL Archive

Weitere Informationen

This paper considers the flowline manufacturing cell scheduling problem (FUNKSA) with sequence-dependent family setup times (SDFSTs) for total tardiness and mean total flowtime minimization. Based on the mathematical model of this problem, a hybrid harmony search (HHS) is proposed. One-point crossover operator that is commonly used in genetic algorithms is adapted and applied for diversification. Iterative local search method is used to further improve the solution. The effectiveness of HHS in finding optimal or near-optimal schedules is compared with the meta-heuristics, NSGA-II. MA and MSA, which are adapted and renamed as NSGA - IIapt, MAapt and MSAapt respectively. Experimental results from 900 problem instances show that HHS performs relatively better than these meta-heuristics for finding schedules to minimize the multi-objective FMCSP with SDFSTs. The proposed HHS algorithm also generates the maximal Pareto front among all these heuristics.