Result: Memetic search for the quadratic assignment problem

Title:
Memetic search for the quadratic assignment problem
Authors:
BENLIC, Una, HAO, Jin-Kao
Source:
Expert systems with applications. 42(1):584-595
Publisher Information:
Amsterdam: Elsevier, 2015.
Publication Year:
2015
Physical Description:
print, 3/4 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, Programmation mathématique, Mathematical programming, Gestion des stocks, gestion de la production. Distribution, Inventory control, production control. Distribution, Logistique, Logistics, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Informatique théorique, Theoretical computing, Algorithmique. Calculabilité. Arithmétique ordinateur, Algorithmics. Computability. Computer arithmetics, Affectation quadratique, Quadratic assignment, Afectación cuadrática, Algorithme génétique, Genetic algorithm, Algoritmo genético, Algorithme recherche, Search algorithm, Algoritmo búsqueda, Algorithme évolutionniste, Evolutionary algorithm, Algoritmo evoluciónista, Evaluation performance, Performance evaluation, Evaluación prestación, Intelligence en essaim, Swarm intelligence, Inteligencia de enjambre, Mise à jour, Updating, Actualización, Mutation, Mutación, Méthode adaptative, Adaptive method, Método adaptativo, Optimisation combinatoire, Combinatorial optimization, Optimización combinatoria, Optimum local, Local optimum, Optimo local, Paysage, Landscape, Paisaje, Problème NP difficile, NP hard problem, Problema NP duro, Problème affectation, Assignment problem, Problema asignación, Problème localisation, Location problem, Problema localización, Problème recherche, Search problem, Problema investigación, Programmation quadratique, Quadratic programming, Programación cuadrática, Recherche locale, Local search, Busca local, Algorithme mémétique, Memetic algorithm, Algoritmo memético, Landscape analysis
Document Type:
Academic journal Article
File Description:
text
Language:
English
Author Affiliations:
CHORDS, University of Stirling, Stirling FK9 4LA, United Kingdom
LERIA, Université d'Angers, 2 bd Lavoisier, 49045 Angers, France
ISSN:
0957-4174
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=28843426
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.28843426
Database:
PASCAL Archive

Further Information

The quadratic assignment problem (QAP) is one of the most studied NP-hard problems with various practical applications. In this work, we propose a powerful population-based memetic algorithm (called BMA) for QAP. BMA integrates an effective local optimization algorithm called Breakout Local Search (BLS) within the evolutionary computing framework which itself is based on a uniform crossover, a fitness-based pool updating strategy and an adaptive mutation procedure. Extensive computational studies on the set of 135 well-known benchmark instances from the QAPLIB revealed that the proposed algorithm is able to attain the best-known results for 133 instances and thus competes very favorably with the current most effective QAP approaches. A study of the search landscape and crossover operators is also proposed to shed light on the behavior of the algorithm.