Treffer: Metaheuristic based solution approaches for the obstacle neutralization problem

Title:
Metaheuristic based solution approaches for the obstacle neutralization problem
Authors:
ALI FUAT ALKAYA, ALGIN, Ramazan
Source:
Expert systems with applications. 42(3):1094-1105
Publisher Information:
Amsterdam: Elsevier, 2015.
Publication Year:
2015
Physical Description:
print, 1/4 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, Flots dans les réseaux. Problèmes combinatoires, Flows in networks. Combinatorial problems, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Informatique théorique, Theoretical computing, Algorithmique. Calculabilité. Arithmétique ordinateur, Algorithmics. Computability. Computer arithmetics, Automatique théorique. Systèmes, Control theory. Systems, Robotique, Robotics, Algorithme génétique, Genetic algorithm, Algoritmo genético, Algorithme optimal, Optimal algorithm, Algoritmo óptimo, Analyse donnée, Data analysis, Análisis datos, Insecte social, Social insect, Insecto social, Intelligence en essaim, Swarm intelligence, Inteligencia de enjambre, Localisation, Localization, Localización, Migration, Migración, Modélisation, Modeling, Modelización, Métamodèle, Metamodel, Metamodelo, Méthode heuristique, Heuristic method, Método heurístico, Plus court chemin, Shortest path, Camino más corto, Problème NP complet, NP complete problem, Problema NP completo, Recuit simulé, Simulated annealing, Recocido simulado, Robot mobile, Moving robot, Robot móvil, Routage, Routing, Enrutamiento, Solution exacte, Exact solution, Solución exacta, Temps exécution, Execution time, Tiempo ejecución, Trajectoire optimale, Optimal trajectory, Trayectoria óptima, Optimisation par colonies de fourmis, Ant colony optimization, Algoritmo de las hormigas, Planification trajectoire, Path planning, Planificación de Trayectoria, Metaheuristics, Obstacle neutralization problem, Optimization
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Computer Engineering Department, Marmara University, Istanbul 34722, Turkey
ISSN:
0957-4174
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=28928440
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.28928440
Database:
PASCAL Archive

Weitere Informationen

The problem of finding shortest path under certain constraints is NP-Complete except for some trivial variants. In this study, we develop metaheuristics for the obstacle neutralization problem (ONP) which is a path planning problem where the goal is to safely and swiftly navigate an agent from a given source location to a destination through an arrangement of potential mine or threat discs in the plane. To solve the ONP, ant system, genetic algorithm, simulated annealing and migrating birds optimization algorithms are developed and customized. We provide computational experiments both on real-world and synthetic data to empirically assess their performance. The results of the algorithms are compared with exact solutions on small instances. The comparison results present that our algorithms finds near-optimal solutions in reasonable execution times. Furthermore, the results show that the proposed versions of the aforementioned algorithms can be applicable to similar problems.