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Başlık: A new hybrid electromagnetism-like algorithm for capacitated vehicle routing problems
Yazarlar: Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü.
0000-0003-2978-2811
0000-0002-9220-7353
Yurtkuran, Alkın
Emel, Erdal
AAH-1410-2021
N-8691-2014
26031880400
6602919521
Anahtar kelimeler: Capacitated vehicle routing problem
Genetic algorithm
Optimizaton
Computer science
Engineering
Operations research & management science
Combinatorial optimization
Distributed parameter networks
Electromagnetism
Heuristic methods
Vehicles
Benchmarking problems
Combinatorial optimization problems
Computational results
Computational time
Distribution network
Electromagnetism-like algorithm
Local search method
Meta heuristics
Objective function values
Population-based algorithm
Vehicle routing problems
Routing algorithms
Yayın Tarihi: Nis-2010
Yayıncı: Pergamon-Elsevier Science
Atıf: Yurtkuran, A. ve Emel, E. (2010). "A new hybrid electromagnetism-like algorithm for capacitated vehicle routing problems". Expert Systems with Applications, 37(4), 3427-3433.
Özet: Vehicle routing problems have been extensively analyzed within the last few decades, since they play a central role in optimization of distribution networks. This paper presents a new Hybrid Electromagnetism-like Algorithm for solving capacitated vehicle routing problems. Electromagnetism-like Algorithm is a population-based algorithm based on attraction-repulsion mechanisms between charged particles. A modified objective function value calculation approach, utilizing the Random-Key Procedure makes it possible for Electromagnetism-like Algorithm to solve known combinatorial optimization problems like capacitated vehicle routing problems. Here, the solutions obtained such are improved by a relatively new local search method, Iterated Swap Procedure, and tested on several benchmarking problems. The computational results show that the proposed Hybrid Electromagnetism-like Algorithm gives promising results within acceptable computational times when compared to other novel meta-heuristics.
URI: https://doi.org/10.1016/j.eswa.2009.10.005
https://www.sciencedirect.com/science/article/pii/S0957417409008719
http://hdl.handle.net/11452/22481
ISSN: 0957-4174
1873-6793
Koleksiyonlarda Görünür:Scopus
Web of Science

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