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Title: | A new hybrid electromagnetism-like algorithm for capacitated vehicle routing problems |
Authors: | 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 |
Keywords: | 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 |
Issue Date: | Apr-2010 |
Publisher: | Pergamon-Elsevier Science |
Citation: | 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. |
Abstract: | 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 |
Appears in Collections: | Scopus Web of Science |
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