DocumentCode
160489
Title
Parallel universes algorithm: A metaheuristic approach to solve vehicle routing problem
Author
Bayat, Alireza Akbari
Author_Institution
Dept. of Math. & Comput. Sci., Amirkabir Univ. of Technol., Tehran, Iran
fYear
2014
fDate
11-13 July 2014
Firstpage
1
Lastpage
7
Abstract
Meta-heuristic algorithms such as genetic and particle swarm optimization (PSO) algorithms have become suitable methods for solving complex optimization problems. This paper presents a new meta-heuristic algorithm called parallel universes. This algorithm is based on an unproven theory in physics called parallel universes. In this article, we first explain the essential steps of the algorithm and how it works. To prove the efficiency of our algorithm, we compare the results of our algorithm with the improved ant colony optimization (IACO), ant-weight strategy (ACO-W), the ant-mutation Operation (ACO-M) and improved ant colony system (IACS). We also examine the speed of convergence to the final solution by the algorithm. Comparing the solution provided by our algorithm with four other algorithms clearly shows the superiority of our algorithm in the final solution.
Keywords
ant colony optimisation; genetic algorithms; particle swarm optimisation; vehicle routing; ant colony optimization; ant-mutation operation; ant-weight strategy; complex optimization problem; genetic algorithm; improved ant colony system; metaheuristic approach; parallel universes algorithm; particle swarm optimization algorithm; vehicle routing problem; Algorithm design and analysis; Computer science; Convergence; Genetic algorithms; Heuristic algorithms; Optimization; Vehicle routing; Parallel algorithms; heuristics; optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Computing, Communication and Networking Technologies (ICCCNT), 2014 International Conference on
Conference_Location
Hefei
Print_ISBN
978-1-4799-2695-4
Type
conf
DOI
10.1109/ICCCNT.2014.6963104
Filename
6963104
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