• 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