Abstract—This paper demonstrates a novel computational method intended to develop inspiration from a synthesis of carbon nanotubes. The proposed method is Artificial Carbon Nanotubes Synthesis Optimization (ACNSO). In this paper, one of the first applications has been executed in the blood vehicle routing problem and has been demonstrated. This algorithm was tested on three sizes of benchmarking datasets of the blood vehicle routing problem. The advantage of this algorithm is to check the travel conditions between the points before creating the initial solution. As a result, the overall processing time is reduced. However, this research presented a definition of the appropriate parameters of this algorithm for the optimal solution. The design of the experiment is adopted to investigate the factors affecting the performance of the algorithm. The experiments were conducted to compare the efficiency of the other algorithms in previous research in terms of the distance.
Index Terms—Metaheuristic approach, artificial carbon nanotubes synthesis optimization, blood vehicle routing problem, design of experiment.
Kanon Sujaree is with the Department of Industrial Engineering, Faculty of Engineering, Innovation Center of Logistics and Water Transportation, Rajamangala University of Technology Rattanakosin, Nakhonpathom, Thailand (e-mail: Kanon.suj@rmutr.ac.th).
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Cite: Kanon Sujaree, "Artificial Carbon Nanotubes Synthesis Optimization: A Novel Nanoscience Based Metaheuristic Approach for Blood Vehicle Routing Problems," International Journal of Materials, Mechanics and Manufacturing vol. 8, no. 3, pp. 109-118, 2020.
Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (
CC BY 4.0).
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