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Asian Conference on Intelligent Information and Database Systems

ACIIDS 2017: Intelligent Information and Database Systems pp 55–64Cite as

To Solve the TDVRPTW via Hadoop MapReduce Parallel Computing

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10192))

Abstract

The convenience of online shopping has made it common to everyone. With the increase of online transaction, optimization of VRP is an important issue in logistics and transportation. TDVRPTW is a crucial problem which considers a given time window in VRP. This paper targets solving TDVRPTW by using Hadoop MapReduce and compares the effectiveness of Hadoop with a single machine. We used an existing program to cluster the demand nodes and then calculated a route for every cluster by using random method and heuristic algorithm including nearest time window algorithm, nearest neighbor algorithm and 2-opt. After that, we executed parallel computing in Hadoop by implementing program on MapReduce. We used Solomon benchmarking problem as the base of experimental examples and made the experiments. This research proved that Hadoop MapReduce has better efficacy to calculate the best solution than a single machine.

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Notes

  1. 1.

    http://www.visa.com.tw/aboutvisa/mediacenter/NR_tw_122215.html, Visa’s customer survey of e-commerce.

  2. 2.

    http://www.ithome.com.tw/article/87190, IDC, 2016.

  3. 3.

    http://www.hadoopwizard.com/which-big-data-company-has-the-worlds-biggest-hadoop-cluster/, Hadoop, 2016.

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Authors and Affiliations

  1. Graduate Institute of Information and Finance Management, National Taipei University of Technology, Taipei, Taiwan

    Bo-Yi Li & Chen-Shu Wang

Authors
  1. Bo-Yi Li
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  2. Chen-Shu Wang
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Corresponding author

Correspondence to Chen-Shu Wang .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wroclaw, Poland

    Ngoc Thanh Nguyen

  2. Japan Advanced Institute of Science and Technology, Nomi, Japan

    Satoshi Tojo

  3. Japan Advanced Institute of Science and Technology, Nomi, Japan

    Le Minh Nguyen

  4. Wrocław University of Science and Technology, Wroclaw, Poland

    Bogdan Trawiński

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Li, BY., Wang, CS. (2017). To Solve the TDVRPTW via Hadoop MapReduce Parallel Computing. In: Nguyen, N., Tojo, S., Nguyen, L., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2017. Lecture Notes in Computer Science(), vol 10192. Springer, Cham. https://doi.org/10.1007/978-3-319-54430-4_6

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  • DOI: https://doi.org/10.1007/978-3-319-54430-4_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54429-8

  • Online ISBN: 978-3-319-54430-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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