IDEAS home Printed from https://ideas.repec.org/a/igg/joris0/v6y2015i1p49-63.html
   My bibliography  Save this article

Simulation-Based Scheduling of Waterway Projects Using a Parallel Genetic Algorithm

Author

Listed:
  • Ning Yang

    (Parsons Corporation, New York, NY, USA)

  • Shiaaulir Wang

    (Clarksville, MD, USA)

  • Paul Schonfeld

    (Department of Civil and Environmental Engineering, University of Maryland, College Park, MD, USA)

Abstract

A Parallel Genetic Algorithm (PGA) is used for a simulation-based optimization of waterway project schedules. This PGA is designed to distribute a Genetic Algorithm application over multiple processors in order to speed up the solution search procedure for a very large combinational problem. The proposed PGA is based on a global parallel model, which is also called a master-slave model. A Message-Passing Interface (MPI) is used in developing the parallel computing program. A case study is presented, whose results show how the adaption of a simulation-based optimization algorithm to parallel computing can greatly reduce computation time. Additional techniques which are found to further improve the PGA performance include: (1) choosing an appropriate task distribution method, (2) distributing simulation replications instead of different solutions, (3) avoiding the simulation of duplicate solutions, (4) avoiding running multiple simulations simultaneously in shared-memory processors, and (5) avoiding using multiple processors which belong to different clusters (physical sub-networks).

Suggested Citation

  • Ning Yang & Shiaaulir Wang & Paul Schonfeld, 2015. "Simulation-Based Scheduling of Waterway Projects Using a Parallel Genetic Algorithm," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 6(1), pages 49-63, January.
    • Handle: RePEc:igg:joris0:v:6:y:2015:i:1:p:49-63
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijoris.2015010104
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:joris0:v:6:y:2015:i:1:p:49-63. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.