A Simple Genetic Algorithm Parallelization Toolkit (SGAPTk) for Transportation Planners and Logistics Managers

In this paper the authors extend the standard meta-description for genetic algorithms with a simple non-trivial parallel implementation. The authors' work is chiefly concerned with the development of a straightforward way for engineers to modify existing genetic algorithm implementations for real industrial or scientific problems to make use of commonly available hardware resources without completely reworking complex, useful and useable codes. The authors present their framework and computational results comparing small scale parallelization for a classical transportation related combinatorial optimization problem – the traveling salesman problem with a standard sequential genetic algorithm implementation. The authors' empirical analysis shows that this simple extension can lead to considerable solution improvements. Next, the authors tested their assumptions that the results are typical and that the method is easily implemented by an engineer not initially familiar with genetic algorithms by implementing the toolkit for another classic scheduling problem.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ADB30 Transportation Network Modeling.
  • Corporate Authors:

    Transportation Research Board

    500 Fifth Street, NW
    Washington, DC  United States  20001
  • Authors:
    • Arkhipov, Dmitri I
    • Wu, Di
    • Regan, Amelia C
  • Conference:
  • Date: 2015


  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 18p
  • Monograph Title: TRB 94th Annual Meeting Compendium of Papers

Subject/Index Terms

Filing Info

  • Accession Number: 01556413
  • Record Type: Publication
  • Report/Paper Numbers: 15-1361
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 30 2014 12:31PM