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High Throughput Computing Application to Transport Modeling

  • Mahmoud Mesbah
  • Majid Sarvi
  • Jefferson Tan
  • Fateme Karimirad
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 145)

Abstract

Optimization of road space allocation (RSA) from a network perspective is computationally challenging. Analogues to the Network Design Problem (NDP), RSA can be classified as a NP-hard problem. In large scale networks when the number of alternatives increases exponentially, there is a need for an efficient method to reduce the number of alternatives as well as a computational approach to reduce the computer execution time of the analysis. A heuristic algorithm based on Genetic Algorithm (GA) is proposed to efficiently select Transit Priority Alternatives (TPAs). In order to reduce the execution time, the GA is modified to implement two parallel processing techniques: A High Performance Computing (HPC) technique using Multi-threading (MT) and a High Throughput Computing (HTC) technique. The advantages and limitations of the MT and HTC techniques are discussed. Moreover, the proposed framework allows for a TPA to be analyzed by a commercial package which is a significant provision for large scale networks in practice.

Keywords

Central Processing Unit High Performance Computing Network Design Problem Large Scale Network Parallel Genetic Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  • Mahmoud Mesbah
    • 1
  • Majid Sarvi
    • 2
  • Jefferson Tan
    • 1
  • Fateme Karimirad
    • 1
  1. 1.The University of Queensland UniversityQueenslandAustralia
  2. 2.Department of Civil EngineeringMonash UniversityClaytonAustralia

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