A high Performance Algorithm for Solving large scale Travelling Salesman Problem using Distributed Memory Architectures

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{Aggarwal:2011:ijcse,
  author =       "Khushboo Aggarwal and Sunil Kumar Singh and 
                 Sakar Khattar",
  title =        "A high Performance Algorithm for Solving large scale
                 Travelling Salesman Problem using Distributed Memory
                 Architectures",
  journal =      "Indian Journal of Computer Science and Engineering",
  year =         "2011",
  volume =       "2",
  number =       "4",
  pages =        "516--521",
  month =        aug # "-" # sep,
  keywords =     "genetic algorithms, genetic programming, TSP,
                 traveling salesman problem, fitness functions",
  ISSN =         "2231-3850",
  annote =       "The Pennsylvania State University CiteSeerX Archives",
  bibsource =    "OAI-PMH server at citeseerx.ist.psu.edu",
  language =     "en",
  oai =          "oai:CiteSeerX.psu:10.1.1.300.6369",
  rights =       "Metadata may be used without restrictions as long as
                 the oai identifier remains attached to it.",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.300.6369",
  URL =          "http://www.ijcse.com/docs/INDJCSE11-02-04-175.pdf",
  size =         "6 pages",
  abstract =     "In this paper, we present an intelligent solution
                 system for travelling salesman problem. The solution
                 has three stages. The first stage uses Clustering
                 Analysis in Data Mining to classify all customers by a
                 number of attributes, such as distance, demand level,
                 the density of customer, and city layout. The second
                 stage introduces how to generate feasible routing
                 schemes for each vehicle type. Specifically, a
                 depth-first search algorithm with control rules is
                 presented to generate feasible routing schemes. In the
                 last stage, a genetic programming model is applied to
                 find the best possible solution. Finally, we present a
                 paradigm for using this algorithm for distributed
                 memory architectures to gain the benefits of parallel
                 processing.",
}

Genetic Programming entries for Khushboo Aggarwal Sunil Kumar Singh Sakar Khattar

Citations