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

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@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