Return to search

Greedy randomized adaptive search procedure for traveling salesman problem

In this thesis we use greedy randomize adaptive search procedure (GRASP) to solve
the traveling salesman problem (TSP). Starting with nearest neighbor method to
construct the initial TSP tour, we apply the 2-opt and the path-relinking method
for the initial tour improvement. To increase 2-opt search speed, fixed-radius near
neighbor search and don0t − look bit techniques are introduced. For the same reason
a new efficient data structure, the reverse array, is proposed to represent the TSP
tour. Computational results show that GRASP gives fairly good solutions in a short
time.

Identiferoai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/3735
Date16 August 2006
CreatorsLee, Seung Ho
ContributorsButenko, Sergiy
PublisherTexas A&M University
Source SetsTexas A and M University
Languageen_US
Detected LanguageEnglish
TypeBook, Thesis, Electronic Thesis, text
Format371208 bytes, electronic, application/pdf, born digital

Page generated in 0.0019 seconds