Doctoral Dissertations

Title

Computational intelligence and the traveling salesman

Abstract

"The Traveling Salesman Problem (TSP) is one of the most widely studied problems in the computer science literature...Computational Intelligence approaches have traditionally performed very poorly on combinatorial optimization problems such as the TSP, when compared to results in Operations Research. This dissertation explores two different Computational Intelligence techniques and combines them with the latest Operations Research local search heuristics to develop new heuristics that expand the capabilities of existing techniques. The first approach combines an Adaptive Resonance Theory (ART) neural network with the iterated Lin-Kernighan algorithm to divide and conquer extremely large TSPs. This new algorithm provides significant advantages in scaling and memory usage. The second approach uses an Evolutionary Algorithm to parallelize the iterated Lin-Kernighan algorithm and explore the search space more thoroughly"--Abstract, leaf iii.

Department(s)

Computer Science

Degree Name

Ph. D. in Computer Science

Publisher

University of Missouri--Rolla

Publication Date

Summer 2004

Pagination

ix, 77 leaves; 1 CD-ROM (4 3/4 in.)

Note about bibliography

Includes bibliographical references (leaves 73-76).

Rights

© 2004 Samuel Aaron Mulder, All rights reserved.

Document Type

Dissertation - Citation

File Type

text

Language

English

Library of Congress Subject Headings

Traveling-salesman problem
Heuristic programming
Combinatorial optimization

Thesis Number

T 8560

Print OCLC #

61895974

Link to Catalog Record

Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.

http://laurel.lso.missouri.edu/record=b5370576~S5

Comments

System requirements: C++ Compiler required. Microsoft Visual Studio.NET using the Intel C++ Compiler 8.0 recommended.

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