Computational intelligence and the traveling salesman
"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.
Ph. D. in Computer Science
University of Missouri--Rolla
ix, 77 leaves; 1 CD-ROM (4 3/4 in.)
© 2004 Samuel Aaron Mulder, All rights reserved.
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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
Mulder, Samuel A., "Computational intelligence and the traveling salesman" (2004). Doctoral Dissertations. 1559.