Parallel algorithms for the degree-constrained minimum spanning tree problem using nearest-neighbor chains and the heap-traversal technique

The degree-constrained minimum spanning tree (d-MST) problem attempts to find a minimum spanning tree with an added constraint that no nodes in the tree have a degree larger than a specified integer d. It is known that computing the d-MST is NP-hard for every d in the range 2 /spl les/ d /spl les/ (...

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Vydáno v:Proceedings. International Conference on Parallel Processing Workshop s. 398 - 404
Hlavní autoři: Li-Jen Mao, Sheau-Dong Lang
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 2002
Témata:
Computer science
Heuristic algorithms
Information management
Iterative algorithms
Lagrangian functions
Nearest neighbor searches
Neural networks
Parallel algorithms
Traveling salesman problems
Tree graphs
ISBN:9780769516806, 0769516807
ISSN:1530-2016
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Shrnutí:The degree-constrained minimum spanning tree (d-MST) problem attempts to find a minimum spanning tree with an added constraint that no nodes in the tree have a degree larger than a specified integer d. It is known that computing the d-MST is NP-hard for every d in the range 2 /spl les/ d /spl les/ (n - 2), where n denotes the total number of nodes. Several approximate algorithms (heuristics) have been proposed in the literature. We have previously proposed three approximate algorithms, IR, TC-RNN, and TC-NNC, for solving the d-MST problem, the last two (TC-RNN and TC-NNC) take advantage of nearest neighbors and their properties. Our experimental results showed that both the TC-RNN and TC-NNC algorithms consistently produce spanning trees with a smaller weight (better quality-of-solution) than that of IR, but using slightly longer execution time. We propose a new heap traversal technique that further improves the time efficiency of TC-RNN and TC-NNC. Our experiments using randomly generated, weighted graphs as inputs show that the TC-NNC algorithm outperforms the other two approximate algorithms in terms of the execution time and quality-of-solution.
ISBN:9780769516806
0769516807
ISSN:1530-2016
DOI:10.1109/ICPPW.2002.1039757