A clustering-based algorithm for the Rectilinear Steiner Tree Problem
General Material Designation
[Thesis]
First Statement of Responsibility
Y. K. Karimjee
.PUBLICATION, DISTRIBUTION, ETC
Name of Publisher, Distributor, etc.
King Fahd University of Petroleum and Minerals (Saudi Arabia)
Date of Publication, Distribution, etc.
1994
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
113
DISSERTATION (THESIS) NOTE
Dissertation or thesis details and type of degree
M.S.
Body granting the degree
King Fahd University of Petroleum and Minerals (Saudi Arabia)
Text preceding or following the note
1994
SUMMARY OR ABSTRACT
Text of Note
The Steiner Tree Problem is the determination of the shortest connecting length between a given set of points and additional points. The Rectilinear Steiner Tree Problem is the same as above but the connecting lines are confined to the horizontal or vertical lines only (usdL\sb1usd metric). A cluster is a set of points that "influence" each other locally. This research gives a new algorithm based on a clustering metric that determines much less steiner points locally in a cluster as well as those external to it. The algorithm matches the worst-case time complexity of O(nlogn) of previous authors while giving better average results then theirs. In addition, a Neural Solution to the Steiner problem in Networks, which is a graph-theoretic representation of the problem, is explored and its limitations presented.