Topics in Combinatorial Algorithms (Multicommodity Flows, Quadratic Programming)
Vaidya, Pravin Moreshwar
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/69567
Description
Title
Topics in Combinatorial Algorithms (Multicommodity Flows, Quadratic Programming)
Author(s)
Vaidya, Pravin Moreshwar
Issue Date
1986
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Computer Science
Abstract
This thesis is a study of a wide variety of combinatorial optimization problems.
In chapters two and three the problems of finding minimum weight matchings and minimum spanning trees on points in space are investigated and fast approximation algorithms are presented for both the problems. A key idea is to exploit the geometry underlying these problems.
In chapter four an optimal algorithm for the All-Nearest-Neighbors problem is described.
In chapter five we develop polynomial time approximation schemes for a generalization of bin packing where some items may be left unpacked and there is a penalty associated with each unpacked item.
In chapter six we investigate the trade-off between storage space and retrieval time for orthogonal range query on a static data base. Lower bounds on the product of space and time are obtained.
In the last chapter we develop fast algorithms for convex quadratic programming and multicommodity flows.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.