Dissertation/Thesis Abstract

A Vector Parallel Branch and Bound Algorithm
by Guilbeau, Jared T., Ph.D., University of Louisiana at Lafayette, 2016, 100; 10242153
Abstract (Summary)

Global optimization problems sometimes attain their extrema on infinite subsets of the search space, forcing mathematically rigorous programs to require large amounts of data to describe these sets. This makes these programs natural candidates for both vectorization methods and parallel computing. Here, we give a brief overview of parallel computing and vectorization methods, exploit their availability by constructing a fully distributed implementation of a mathematically rigorous Vector Parallel Branch and Bound Algorithm using MATLAB’s SPMD architecture and interval arithmetic, and analyze the performance of the algorithm across different methods of inter-processor communication.

Indexing (document details)
Advisor: Kearfott, R. Baker
Commitee: Browne, Cameron, Sutton, Karyn
School: University of Louisiana at Lafayette
Department: Sciences
School Location: United States -- Louisiana
Source: DAI-B 78/12(E), Dissertation Abstracts International
Subjects: Mathematics, Operations research, Computer science
Keywords: Branch and Bound, Global optimization, Interval arithmetic, Parallel processing, Vector operations
Publication Number: 10242153
ISBN: 978-0-355-11282-5
Copyright © 2021 ProQuest LLC. All rights reserved. Terms and Conditions Privacy Policy Cookie Policy