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Diane Elizabeth Vaughan
Dr. Diane Elizabeth Vaughan
Post
Doctorate Research Associate
Department of Mechanical and Industrial
Engineering
University of Illinois at Urbana-Champaign
1206 West Green Street,
MC-244
vaughand@vt.edu
(540) 626 5741 (Home)
(540) 231-3838 (Office)
Formal Curriculum Vitae (pdf)
Research Activities (Want to know more?)
Projection Pursuit: The
objective of this project is to study the problem of finding an optimal
projection of data contained in a high dimensional space to a lower dimensional
space. The Bayes Classifier is used to
classify the data in the low dimensional space.
Hybrid Local Search Algorithms: This research creates hybrid algorithms that
combine heuristic procedures that guarantee long term convergence (globally optimal
solutions) with heuristic procedures that guarantee reasonable finite-time
performance (locally optimal solutions).
Formulating the
Meta-Heuristic Tabu Search: The
goal of this project is to mathematically formulate probabilistic tabu search
to be used in conjunction with other heuristics (i.e., simulated annealing), in
such a way that the heuristic can be easily modeled as a nonstationary Markov
Chain.
Discrete Manufacturing
Process Design Optimization: This research is motivated by the Air Force’s interest in
identifying optimal manufacturing process designs, where the finished unit
(e.g., a titanium integrated blade rotor) meets certain geometric and
microstructural specifications, and is produced at minimum cost.
Simultaneous Generalized Hill Climbing
Algorithms: This
research focuses on approaching sets of related discrete optimization problems
(i.e., overlapping traveling salesman problems, machine shop scheduling
problems with similar constraints).
Optimal Search Strategy Problem: This research models optimal strategies for
conducting military searches using a set of platforms (i.e., helicopters,
planes) as the well-known traveling salesman problem.
Optimal Earthmoving Vehicle Routes: This research develops a
mathematical model for minimizing the cost of operating large capacity vehicles
to level project sites prior to a construction project.
Analysis of the Urn
Problem:
This research uses
probability theory as well as computational techniques to approach variations
of the well-known urn problem.
Hybrid Neighborhood
Functions: This research develops hybrid neighborhood
functions that combine aggressive neighborhood structures with myopic
neighborhood structures.
Education
2000
Ph.D. (Industrial and Systems
Engineering, Operations Research)
Virginia Polytechnic Institute and State University, (coursework)
1997 M.S. (Mathematics)
Oregon State University, (coursework)
1994 B.A. (Mathematics) Central Washington University
Dissertation Simultaneous Generalized Hill
Climbing Algorithms for Addressing
Sets of Discrete Optimization Problems
(Summary) (pdf)
(Talk)
Awards
2001 Paul
E. Torgersen Graduate Student Research Excellence Award, Second place
2001 AAUW Postdoctoral
Research Leave Fellowship (Runner-up)
1995 Nominated for and Attended Industrial
Mathematics Modeling Workshop, N.C. State University
1993 Ronald E. McNair Scholar
1993 Ronald E. McNair Scholar
Summer
Research Grant Award, Surge Tank Analysis
Professional Affiliations
Institute for Operations Research and the Management Sciences (INFORMS)
Institute of Industrial Engineers (IIE)
American Association of University Women (AAUW)
Media coverage
The paper “A New
Neighborhood Function for Discrete Manufacturing Process Design Optimization
Using Generalized Hill Climbing Algorithms,” (co-authored with Derek E.
Armstrong and Sheldon H. Jacobson) published in ASME Journal of Mechanical
Design (Volume 122, Number 2, 164-171) was featured in an article on October
20, 2000 focusing on new directions in manufacturing research in Advanced
Manufacturing Technology.
Collaborators
Sheldon H. Jacobson, Ph.D.,
Associate Professor, Department of Mechanical and Industrial Engineering
University of Illinois at Urbana-Champaign
LTC
Darrall Henderson, Ph.D., Assistant Professor, Department of Mathematical
Sciences, United States Military Academy, West Point, New York
John E. Kobza,
Ph.D., Associate Professor, Department of Industrial Engineering, Texas Tech
University
Ron R.
Wakefield, Ph.D., William E. Jamerson Professor of Building Construction,
Virginia Polytechnic Institute and State University
Derek
Armstrong, Graduate Student, Department of Mechanical and Industrial
Engineering University of Illinois at Urbana-Champaign
Papers (Abstracts)
Vaughan, D.E.,
Jacobson, S.H., Armstrong, D., 2000, “A
New Neighborhood Function for Discrete Manufacturing Process Design
Optimization using Generalized Hill Climbing Algorithms,” ASME Journal
of Mechanical Design, 122 (2), 164-171. (pdf)
Henderson, D.,
Vaughan, D.E., Jacobson, S.H., Wakefield, R., Sewell, E.C., 2002, “Analyzing the Cut and Fill Problem
Using Local Search Algorithms,” Accepted.
European Journal of Operations Research. (pdf)
Henderson,
D., Vaughan, D.E., Jacobson, S.H., Wakefield, R., 2002a, “Optimal Search Strategies Using Local Search
Strategies,” Invited Paper, Nominated for Barchi Prize, Submitted to Military
Operations Research. (pdf)
Henderson,
D., Wakefield, R.R., Vaughan, D.E., Jacobson, S.H., 2002b, “Optimal Earthmoving
Vehicle Routes Using Local Search Algorithms,” Invited Paper, Accepted by the First
International Conference on Innovation in Architecture, Engineering and
Construction.
Vaughan,
D.E., Jacobson, S.H., 2002a, “Formulating
the Meta-Heuristic Tabu Search in the Generalized Hill Climbing Algorithm
Framework,” Submitted. (pdf)
Vaughan, D.E.,
Jacobson, S.H., 2002b, “Simultaneous Generalized Hill Climbing Algorithms for
Addressing Sets of Discrete Optimization Problems,” Submitted. (pdf)
Vaughan, D.E.,
Jacobson, S.H., 2002c, “Nonstationary Markov
Chain Analysis of Simultaneous Generalized Hill Climbing Algorithms,”
Submitted. (pdf)
Papers in preparation to be submitted
Vaughan,
D.E., Kobza, J., Jacobson, S.H., 2002, “The Urn Problem with Random Sample Sizes,”
Technical Paper, University of Illinois at Urbana-Champaign.
Vaughan,
D.E., Henderson, D., Jacobson, S.H., 2002, “Investigating Neighborhood
Functions for the Optimal Search Strategy Problem,” Technical Paper, University
of Illinois at Urbana-Champaign.
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