Operations Research

Operations Research (OR) is distinguished by its use of quantitative methods (mathematics, statistics, and computing) to aid in rational decision making. Operations Research has been successfully applied to a wide range of problems arising in business and government, such as locating industrial plants, allocating emergency facilities, planning capital investments, designing communication systems, and scheduling production in factories. A common element of these decision problems is the need to allocate scarce resources (such as money, time, or space) while attempting to meet conflicting objectives (such as minimizing cost or maximizing production).

Faculty

W. P. Adams » mathematical programming, optimization
P. M. Dearing » location theory, discrete optimization
P. Hyden » simulation
J. P. Jarvis » network algorithms, discrete computing
P. C. Kiessler » stochastic processes, queueing theory
M. M. Kostreva » optimization, nonlinear analysis
M. J. Saltzman » computational operations research, mathematical programming
D. R. Shier » network optimization, discrete mathematics
M. Wiecek » optimization, multicriteria decision making

Curriculum

Operations Research often approaches a particular problem from several modeling perspectives and uses various analytical techniques. Because of the diversity and broad scope of decision problems, the successful OR practitioner requires training in a number of mathematical concepts and techniques. Areas in the mathematical sciences that relate directly to OR are optimization (linear, nonlinear, integer, network programming, calculus of variations, control theory); applied probability (stochastic processes, queueing, reliability); and applied statistics (simulation, econometrics, time series). Computational mathematics also plays an important role in the effective application of OR because of the need to structure and analyze vast amounts of data and to solve large-scale problems efficiently. Other areas of the mathematical sciences related to OR are combinatorics, graph theory, financial mathematics, and dynamical systems.

Courses

	probability	stochastic processes
	stochastic models in OR - I	stochastic models in OR - II
	mathematical programming	advanced linear programming
	nonlinear programming	discrete optimization
	network flow programming	network algorithms & data structures
	multicriteria optimization	complementarity models

Sample Curricula

- Sample Program for M.S. Concentration in Optimization

FALL: 800, 810, 853

SPRING: 803, 805, 860

SUMMER: 821

FALL: 812, 814, 988

SPRING: 811, 813, 817, 892

- Sample Program for M.S. Concentration in Stochastics

FALL: 803, 810, 853

SPRING: 805, 817, 860

SUMMER: 821

FALL: 800, 818, 988

SPRING: 811, 809, 901, 892

Recent M.S. Graduates (master's project title)

Kara Andrighetti ("Subgradient Optimization for Lagrangian Coordination")
Suman Balasubramanian ("An Extended GRASP for the Three Index Assignment Problem")
Gisela Bardossy ("Label-Correcting Algorithms for Single-Source Shortest Path Problems")
Sharmistha Chakrabarti ("Linear Programming Approaches Applied to Square Blocking on Hypercube Problems")
Minsang Chan ("A p-Center Location Problem Minimizing the Maximum of Travel Time Plus Waiting Time")
Yunwei Cui ("Solving l₁ Planar Location Problems with Barriers by Convex Domains")
Ben Clark ("The Time Dependent Multi-Criteria Knapsack Problem: Theory, Applications and Implementation")
Steven Dooley ("Automated Political Redistricting for South Carolina: An Analysis and Proposal")
Jonathan Edds ("Cancellation in Cyclic Consecutive Sets")
Alexander Engau ("Can We Get Worse? - Exploring Epsilon-Efficiency in Multiobjective Programming")
Stacey Faulkenberg ("Bilevel Mathematical Programs: Methodology and Application in Packaging")
Ken Flowers ("Store Ranking Problems: Analysis and Algorithms")
Nadine Gaertner ("A Multicommodity Flow Approach to a Matrix Decomposition Problem")
Elena Gavriliouk ("Aggregation in Hub Location Models")
Brian Hunt ("On Finding Equilibrium Points of Bimatrix Games by Exploiting a Special Matrix Structure")
David Hurst ("SIGMA to MATLAB: Simulation with Time Dilation")
Sathish Indika ("Exact and Heuristic Approaches for Scheduling Aircraft Maintenance Programs")
Thomas Kehl ("Optimal Server Positioning on Trees")
Cassandra Kirby ("Examining the Source and Consistency of Consumer Reports' Automobile Recommendations")
Christine Kraft ("Predicting Course Enrollment")
Jennifer LaVare ("Finding Rectilinear Distances Among Points and Barriers")
Jonathon Leverenz ("Balanced Sampling in Ranked Populations")
Carrie Paul ("A Network Model for Assigning Instructors to Classes")
Dustin Reed ("Patterns in the Consumer Reports Used Car List")
Stefan Ruzika ("A Review of Approximation Methods in Multiple Objective Programming")
Sundeep Samson ("Performance-Based Decisions for Complex Systems: A Manual")
Vijay Singh ("Multi-Scenario Multi-Criteria Optimization in Engineering Design")
Ben Staufeneger ("Lift and Project Cuts in a Cut and Branch Framework")
Nicholas Tallyn ("A Computational Study of Reverse Ordering Heuristics for Minimum Chordal Supergraphs")
Alicia Teal ("The Effects of Shift Scheduling on the Sleep-Wake Cycle Analysis of a Two-Week Shift Schedule")
Phantipa Thipwiwatpotjana ("One-Center Problem in R² with Block Distance")
Mary Zachary ("An Integer Programming Approach to Restaurant Staff Scheduling")

Recent Ph.D. Graduates (dissertation title)

Jim Brumbaugh-Smith ("Diversified Network Routing via Minimax Objectives")
Xiben Chen ("Methods of Feasible Directions for Nonlinear Programming: Theory and Algorithms")
Steve Clark ("Stochastic Control Models for Research and Development Projects")
Arthur Field ("Applying Monte Carlo Simulation Techniques to Amusement Park Queuing Protocols to Reduce Waiting Time and Enhance Customer Satisfaction")
Richard Forrester ("Addressing Formulation Size, Strength, and Mathematical Structure in Modeling Discrete Decision Problems")
Artur Gorka ("The Random Multi-Directional Method of Feasible Directions")
Paul Hadavas ("Exploiting Network Substructures and Persistency in Solving 0-1 and General Nonconvex Optimization Problems")
Brian Hunt ("Multiobjective Programming with Convex Cones: Methodology and Applications")
Kevin Hutson ("Stochastic Minimum Spanning Trees")
Laura Lancaster ("A Generalization of Multiple Objective Dynamic Programming with Time-Dependent Costs")
Erin McNelis ("Using a Circadian Rhythms Model to Develop Optimal Shift Work Schedules")
Dawn Rose ("Solution Approaches for a Multi-Dimensional Scheduling Problem in the Apparel Industry")
Bernd Schandl ("Norm-Based Evaluation and Approximation in Multicriteria Programming")
Roy Segars ("Location Problems with Barriers Using Rectilinear Distance")
Debbie Summerlin ("A Linear Zero-One Model for Designing Interconnected Local Area Networks")
Amy Ward ("Minimax Optimal Control of Steady State Systems")
Ruth Wassermann ("Full-Load Truck Routing with Time Windows")
Tom Whitaker ("Improved Methods for Numerical Shade Sorting in Apparel Manufacturing")

Current Ph.D. Students (dissertation advisor)

Alexander Engau (M. Wiecek)
Kanoktip Nimitkiatklai (P. Kiessler)
Vijay Singh (M. M. Kostreva)

Additional OR Links

INFORMS home page
INFORMS OR/MS Resource Collection (formerly Michael Trick's OR page)
educational programs in OR/MS
IFORS TutORial page
John Beasley's OR Notes
John Mitchell's OR/Optimization page
Harvey Greenberg's Math Programming Glossary
Optimization: Frequently Asked Questions

Last Updated: July 18, 2005
Send comments to: shierd@clemson.edu