Selected Publications



Network Optimization

  • Barr, R., F. Glover, and D. Klingman, Enhancements to Spanning Tree Labelling Procedures for Network Optimization, INFOR 17:1 (1979) 16-34 (PDF).
  • Barr, R., and J. S. Turner, Microdata File Merging through Large-Scale Network TechnologyMathematical Programming Study 15 (1981) 1-22 (PDF).
  • Barr, R., K. Farhangian and J. L. Kennington, Networks With Side Constraints: An LU Factorization Update, Annals of the Society of Logistics Engineers 1 (1986) 66-85 (PDF)
  • Barr, R. and B. Hickman, Parallel Simplex for Large Pure Network  Problems: Computational Testing and Sources of Speedup, which appeared  in slightly different form as "Parallelization Strategies for the  Network Simplex Algorithm," in Operations Research 42:1 (1994) pp-pp (PDF)
  • Barr, R., and M. Lewis,  Minimal Wavelength Assignment in Survivable Mesh Networks,  presentation at 7th INFORMS Computing Society Conference, Cancun, Mexico, January, 2000. (PDF, 128K)
  • Barr, R., B. Hickman, and J. S. Turner, Optimal Microdata File Merging: A New Model and Network Optimization Algorithm, presentation at 2000 INFORMS National Conference, San Antonio, TX (PDF, 296K).
  • Barr, R., and R. Patterson, Grooming Telecommunications Networks,Optical  Networks 2:3 (2001) 20-23 (PDF).
  • Garlick, R., and R. Barr, Dynamic Wavelength Routing in WDM Networks via Ant Colony Optimization, in Ant Algorithms (2002) 250-255 (PDF).
  • Apte, A., and R. Barr, An Interval-Pivoting Algorithm for the  Uniform-Bound Interval-Flow Transportation Problem, Technical Report  04-EMIS-01, May, 2004 (PDF).
  • R. Barr and R. Jones, Extreme-Point Search Heuristics for Solving Interval-Flow Transshipment Networks, technical report, June 2012 (PDF)
  • Barr, R., F. Glover, T. Huskinson, and G. Kochenberger, An Extreme-point Tabu-search Algorithm for Fixed-charge Network Problems, Networks 77:2 322–340, 2021. (Special Issue Article)
  • Barr, R. and T. McLoud, The Invisible Hand Heuristic for Origin-Destination Integer Multicommodity Network Flows, Networks 77, 2021.

Algorithm Experimentation and Reporting

  • Amini, M., R. Barr, Network Reoptimization Algorithms: A Statistically Designed Comparison, ORSA Journal on Computing 5:4 (1993)  395-409 (PDF)
  • Barr, R., and B. Hickman, Reporting Computational Experiments with Parallel Algorithms: Issues, Measures, and Experts' Opinions, which appeared in slightly different form in ORSA Journal on Computing 5:1 (1993) 2-18 (PDF)
  • Barr, R., B. Golden, J. Kelly, M. Rescende, and W. Stewart, Designing and Reporting on Computational Experiments with Heuristic Methods, which appeared in slightly different form in Journal of Heuristics 1:1 (1995) 9-32 (PDF)

Benchmarking with Data Envelopment Analysis

  • Barr, R., M. Durchholz, and L. Seiford, Peeling the DEA Onion: Layering and  Rank-Ordering DMUs Using Tiered DEA, Southern Methodist University technical report, 1994/2000 (PDF). See also (Barr and Seiford, 1996) below.
  • Barr, R. and L. Seiford, Benchmarking and Performance Improvement Tools  for Manufacturing and Service Processes, Proceedings of the 1996 National Science  Foundation Design and Manufacturing Grantees Conference, Albuquerque, New Mexico, January, 1996 (HTML)
  • Barr, R., L. Seiford, and T. Siems, Forecasting Bank Failure: A Non-Parametric Frontier Estimation Approach, which appeared in slightly different form in Reserches Economiques de Lovain 60:4 (1994) 417-429 (PDF)
  • Barr, R., and T. Siems, Bank Failure Prediction via Data Envelopment Analysis, which appeared in slightly different form in R. Barr, R. Helgason and J. Kennington, eds.Interfaces in Computer Science and Operations Research: Advances in Metaheuristics, Optimization, and Stochastic Modeling Technologies, Springer (1997) 341-366 (PDF, 288K)
  • Barr, R., and M. Durchholz, Parallel and Hierarchical Decomposition Approaches for Solving Large-Scale Data Envelopment Analysis Models, which appeared in slightly different form in Annals of Operations Research 73 (1997) 339-372 (PDF)
  • Siems, T., and R. Barr,  Benchmarking the Productive Efficiency of U.S. Banks, Financial Insustry Studies,  Federal Reserve Bank of Dallas, December, 1998  (PDF).
  • Richard S. Barr, Kory A. Killgo, Thomas F. Siems and Sheri Zimmel, Evaluating the Productive Efficiency and Performance of U.S. Commercial  Banks, technical report, December, 1999, revised July, 2000  (PDF), which appeared in slightly different form in Managerial Finance 28:8 (2002) 3-25
  • Thomas, R., R. Barr, W. Cron, and J. Slocum, Evaluating Retail Store Efficiency with Data Envelopment Analysis, International Journal of Research in Marketing 15 (1998) 487-503 (PDF)
  • Barr, R., DEA Software Tools and Technology: A State-of-the-Art  Survey, which appeared in slightly different form in W.W. Cooper, L. M.  Seiford, and J. Zhu, eds. Handbook on Data Envelopment Analysis, Kluwer Academic Publishers, Boston, 2004, pp. 539-566  (PDF)
  • Barr, R., T. Siems, N. Wells, Are Banks Near the DEA Efficient Frontier Better-Off?, working paper, 2021.

Data Analytics

  • Barr, R., and J. S. Turner, Microdata File Merging through Large-Scale Network Technology,Mathematical Programming Study 15 (1981) 1-22
  • Barr, R., and J. Turner,Quality Issues and Evidence in Statistical File Merging, in G. Liepins and Uppuluri, eds., Theory and Pragmatics of Data Quality Control, Marcel-Dekker, New York (1990) 245-313 (PDF)
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