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Biography

Name: Patrick R. McMullen

Title: Associate Professor

Affiliation: School of Business, Wake Forest University, USA

Email: mcmullpr@wfu.edu


Research fields:

Continuous Optimization

Discrete Optimization

Heuristics Mathematical Programming

Networks

Simulation

Stochastic Models and Statistics

Inventory

Planning and Scheduling

Quality Management

Education Operations Research

Government Operations Research

Health Services Operations Research

Marketing Science

Military and Homeland Security

Operations Research in Nonprofit Organization

Policy Modeling and Public Sector OR

Sports Operations Research


Qualifications:

1995 Ph.D., University of Oregon, Decision Science

1991 M.B.A., Butler University, Management

1987 B.Sc., University of Louisville, Industrial Engineering


Publications:

  1. McMullen, P.R. (2020). "Social Distancing via Coulomb's Law,Applied Mathematics, 11, 532-545.
  2. McMullen, P.R. (2020). "An Agent-Based Approach to the Newsvendor Problem with Price-Sensitive Demand,American Journal of Operations Research, 10, 101-110.
  3. McMullen, P.R. (2019). "A Markov Simulation Approach to Balancing Bike-Sharing Systems,American Journal of Operational Research, 9(1), 12-17.
  4. McMullen, P.R. (2017). "Standardization of Winning Streaks in Sports,Applied Mathematics, 8, 344-357.
  5. McMullen, P.R. (2017). "Ant-Colony Optimization for the System Reliability Problem with Quantity Discounts,American Journal of Operations Research, 7, 99-112.
  6. McMullen, P.R. (2015). "Using Baseball Data as a Gentle Introduction to Teaching Linear Regression,Creative Education. Vol. 6, No. 14, pp. 1477-1483.
  7. McMullen, P.R. (2015). "JIT Mixed-Model Sequencing Rules: Is There a Best One?American Journal of Operations Research. Vol. 5, No. 1, pp. 22-29.
  8. McMullen, P.R. (2013). "A Genetic Algorithm for Multiple Inspections with Multiple ObjectivesAmerican Journal of Operations Research. Vol. 3, No. 6, pp. 463-473.
  9. McMullen, P.R. (2012). "Limited Resequencing for Mixed-Models with Multiple Objectives, Part II: A Permutation ApproachAmerican Journal of Operations Research. Vol. 2, No. 1, pp. 10-21.
  10. McMullen, P.R., Meredith, J.M. (2010). "Editorial: Passing on the Torch of Operations Management Research,Operations Management Research . Vol. 4, No. 3/4, pp. 87-88.
  11. McMullen, P.R. (2011). "Limited Resequencing for Mixed-Models with Multiple Objectives," American Journal of Operations Research. Vol. 1, No. 4, pp. 220-228.
  12. McMullen, P.R. (2010). "JIT Mixed-Model Sequencing with Batching and Setups Considerations via Search Heuristics," International Jounal of Production Research. Vol. 47, No. 22, pp. 6559-6582.
  13. Meredith, J.R. & McMullen, P.R. (2010)."Editorial: State of the Journal: February, 2010," Operations Management Research. Vol. 3, Number 1, pp. 1-6.
  14. Meredith, J.R. & McMullen, P.R. (2008)."Introducing Operations Mangement Research: Advancing Practice Through Theory,"Operations Management Research. Vol. 1, Number 1, pp. 1-5.
  15. McMullen, P.R. & Shafer, S.M. (2008)."Beyond Central Tendency:  Helping Students Understand the Concept of Variation,"Decision Sciences Journal of Innovative Education. Vol. 6, Number 2, pp. 515-519
  16. Clayton, H. & McMullen, P.R. (2007), "Combining Approaches to Evaluating AuditingPopulations: A Simulation Study," European Journal of Operational Research. Vol. 178, pp. 907-917.
  17. McMullen, P.R. (2006), "An Objective Function to Address Production Sequencing with Minimal Tooling Replacements,International Journal of Production Research. Vol. 44, No. 12, pp. 2465-2478.
  18. Albritton, M.D. & McMullen, P.R. (2006), "Classroom Integration of Statistics and Management Science via Forecasting.Decision Sciences Journal of Innovative Education. Vol. 4, No. 2., pp. 331-336..
  19. Albritton, M.D., McMullen, P.R. (2007), "Designing Optimal Products Using a Colony of Virtual Ants," European Journal of Operational Research. Vol. 176, pp. 498-520.
  20. McMullen, P.R., Tarasewich, P. (2006),  Multi-objective assembly line balancing via a modified ant-colony optimization technique International Journal of Production Research. 44, 27-42.