Geoffrey Pond

Geoff Pond has been a member of RMC’s Department of Management since July, 2015 and taught an adjunct basis at both Queen's University (Smith School of Business and Engineering & Applied Science) and uOttawa (Telfer School of Business) since 2016.

Prior to joining academia, Dr. Pond spent 7 years as a member of Defence Research and Development Canada as an analyst with the Centre for Operations Research and Analysis. He has been a member of NATO and ABCA research panels, authored a number of government reports, and presented research at a number of national and international conferences.

His research is focused on optimization of resources, specifically in support of fleet management. His PhD in mechanical engineering was awarded by the University of New Brunswick in 2006. Dr. Pond also holds a Masters Degree in Public Administration awarded by Queen's University.

Academic Degrees

• Ph.D. Mechanical Engineering
  University of New Brunswick (2006)

• Master’s in Public Administration
  Queen’s University (2016)

• B.Sc.Eng. Mechanical Engineering
  University of New Brunswick (2003)

• Diploma in Technology Management and Entrepreneurship
  University of New Brunswick, Dr. J. Herbert Smith Centre (2001)

Academic Experience

• Department of Management and Economics, Royal Military College of Canada
  Associate Professor (2015 - Present)
  Sessional Instructor (2015)

• Smith School of Business, Queen's University
  Term Adjunct (2015 – Present)

• Telfer School of Management, University of Ottawa
  Term Adjunct (2016 & 2020)

• Laurentian University School of Business, St. Lawrence College
  Faculty Member (2008-2015)

Research Interests

Optimisation

• the application of global meta-heuristics to business and military problems. More specifically, Differential Evolution (DE), Genetic Algorithms (GA), Ant Colony, Particle Swarm, and Tabu Search algorithms.
• Hybrid algorithms which include a local search strategy (i.e., linear programming, vertex swap algorithm, or greedy algorithms), within a global meta-heuristic.
• Fuzzy logic and fuzzy optimization
• Supervised and Unsupervised Learning

Fleet Management

• Applications of aforementioned optimization strategies to
  • Fleet staging
  • Fleet composition
  • Maintenance planning
  • Spare parts inventories

Awards

• (Nomination) Teaching Excellence Award (RMC) (2017)
• Best Presentation Award, UK OR Society (2011)
• Science and Technology Excellence Award, Defence Research and Development Canada (2010)
• Best Overall Paper, International Symposium of Military Operations Research (2010)
• Best Paper (Honourable Mention), Administrative Sciences Association of Canada (2010)
• Nominated by UNB: Doctoral Prize (23 submissions made nationally), NSERC: Engineering and Computer Science (2007)
• Advanced Studies Scholarship (Doctoral), Association of Professional Engineers and Geoscientists of New Brunswick (2005)
• Graduate Bursary, University of New Brunswick (2004)
• Youth Delegate Award, International Federation for the Promotion of Mechanism and Machine Science (2004)