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Mark Rempel

Observed names: M. Rempel, MARK REMPEL, Rempel, Mark
ORCID: 0000-0002-6248-1722
Observed ORCID: 0000-0002-6248-1722
OpenAlex ID: A5061348941
A review of approximate dynamic programming applications within military operations research
2021 · M. Rempel, J. Cai · Operations Research Perspectives · 15
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A methodological approach for modeling the spread of disease using geographical discrete-event spatial models
2023 · Glenn Davidson, Aidan Fahlman, et al. · SIMULATION · 8
Modelling a major maritime disaster scenario using the universal modelling framework for sequential decisions
2023 · M. Rempel · Safety Science · 5
An approximate dynamic programming approach to tackling mass evacuation operations
2021 · Mark Rempel, Nicholi Shiell, et al. · IEEE Symposium Series on Computational Intelligence (SSCI) · 5
A multiobjective coverage‐based model for Civilian search and rescue
2009 · Yaw Asiedu, Mark Rempel · Naval Research Logistics (NRL) · 5
GeoHexViz: A Python package for the visualizing hexagonally binned geospatial data
2023 · Tony M. Abou Zeidan, Mark Rempel · The Journal of Open Source Software · 3
PDF
Extended Compartmental Model of Covid-19: A Cell-DEVS Defitinion
2021 · Aidan Fahlman, Cristina Ruiz-Martin, et al. · IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications (DS-RT) · 3
On a Second Generation Strategic Decision-Making Process for the Canadian Forces
2010 · Mark Rempel · 3
Reinforcement Learning for decision support in defense and security: A systematic review
2026 · Maarten P. D. Schadd, David S. Berman, et al. · Annals of Operations Research · 2
PDF
An Overview of the Canadian Forces' Second Generation Capability-Based Planning Analytical Process
2010 · Mark Rempel · 2
Modelling Defence Planning as a Sequential Decision Problem
2025 · Carolyn Chen, Mark Rempel, et al. · International Conference on Operations Research and Enterprise Systems · 1
Using Reinforcement Learning to Provide Decision Support in Multi-Domain Mass Evacuation Operations
2023 · Mark Rempel, Nicholi Shiell · NATO Journal of Science and Technology · 1
PDF
Studying the Spread of Diseases Using Geographical Data and Irregular Topologies with Cell-DEVS
2021 · Roman Cardenas, Cristina Ruiz Martin, et al. · Annual Modeling and Simulation Conference (ANNSIM) · 1
Decision Support for Optimal Use of Joint Training Funds in the Canadian Armed Forces
2019 · Matthew R. MacLeod, Mark Rempel, et al. · Advances in public policy and administration (APPA) book series · 1
Visualizing capability requirements in planning scenarios using Principal Component Analysis
2012 · Mark Rempel · 1
High‐Level Methodologies to Evaluate Naval Task Groups
2011 · RANDY MARTENS, MARK REMPEL · Naval Engineers Journal · 1
Reinforcement Learning for decision support in defense and security. A systematic review
2026 · Schadd, Maarten, Berman, David, et al. · Annals of Operations Research
pyMassEvac: A Python package for simulating multi-domain mass evacuation operations
2026 · Mark Rempel · The Journal of Open Source Software
PDF
pyMassEvac: A Python package for simulating multi-domain mass evacuation operations
2026 · Rempel, Mark · Zenodo (CERN European Organization for Nuclear Research)
The Crossroads Between Defence Investment Planning and Multi-Period Portfolio Optimization
2026 · Mark Rempel · IEEE Access
Using Visualization to Support Investment & Divestment Decisions in the Canadian Armed Forces
2021 · Mark Rempel · Journal of Data Science
PDF
Decision Support for Optimal Use of Joint Training Funds in the Canadian Armed Forces
2021 · Matthew R. MacLeod, Mark Rempel, et al. · IGI Global eBooks
The Portfolio Approach Developed to Underpin the Capital Investment Program Plan Review (CIPPR)
2014 · Chad Young, Mark Rempel
Works count: 24
Citation count: 57
H-index: 5
I10-index: 1
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