Conceptual modeling for simulation: issues and research requirements
Proceedings of the 38th conference on Winter simulation
The simulation project life-cycle: models and realities
Proceedings of the 38th conference on Winter simulation
Models of motivation in software engineering
Information and Software Technology
OM Practice---Balancing Risk and Efficiency at a Major Commercial Bank
Manufacturing & Service Operations Management
Information models for queueing system simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Conceptual modeling of petascale computer systems
IIT'09 Proceedings of the 6th international conference on Innovations in information technology
Implementation issues of modeling healthcare problems: misconceptions and lessons
Winter Simulation Conference
Approaching complexity in modeling and simulation of logistics systems (WIP)
Proceedings of the 2012 Symposium on Theory of Modeling and Simulation - DEVS Integrative M&S Symposium
Model development in discrete-event simulation: insights from six expert modelers
Proceedings of the Winter Simulation Conference
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Skill in modeling is one of the keys to success in OR/MS practice. This has been recognized for many years, but we often give it only lip service. Models are used in many ways in OR/MS practice. A few simple principles of modeling may be useful. The six principles discussed here cover simplicity versus complexity; model development as a gradual, almost piecemeal process; dividing larger models into smaller components; using analogies; proper uses of data; and finally the way in which the modeling process can seem chaotic. Others may wish to comment on these principles and add their own.