A specification language to assist in analysis of discrete event simulation models
Communications of the ACM
Multifacetted modelling and discrete event simulation
Multifacetted modelling and discrete event simulation
Compilers: principles, techniques, and tools
Compilers: principles, techniques, and tools
An introduction to simulation using GPSS/H
An introduction to simulation using GPSS/H
Structural and behavioral equivalence of simulation models
ACM Transactions on Modeling and Computer Simulation (TOMACS)
ACM SIGSIM Simulation Digest
Model diagnosis using the condition specification: from conceptualization to implementation
WSC '94 Proceedings of the 26th conference on Winter simulation
The methodology roles in the realization of a model development environment
WSC '88 Proceedings of the 20th conference on Winter simulation
The implementation of four conceptual frameworks for simulation modeling in high-level languages
WSC '88 Proceedings of the 20th conference on Winter simulation
Exploring the forms of model diagnosis in a simulation support environment
WSC '87 Proceedings of the 19th conference on Winter simulation
The control and transformation metric: toward the measurement of simulation model complexity
WSC '87 Proceedings of the 19th conference on Winter simulation
Simultaneous events and distributed simulation
WSC' 90 Proceedings of the 22nd conference on Winter simulation
Incorporating support for model execution within the condition specification
Transactions of the Society for Computer Simulation International
Simulation modeling with event graphs
Communications of the ACM
Communications of the ACM
The time and state relationships in simulation modeling
Communications of the ACM - Special issue on simulation modeling and statistical computing
Guarded commands, nondeterminacy and formal derivation of programs
Communications of the ACM
Theory of Modelling and Simulation
Theory of Modelling and Simulation
A tutorial view of simulation model development
WSC '83 Proceedings of the 15th conference on Winter simulation - Volume 1
Model specification and analysis for discrete event simulation
Model specification and analysis for discrete event simulation
Simulation modeling methodology: principles and etiology of decision support
Simulation modeling methodology: principles and etiology of decision support
The art of simulation
Redundancy in model representation: a blessing or a curse?
WSC '96 Proceedings of the 28th conference on Winter simulation
A two-stage modeling and simulation process for web-based modeling and simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Next generation modeling I: RUBE: a customized 2d and 3d modeling framework for simulation
Proceedings of the 35th conference on Winter simulation: driving innovation
Characterizations and relationships of world views
WSC '04 Proceedings of the 36th conference on Winter simulation
Building modeling tools that support verification, validation, and testing for the domain expert
WSC '05 Proceedings of the 37th conference on Winter simulation
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
CS-XML and model understanding
SpringSim '09 Proceedings of the 2009 Spring Simulation Multiconference
CS-XML and model understanding
SpringSim '09 Proceedings of the 2009 Spring Simulation Multiconference
Information models for queueing system simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
A forthcoming useful tool: enhancing understanding of models through analysis
Proceedings of the Winter Simulation Conference
A forthcoming useful tool: enhancing understanding of models through analysis
Proceedings of the Winter Simulation Conference
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Although redundancy in model specification generally has negative connotations, we offer arguments for revising those convictions. Defining “representational redundancy” as the inclusion of any symbols not required to fulfill the study objectives, we cite several sources of redundancy, classified as accidental or intentional, that contribute positively to the model development tasks. Comparative benefits and detriments are discussed briefly. Focusing on the most interesting source of redundancy‐that which is intentionally induced by a modeling methodology—we demonstrate that automated elimination of redundancy can actually improve model execution time. Using four models drawn from the literature that are easily understood, but which represent some differences in size and complexity, the direct graphical representations shows improvements over a base case ranging from 27.3 percent to 68.1 percent in execution time. Further, increasing improvement is realized with increasing model size and complexity. These results are encouraging because they suggest that modeling methodologies with automated model diagnosis can significantly reduce both execution and developments time and cost.