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Editorial Scope and Charter
The ACM Transactions on Modeling and Computer Simulation (TOMACS) provides a single archival source for the publication of high-quality research and developmental results in computer simulation. The subjects of emphasis are discrete event simulation, combined discrete and continuous simulation, as well as Monte Carlo methods. Papers in continuous simulation will also receive serious consideration if their contributions to modeling and simulation in general are substantial. The use of simulation techniques is pervasive, extending to virtually all the sciences. TOMACS serves to enhance the understanding, improve the practice, and increase the utilization of computer simulation. Submissions should contribute to the realization of these objectives, and papers treating applications should stress their contributions vis-a-vis these objectives. The scope of papers published in TOMACS includes, but is not limited to, the following general areas: Advanced Applications: Novel techniques and tools for simulating specific complex systems such as those arising in communications, computer, health care, manufacturing and transportation systems. Distributed Simulation: The interoperation of diverse, geographically distributed simulations for training, test and evaluation purposes, often operating with real-time constraints and with humans, hardware, and software in the loop. Model Execution: Development and analysis of algorithms to improve the execution efficiency of discrete event simulation programs, especially on multiple computer platforms. Modeling Methodology: New techniques, theory and tools for modeling general systems, including simulation languages and model development systems, object-oriented modeling, hybrid and hierarchical modeling, metamodeling and visual modeling, as well as the interaction of simulation with decision support, artificial intelligence and virtual reality. Random Numbers and Objects: Modeling and Generation: Random number generators and testing, low-discrepancy sequences, random variate transformations, stochastic process and random object generators, statistical distribution fitting and data modeling. Simulation Analysis: Analysis of the stochastic nature of simulation output and algorithms, including simulation-based optimization and search, sensitivity analysis, variance reduction techniques and Markov chain Monte Carlo,
Verification, Validation, and Accreditation:
The assessment of accuracy of simulation models.
More detailed descriptions of these areas TOMACS welcomes the following types of contributions:
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