ACM Transactions on Modeling and Computer Simulation (TOMACS) provides a single archival source for the publication of high-quality research and developmental results referring to all phases of the modeling and simulation life cycle. The subjects of emphasis are discrete event simulation, combined discrete and continuous simulation, as well as Monte Carlo methods.

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-á-vis these objectives.

Scope

The scope of papers published in TOMACS includes, but is not limited to, the following general areas:

        Modeling Methodology: modeling languages, model reuse, component-based approaches, agent-based approaches, multi-formalism modeling, multi-abstraction modeling, multi-view modeling, hierarchical, multi-level modeling, meta/type  modeling and visual modeling, composition and refinement of models, hybrid modeling.

        Model Execution: development and analysis of algorithms and data structures, approximative algorithms, hybrid algorithms, parallel algorithms, including GPU based approaches, distributed simulation, grid-based and cloud-based execution, inter-operation of simulation systems, distributed simulations for training, test and evaluation purposes, data driven simulation.

        Random numbers and objects: random number generators and testing, low-discrepancy sequences, random variate transformations, stochastic process and random object generators, statistical distribution fitting and data modeling.

        Experiment design and simulation analysis: analysis of the stochastic nature of simulation output and algorithms, including rare event simulation, meta/surrogate-modeling, simulation-based optimization and search, sensitivity analysis, uncertainty quantification, variance reduction techniques and Markov chain Monte Carlo approaches.

        Support for conducting simulation experiments and simulation studies:  workflows, domain-specific languages for experiment support, planning, model-based approaches, methods for enhancing reproducibility and provenance.

        Verification, validation, and accreditation of models: detailed studies, workflow-based support, addressing questions of provenance, statistical model checking, reproducibility of simulation results

        Interplay between other areas of computer science and simulation: simulation for decision support, workflows, artificial intelligence, machine learning, virtual reality, big data, service-oriented approaches, grid-computing, visual analytics, probabilistic programming.

        Advanced Applications: novel techniques and tools for simulating specific complex systems such as those arising in communication networks, computer science, cyber physical systems, health care, manufacturing, social science, systems biology, systems medicine, transportation systems.

This journal is published on a quarterly basis.