This paper reviews statistical methods for analyzing output data from computer simulations. First, it focuses on the estimation of steady-state system parameters. The estimation techniques include the replication/deletion approach, the regenerative method, the batch means method, and methods based on standardized time series. Second, it reviews recent statistical procedures to find the best system among a set of competing alternatives.

Proceedings of the 2000 winter simulation conference

Modeling and simulation techniques are today extensively used both in industry and science. Parts of larger systems are, however, typically modeled and simulated by different techniques, tools, and algorithms. In addition, experts from different disciplines use various modeling and simulation techniques. Both these facts make it difficult to study coupled heterogeneous systems.Co-simulation is an emerging enabling technique, where global simulation of a coupled system can be achieved by composing the simulations of its parts. Due to its potential and interdisciplinary nature, co-simulation is being studied in different disciplines but with limited sharing of findings.In this survey, we study and survey the state-of-the-art techniques for co-simulation, with the goal of enhancing future research and highlighting the main challenges.To study this broad topic, we start by focusing on discrete-event-based co-simulation, followed by continuous-time-based co-simulation. Finally, we explore the interactions between these two paradigms, in hybrid co-simulation.To survey the current techniques, tools, and research challenges, we systematically classify recently published research literature on co-simulation, and summarize it into a taxonomy. As a result, we identify the need for finding generic approaches for modular, stable, and accurate coupling of simulation units, as well as expressing the adaptations required to ensure that the coupling is correct.

/pdf/co-simulation-a-survey-158xsoh6d5.pdf

Co-Simulation: A Survey

A review of Web-based simulation and supporting tools

Simulation model reuse: definitions, benefits and obstacles

: In modeling and simulation (MS past Department of Defense (DoD) efforts to achieve it have had distinctly mixed success despite the many technological developments that have occurred over the past 5 to 10 years. In reviewing this situation, we have sought to identify key elements for defining a path to future success.

https://www.rand.org/content/dam/rand/pubs/monographs/2004/RAND_MG101.pdf

Improving the Composability of Department of Defense Models and Simulations

We consider the issue of composability as a design principle for simulation. While component based modeling is believed to potentially reduce the complexities of the modeling task, we describe a few of the complexities introduced through composability. We observe that these complexities might tend to offset the benefits of component based modeling on a large scale.

/pdf/observations-on-the-complexity-of-composable-simulation-17b3l44v7d.pdf

Observations on the complexity of composable simulation

http://www.mitre.org/sites/default/files/pdf/investigating_page.pdf

Jeffrey M. Opper

Papers

Observations on the complexity of composable simulation

Investigating the application of web-based simulation principles within the architecture for a next-generation computer generated forces model