Includes bibliographical references.

Article 1. Novel approaches to feasibility determination -- Article 2. Global-local metamodel-assisted stochastic programming via simulation -- Article 3. Application of simulation in healthcare service operations -- Article 4. Green simulation with database monte carlo -- Article 5. Replication of computational results report for "Green simulation with database monte carlo" -- Article 6. Discrete-Event Modeling and Simulation of diffusion processes in multiplex networks.

[Article Title: Novel Approaches to Feasibility Determination / D. Solow, R. Szechtman, and E. Yucesan, p. 1 - 1:25]

Abstract: This article proposes two-stage Bayesian and frequentist procedures for determining whether a number of systems—each characterized by the same number of performance measures—belongs to a set Γ defined by a finite collection of linear inequalities. A system is “in (not in) Γ” if the vector of the means is in (not in) Γ, where the means must be estimated using Monte Carlo simulation.

https://doi.org/10.1145/3426359

[Article Title: Global-local Metamodel-assisted Stochastic Programming via Simulation / W. Xie, Y, Yi, and H. Zheng, p. 2 - 2:34]

Abstract: To integrate strategic, tactical, and operational decisions, stochastic programming has been widely used to guide dynamic decision-making. In this article, we consider complex systems and introduce the global-local metamodel-assisted stochastic programming via simulation that can efficiently employ the simulation resource to iteratively solve for the optimal first- and second-stage decisions.

https://doi.org/10.1145/3411080

[Article Title: Application of Simulation in Healthcare Service Operations: A Review and Research Agenda / S. N. Roy, B. J. Shah, and H. Gajjar, p. 3 - 3:23]

Abstract: The health system is intricate due to its dynamic nature and critical service requirements. The involvement of multiple layers of health service providers quadrupled this complexity and results in a complicated operating environment. Simulation is often considered an apt technique to model and study complex systems in the literature. The popularity of simulation in the healthcare domain had only accelerated with time and resulted in a large number of articles intended to solve myriad healthcare problems.

https://doi.org/10.1145/3427753

[Article Title: Green Simulation with Database Monte Carlo / M. Feng and J. Staum, p. 4 - 4:26]

Abstract: In a setting in which experiments are performed repeatedly with the same simulation model, green simulation means reusing outputs from previous experiments to answer the question currently being asked of the model. In this article, we address the setting in which experiments are run to answer questions quickly, with a time limit providing a fixed computational budget, and then idle time is available for further experimentation before the next question is asked. The general strategy is database Monte Carlo for green simulation: the output of experiments is stored in a database and used to improve the computational efficiency of future experiments.

https://doi.org/10.1145/3429336

[Article Title: Replication of Computational Results Report for “Green Simulation with Database Monte Carlo” / A. Pellegrini, p. 5 - 5:4]

Abstract: This article presents the reproducibility results associated with the article “Green Simulation with Database Monte Carlo,” by Mingbin Feng and Jeremy Staum. The authors have uploaded their artifact to Zenodo, which ensures a long-term retention of the artifact. The artifact, which is based on a set of R scripts, allows to easily regenerate data for the figures and the tables, it completes successfully, and allows to reproduce all the experimental results in the article. The article can thus receive the Artifacts Available, the Artifacts Evaluated—Functional, and the Results Reproduced badges.

https://doi.org/10.1145/3426823

[Article Title: Discrete-Event Modeling and Simulation of Diffusion Processes in Multiplex Networks / C. Ruiz-Martin, G. Wainer, and A. Lopez-Paredes, p. 6 - 6:32]

Abstract: A variety of phenomena (such as the spread of diseases, pollution in rivers, etc.) can be studied as diffusion processes over networks (i.e., the diffusion of the phenomenon over a set of interconnected entities). This research introduces a method to study such diffusion processes in multiplex dynamic networks.

https://doi.org/10.1145/3434490