SIMULATION: Transactions of The Society for Modeling and Simulation International

de Mooij, Jan; Bhattacharya, Parantapa; Dell’Anna, Davide; Dastani, Mehdi; Logan, Brian; Swarup, Samarth

doi: 10.1177/00375497231184898pmid: N/A

Agent-based modeling is increasingly being used in computational epidemiology to characterize important behavioral dimensions, such as the heterogeneity of the individual responses to interventions, when studying the spread of a disease. Existing agent-based simulation frameworks and platforms currently fall in one of two categories: those that can simulate millions of individuals with simple behaviors (e.g., based on simple state machines), and those that consider more complex and social behaviors (e.g., agents that act according to their own agenda and preferences, and deliberate about norm compliance) but, due to the computational complexity of reasoning involved, have limited scalability. In this paper, we present a novel framework that enables large-scale distributed epidemic simulations with complex behaving social agents whose decisions are based on a variety of concepts and internal attitudes such as sense, knowledge, preferences, norms, and plans. The proposed framework supports simulations with millions of such agents that can individually deliberate about their own knowledge, goals, and preferences, and can adapt their behavior based on other agents’ behaviors and on their attitude toward complying with norms. We showcase the applicability and scalability of the proposed framework by developing a model of the spread of COVID-19 in the US state of Virginia. Results illustrate that the framework can be effectively employed to simulate disease spreading with millions of complex behaving agents and investigate behavioral interventions over a period of time of months.

Alam, MD Jahedul; Pinchemel, Alexandre; Habib, Muhammad Ahsanul; Caetano, Mauro

doi: 10.1177/00375497231185358pmid: N/A

This study develops a framework of pedestrian evacuation microsimulation modeling that considers pedestrians’ social-physiological behavior in assessing an airport evacuation. The study implements social force model within a simulation platform enabling the articulation of stochastic pedestrian walking behavior realistically and reliably. It performs a sensitivity analysis of pedestrian behavior parameters to identify the candidate parameters required to capture pedestrian behavior under different levels of panic conditions. The study considers the case study of the Ottawa International Airport and tests and evaluates contrasting evacuation scenarios under low panic, medium panic, and high panic situations. Results indicate that under the low panic evacuation scenario, the pedestrians yield their movements with an increase in network bottleneck, potentially exhibit cooperative behavior, and control their speed with the rise of crowd density. On the contrary, individuals in high panic evacuation scenarios exhibit aggressive behavior indicated by their average speed, which is approximately 1.15 and 3.5 times the average compared with medium panic and low panic evacuation scenarios, respectively. Results suggest that it takes 5.38 min to evacuate 1300 passengers under high panic conditions compared with 9.75 min for a low panic evacuation scenario. However, in the case of a high panic evacuation scenario, the average speed keeps increasing even with the increase in crowd density. This framework can develop and evaluate strategies for safely evacuating the airport in the case of an emergency.

Chen, Jinchao; Zhang, Haoran; He, Ruimeng; Du, Chenglie; Cui, Jie; Sun, Xiaoying

doi: 10.1177/00375497231189285pmid: N/A

In recent years, the number of invested resources adopted in experiments of embedded applications dropped significantly as many simulation technologies are widely used. However, the efficiency of simulations is seriously influenced by some expensive and difficult-to-obtain devices. It is urgent and of great significance to build a universal simulation platform for embedded applications on general-purpose operating systems with an objective of improving the efficiency and effectiveness of system development and implementation. Since virtualization technology can greatly enhance the simulation efficiency by providing virtual models to simulate the behaviors of real devices, this paper designs and realizes a real-time simulation platform on general-purpose operating systems with the virtualization technology such that embedded applications would be correctly and efficiently debugged and tested on the general-purpose operating systems. The proposed simulation platform contains four layers named hardware resource, virtualization, virtual runtime environment, and interface adaptation, allowing dynamic debugging and testing of embedded applications without requiring the actual presence of real devices. Experiments are conducted to verify the functionalities of the proposed simulation platform, and results demonstrate that the proposed simulation platform can meet the real-time and high reliability requirements of embedded applications.

Özkan, Emin Deniz; Nas, Selçuk

doi: 10.1177/00375497231189749pmid: N/A

In the face of developments in maritime transportation due to globalization, ports are tending toward new tugboat investments in order to respond to the increasing demand. Due to the high costs of tugboats, organizations may face high investment costs. It is important to determine the most suitable number of tugboats, considering the variables in a port area where towage services will be provided. In this study, a simulation model was developed to determine sufficient tugboat allocation according to some variables in ports. The simulation model was subjected to various experiments, and statistical analyses of the obtained results were performed. The relationships between the variables affecting the level of towage service were revealed.

Damla Gönül-Sezer, Eylül; Demirel, Duygun Fatih

doi: 10.1177/00375497231192108pmid: N/A

The relationship between military expenditures and economic productivity has taken the attention of many researchers and there exist an important number of studies approaching the topic through several techniques. However, there is no consensus among the scholars whether military expenditures trigger economic growth, productivity, and other macroeconomic indicators. Such arguments are mainly due to unclear results obtained from the existing studies, in which the complex relationships between military expenditures and macroeconomics are not fully incorporated. Considering the bidirectional and nonlinear relationships among macroeconomic indicators and complex feedback mechanisms, a system dynamics (SD) model for examining the impacts of military expenditures on economic productivity in Turkey is proposed. The proposed SD model aims to reflect the complex environment surrounding the military spending–economic productivity nexus and to analyze the feedback structures that lead to miscellaneous consequences with delays. A stock–flow model is developed to represent the complex nonlinear relationships and causalities between the variables. Data from SIPRI, the World Bank, and several local statistical sources covering the years 2009–2018 are utilized to simulate the existing case, warfare in neighbors, economic shrinkage scenarios, and the combination of the latter two. The results obtained from the scenarios suggest that short fixes such as importing military products instead of national investments give rise to chronic issues like continual dependence on foreign supply, hence, leading to decrease in overall economic growth. To the best of our knowledge, this is the first attempt to integrate SD methodology with military expenditure and economic productivity analysis.