Hybrid Simulation modeling has been grabbing researchers’ attention lately. This article reports on a preliminary review of the literature and investigates the prevalence and utilization of Hybrid Simulation in healthcare. Findings show that combining Discrete-Event Simulation and System Dynamics is the most common approach to developing HS models in healthcare. However, the popularity of combining Agent-Based Simulation with others is on the rise.
The present study explores a simulation model combining system dynamics and discrete-event simulation for an electric vehicle charging system. The model allows for different parameters to be set individually, enabling the exploration of different system and usage scenarios. Multiple simulation runs were performed to analyze the considered energy system over a 1-year period and compare relevant output parameters for different system configurations and system locations.
The aircraft turnaround process consists of "ground handling operations" that are required to set an aircraft ready for its subsequent departure. This work focuses on enhancing the planning and real-time allocation of apron operations that are used to turn around an aircraft between two consecutive flights.
Simulation is one of the most used approaches to analyze semiconductor manufacturing systems. However, most simulation models are designed for single-use applications and study a limited set of problems that are not reusable afterwards. This paper proposes a generic, data-driven simulation model to evaluate and analyze a wide range of problems arising in modern semiconductor manufacturing systems.
This paper introduces a simulation study of interventions to ensure a stable supply of a generic medicine in Norway. A hybrid simulation modeling framework is proposed to evaluate the effect of alternative supply chain shortage interventions in response to various disruptions to support national decision making with respect to preparedness planning and emergency response.
Urban logistics is becoming increasingly important due to the global rise of e-commerce with home deliveries of small but frequent orders from consumers. The introduction of self-collection delivery systems is an innovation for last mile delivery operations in urban areas and brings new benefits. This paper introduces the application of hybrid modeling approach for the self-collection delivery costs optimization and estimation of future demand based on several socio-economic parameters.
Environmental sustainability is among the key concerns of our time. This study uses a multimethod simulation model to assess the impact of different e-grocery fulfillment strategies alongside the entire supply chain on sustainability metrics.
This paper proposes a simulation-based decentralized planning and scheduling approach to improve the performances of a job-shop production system, compliant with a semi-heterarchical Industry 4.0 architecture. To this extent, to face the increasing complexity of such a scenario, a parametric simulation model able to represent a wide number of job-shop systems is introduced.
In many industrial manufacturing companies, energy has become a major cost factor. Energy aspects are included in the decision-making system of production line planning and control to reduce manufacturing costs. For this priority, the simulation of production line processes requires not only the consideration of logistical and technical production factors but also the integration of time-dependent energy flows. A hybrid (multimethod) simulation shows the complex interactions between material flow and energy usage in production close to reality. This paper presents a simulation approach combining System Dynamics, Discrete-Event and Agent-Based Simulation for energy efficiency analysis in production, considering the energy consumption in the context of planning and scheduling operations.