The job-shop scheduling problem was considered with sequence-dependent setup times and preventive maintenance constraints. A hybrid model combining discrete-event simulation and an optimization algorithm in Python was applied to simulate the production process and solve the job-shop problem.
An animated, data-driven and data-generated simulation model was developed to support the development of both the design and configuration methodology and operational control strategy of Shuttle-based Storage and Retrieval Systems.
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.
A novel data trading approach was presented in this paper – one where trading was controlled by seller preferences. The approach followed the principles of seller’s rights protection and control over the data sharing available in a community of users. A hybrid approach was shown to combine market and technology simulations and enable system developers to test robust future scenarios.
In this study, researchers investigated the process of orthopedic treatment in an Australian health service, from the point of referral to surgical intervention. In a number of cases, surgical intervention could be avoided through participation in community-based rehabilitation programs.
Blood supply chains are an essential element of healthcare systems. Simulation provides the means to test out digital innovations for blood supply chains regarding their operational efficiency and expected costs.
A discrete event simulation model was developed for a network of eight major intensive care units (ICUs) as well as high-acuity units (HAUs) in British Columbia, Canada. The simulation model will be used to develop strategies for managing the combined impacts of COVID-19 and seasonal influenza without the need for extensive public health interventions to limit transmission.
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.
Sustainability assessment is a multi-faceted, dynamic, and complex paradigm in the context of buildings with several social, economic, and environmental interactions. Currently, the building sector lacks a sustainability evaluation and benchmarking mechanism. So, a system-thinking approach that can solve these challenges due to its ability to evaluate complex systems was developed.
Demands for health care are becoming overwhelming for healthcare systems around the world regarding the availability of resources, particularly in emergency departments (EDs). This paper provides a case study of the Uppsala University Hospital, where a data-driven simulation model was designed to examine the current state of the patient flow and to investigate potential logistics solutions for improving that flow through a novel strategy.