Strategic management simulation is an increasing field of practice mostly driven by the big consulting firms. While System Dynamics (SD) is a widely used simulation method in given its advantage on global aggregates and deterministic model, hybrid modelling can achieve similar popularity. This paper presents some suggestions on how to use hybrid modelling with AnyLogic strategic management software.
Evolution of technology and the complexity of the medical system have contributed to the increasing interest in telemedicine. The purpose of this paper is to present a discrete event simulation model of the teledermatology process using the tool TelDerm. The logic of the simulation describes the telemedicine work flow from the detection of the problem to its resolution. The scenarios reflect different changes in the flow in order to quantify the impact of telemedicine on the healthcare system. Several key performance indicators measure medical and administrative workload variations for all human resources involved. In addition, we assess the impact on the patient’s journey through the process.
The ever-increasing importance of airport retail has encouraged both industry and academics to look into ways to increase airport retail revenue. Despite the growing interest in this topic, there is a lack of passenger shopping behavioral model. This paper aims to fill this gap and enhance our understanding of how the location of the shop affects passenger decision. This paper first investigates the possible passenger shopping behavioral model through an exploratory Eye-tracking exercise. Data was collected to calibrate and validate the behavioral model through the use of an Agent-Based Simulation Model.
Emergency Room (Emergency Department) overcrowding is a pervasive problem worldwide, which impacts both performance and safety. Staff are required to react and adapt to changes in demand in real-time, while continuing to treat patients.
This paper employs a case study to propose a hybrid application of discrete-event simulation (DES) and time-series forecasting across multiple centers in an urgent care network as one of the emergency room overcrowding solutions. It uses seasonal ARIMA time-series forecasting to predict overcrowding in a near-future moving-window (1-4 hours) using data downloaded from a digital platform (NHSquicker). NHSquicker delivers real-time wait-times from multiple centers of urgent care in the South-West of England. Alongside historical distributions, this data loads the operational state of a real-time discrete-event simulation model at initialization.
A steel stock yard for storing the purchased steel plates is the first step of shipbuilding. It is also space where sorting is performed to supply proper steel plates to the cutting process at the right time. Usually, it is difficult to supply all steel plates from one steelwork. Therefore, the deviation of the duration of plate procurement increases in the process of supplying steel plates from multiple steelworks. The changes in production plans from this deviation affect the duration for which the steel plates stay in the stock yard.
To address this problem, shipbuilding yards are researching on efficient management of steel plates in a limited space. In this study, a steel stock yard simulation model was constructed using discrete event simulation.
Aircraft ground handling involves all services to an aircraft (e.g. passenger boarding/disembarking, re-fuelling, deicing) between its arrival and immediately following departure. The aircraft, parked at its stand, witnesses a number of service providers move around it to perform their duties. Inter-dependencies among service providers abound, and knock-on effects at disrupted times are rife. Coordination from the side of the airport operator is difficult.
The research team proposes a tactical robust scheme by which ground handlers and the airport operator cooperate, although indirectly, in the development of plans for the next day that are less likely to be impacted by at least the more frequent operational disruptions. The scheme is based on a simheuristic approach which integrates ad-hoc heuristics with a hybrid simulation model (agent-based/discrete-event).
There has been an increased interest in resilient supplier selection in recent years, much of it focusing on forecasting the disruption probabilities. The results of this study advance our understanding about how and when machine learning and simulation can be combined to create digital supply chain twins, and through these twins improve resilience. The proposed data-driven decision-making model for resilient supplier selection can be further exploited for design of risk mitigation strategies in supply chain disruption management models, redesigning the supplier base or investing in most important and risky suppliers.
The purpose of this research is to investigate how electric vehicles can promote energy transition and how blockchain can facilitate the decentralisation of future energy systems.
With the slow but steady rollout of smart meters and advancements in internet of things (IoT) technology, and with the help of agent-based modeling, the results from this study will prove the worth of blockchain’s inclusion in the smart grids of the future.
In December 2019, there was a case of viral pneumonia in Wuhan. After confirming that the pathogen of this disease is a new coronavirus, the World Health Organization (WHO) confirmed and named it 2019-nCoV. The pneumonia caused by this pathogen infection is called a novel corona virus pneumonia.
To better understand the mode of transmission of 2019-nCoV among the population and the effects of control measures, the study was conducted using agent-based modeling (ABM) to simulate an interactive environment over a certain space-time range. The study simulates the trend of 2019-nCoV infection at different levels of close contact in order to provide relevant information and references.
Many developed countries of the world such as Japan, Korea, Singapore, Germany etc., are facing the issue of decreasing birth rates and increasing aged populations. One of the potential solutions for this problem is liberal immigration and refugee laws. Korea has stringent immigration laws and most of the immigration into the country is temporary in nature. However, we have witnessed exodus from Middle East countries to many European countries. Such a phenomenon could have lasting impacts on the host country. Following this cue, we built a demographic simulator for modeling the rapid influx of people seeking refuge in Korea. In this particular simulation test case, we observed the change in demographic distribution of Korea.