Academic articles

Klein Mechanisch Werkplaats Eindhoven (KMWE) is a precision manufacturing company situated in the Netherlands and recently relocated to a new location known as the 'Brainport Industries Campus' (BIC). This move allowed KMWE to improve the performance of its manufacturing facility by investing in vertical automated storage and retrieval systems (AS/RSs). However, these decisions needed to be made under input uncertainties since the move to BIC and modernization of existing equipment would cause changes in operating parameters inside the facility.

In this study, the researchers show how hybrid simulation modelling was used in production planning optimization, in particular to assess the impact of input uncertainties (such as operator productivity, vertical storage height) on the throughput performance of TSC.

This paper presents transportation network analysis results based on data from an agent-based simulation study. The research is aimed at establishing whether a fleet of electric vans with different charging options can match the performance of a diesel fleet. The researchers describe a base model imitating the operations of a real-world retailer using agents. They then introduce electric vehicles and charging hubs into their model. After that, they evaluate how the use of electric vehicles, charging power, and charging hubs influence the retailer’s operations. The simulation experiment suggests that, though they are useful, technological interventions alone are not sufficient to match the performance of a diesel fleet. Hence, reorganization of the urban delivery system is required in order to reduce carbon emissions significantly.

Schelling’s social segregation model has been extensively used for human behavior analysis and studied over the years. A major implication of the model is that individual preferences of similarity lead to a collective segregation behavior. Schelling used Agent-Based Modeling (ABM) with uni-dimensional agents. In reality, people are multidimensional. This raises the question of whether multi-dimensionality can boost stability or reduce segregation in society.

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.