Academic articles

Today, the demand for higher building security has grown considerably, especially for evacuations in cases of fire, chemical, biological and radiological incidents or terrorist attacks. However, the planning of relevant safety measures for new buildings or the evaluation of existing buildings requires reliable information for a farsighted decision making. Simulation tools that can realistically map the spread of fire, smoke and pollutants in buildings already exist, but they are conventionally based on 1D or single zone static models which allows only rough estimation of the safety. As a result, decision making is typically very conservative and does not consider the consequences of possible intervening measures. Accordingly, safety and rescue operation plans are subject to a high degree of uncertainty with regard to their effects. Therefore, more and more often realistic 3D CFD simulations are being asked for, which is becoming possible with the continuous growth of computer power. However, such simulations are still very costly and time-consuming, especially with regard to the involved modelling efforts.

Due to the significant rise in environmental awareness of companies and customers for the past few years, research on how to optimize business with respect to carbon dioxide (CO2) emission has gained more attention and importance. This paper investigates how flexibility can be an enabler for CO2 reduction over a global production network especially in a capital intensive and high volatile market like the semiconductor one. We tested this hypothesis with discrete-event simulation experiments based on a case study obtained from a semiconductor company. The study indicates that global supply chains (SCs), like those in the semiconductor industry, should be equipped with a certain level of flexibility to cope with demand volatility if the CO2 burden due to transportation is low compared to those due to manufacturing. This flexibility provides ecological benefits to companies in reducing the carbon footprint of their products.

We consider the dynamic price and lead time quotation problem in the practical context of the semiconductor industry. Our model considers an inventory decoupled supply chain and accounts for a limited capacity, stochastic demand and processing times and quote-sensitive customers. We focus on performance evaluation under two decision making strategies. The first is lead time based pricing (LTBP). It follows a sequential approach where the firm decides first on the lead time quote (manufacturing) and then quotes the price under the given lead time (marketing). The second strategy suggests determining the lead time and the price quotes simultaneously. From the practical view-point, it is interesting to first understand the system performance under LTBP and then look for the ways to realize it. Based on our numerical results, we elaborate on the effect of LTBP on the key performance indicators and discuss conditions for close performance to a simultaneous decision strategy.

Snowplow operations are critical for public safety and economic success in countries where difficult driving conditions occur in winter. Specifically, the salt supply ensuring good driving conditions is a crucial factor. In this paper, the strategic supply chain design of a winter service provider in Austria is investigated. Two research directions on the influence of bigger and fewer salt silos per depot and the logistic costs for a unique summer salt purchasing strategy are addressed applying two independent solution approaches. On the same data basis, a simulation model is developed and a mixed integer linear problem is applied to answer the respective research questions.

This paper focuses on the influence of different order placement behavior of users on the allocation of common resources inside a multi-user warehouse. Furthermore, the interdependencies between one user’s resource usage on other users’ order processing time is investigated. For this objective, an agent-based simulation model has been developed, depicting a rectangular warehouse with two users and one order picker. Results show that different order placement behavior and resource usage of one user have a strong influence on order processing times of other users. Furthermore, by simulating uneven order placement by one user, it can be shown that peaks in order demand influence other user’s order processing times with a delay of up to two hours after the peak occurred. Thus, the results highlight the need for coordinated order placement of partners inside a multi-user warehouse.

This paper presents a joint simulation project in the area of railway fleet maintenance optimization. A simulation model was developed to understand and visualize the complex interaction in a railway system comprising rolling stock, depots, and maintenance guidelines. In many cases, requirements on such a system come from different sides, such as fleet operation (timetables and availability), maintenance engineering (maintenance regime), and depot management (depot restrictions). The paper describes the domain-specific challenge, the model for planned maintenance optimization, the implemented scheduling algorithm, and resulting insights. It, furthermore, describes how the model can be used for a variety of different use cases all along a railway project: from sizing to forecast and performance analysis and from initial tender theory check to operational risk analysis and preventive maintenance optimization. Two real-world use cases are presented: West Coast Main Line and TransPennine Express, both in the United Kingdom.

The negative effects of urban freight transports, such as air quality problems, road congestion, and noise emissions lead in many cities to major difficulties. A widely studied measure to reduce these negative effects are Urban Consolidation Centers (UCCs), which aim to bundle freight flows to reduce the number of urban freight transports. However, many projects showed that the additional costs of UCCs often made it unattractive for carriers to participate in such schemes. This paper presents an agent-based simulation to assess the impact of urban access regulations on the cost-attractiveness of UCCs for carriers. A case study inspired by the Frankfurt Rhine-Main area is presented to compare deliveries of a group of carriers with and without a Urban Consolidation Center under various urban access scenarios. The simulation shows that regulations increase the cost-attractiveness of UCCs for carriers to varying degrees while increasing the overall traffic volume.

The 1999 Columbine attack changed police response to the active shooter incidents (ASI) by the public and first responder’s tactics and training. With FBI data suggesting ASI events increasing, this study offers an AnyLogic models to understand mitigation actions such as Run.Hide.Fight. Our model represents a general densely populated area, such as public transportation terminal or indoor arena. Model agents include civilians, police, and shooter agents interact with the following parameters: civilian evacuation time, the response of police, firearm discharge by the shooter and police. The casualty rates vary from 85 to 1 causalities when the shooter’s rate of discharge was 1 to 60 seconds, respectively. The model as developed was shown to provide a method to evaluate and compare actions such as adequacy of training, introduction of technology into public buildings and the general design of public spaces to reduce the impact of ASI events.

Recent US healthcare reform debates have triggered substantial discussion on how best to improve access to insurance. Colorectal cancer (CRC) is an example of a largely preventable condition, if access to and use of healthcare is increased. Early and ongoing screening and intervention can identify and remove polyps before they become cancerous. We present the development of an individual-based discrete-event simulation model to estimate the impact of insurance expansion scenarios on CRC screening, incidence, mortality, and costs. A national repeated cross-sectional survey was used to estimate which individuals obtained insurance in North Carolina (NC) after the Affordable Care Act (ACA). The potential impact of expanding the state’s Medicaid program is tested and compared to no insurance reform and the ACA without Medicaid expansion. The model integrates a census-based synthetic population, national data, claims based statistical models, and a natural history module in which simulated polyps and cancer progress.

This study is designed to demonstrate the benefit of using a single simulation model in order to analyze operations at two distinct, but related, pediatric orthopedic outpatient clinics in Massachusetts. A simulation model with a built-in dashboard is constructed for the clinics using AnyLogic. The constructed simulation model has been proven to be a useful tool in anticipating the effects of changes in system features such as patient volume, provider team mix, and exam room assignment policies. With the development of a flexible simulation model the ultimate goal is to assist clinic managers in their efforts to reduce patient waiting time and lengths of stay in the two distinct orthopedic clinics.