Academic articles

Electric Vehicles: The Driving Power for Energy Transition - Blockchain-based Decentralised Energy Trading


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.

Simulation of epidemic trends for a new coronavirus under effective control measures


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.

Building a Demographic Simulator to Model a Refugee Influx and Its Impact on Demographic Structure


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.

Coal Lading Port Optimization with AnyLogic


This case study considers the simulation of a coal lading port in order to determine which extensions are needed based on expected capacity demands. These investigations are executed in cooperation with the German company TAKRAF GmbH which planned and constructed the considered port. Processes at this port are influenced by uncertainties, like the provided coal mix from mines and transportation times from mines to the port or meteorological disturbances. The maximum capacity of the current state of the port was determined at a first step. Components which mainly limit the maximum outcome were identified. Based on these results, different extension scenarios were evaluated.

Agent Based Simulation Marketing Mix Model for Budget Management in Cosmetic Industry


A worldwide leading company in the cosmetic industry was dealing with great challenges regarding adapting its positioning strategy to the dynamically changing behaviors of the market. The company needed to decide where to invest its marketing budget to optimize its revenue and was using different traditional marketing mix models without any success. A marketing mix model was developed using agent-based modeling to predict the market’s reaction to a given distribution of a certain budget among the different touchpoints available. This innovative model uses market information and consumer information collected from surveys to estimate the company’s sales, level of awareness and level of consideration given its distributed investment. The tool was implemented as part of the marketing plan decision making process, providing the ability to test different scenarios and generate quantitative analysis of its results.

Emergency Management Simulator for Modeling Crowd Behaviour Under Fire and Toxic Gas Expansion


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.

Simulation-based Evaluation of Urban Consolidation Centers Considering Urban Access Regulations


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.

Agent-based Modeling for Casualty Rate Assessment of Large Event Active Shooter Incidents


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.

Dynamic Behavioural Modeling, Simulation and Analysis of Household Water Consumption in an Urban Area: a Hybrid Approach


Pakistan is rapidly becoming a water stressed country, thus affecting people’s well-being. Authorities are faced with making drastic water conservation policies toward achieving effective management of available water resources and efficient water supply delivery coupled with responsible demand side management. Due to the lack of modern water metering in Pakistan, water consumption is not being accurately monitored. To achieve this goal, we propose a hybrid modeling and simulation framework, consisting of Agent-Based Modeling (ABM) paradigm that deals with the behavior and characteristics of individuals and System Dynamics(SD) paradigm that accounts for water flow dynamics. Our approach provides dual-resolution expressiveness suitable for replicating real-world urban infrastructure scenarios. The key objective of the research is to assist authorities to understand and forecast short-term and long-term water consumption through examining varying patterns of water consumption in different climates and thus improving demand side water usage dynamically subject to water supply availability.

Simulating Passenger’s Shopping Behavior at Airport With a Conceptual Agent-based Model


Airport retail revenue has long been recognized as a critical revenue stream to ensure an airport’s financial sustainability and stability. However, there is a lack of simulation model on how airport terminal could be better designed to facilitate this vital revenue stream. This paper presents a conceptual agent-based simulation model on passengers shopping behavior in the airport context. This model attempts to investigate the relationship between terminal design and retail performance through different scenarios studies. Results show that finger pier terminal shape can have a negative impact on retail revenue if shops are decentralized. Terminal with centralized shopping areas also performed better than a terminal with decentralized shopping area. Future research directions were proposed at the end to improve the existing simulation model with the aim of making it an essential evaluation tool for future terminal design.