Academic articles

Agent-Based Learning Environment for Survey Research


Survey-based research methodology is commonly used in various disciplines, ranging from social sciences to healthcare. However, it is difficult to provide real-world experience of survey sampling methodologies to students and novice researchers. In this paper, the researchers proposed the development of a virtual learning environment based on agent-based modeling to help learn about different aspects and challenges of survey-based research.

System-Level Simulation of Maritime Traffic in Northern Baltic Sea


Maritime traffic in winter in the Baltic Sea (particularly the northern part) is challenged by heavy ice formation. This work presented an integration of ice characteristics, operational-level details of ships, and system-level details such as traffic flows and icebreaker scheduling through a simulation framework.

Simulating Prosumer Data Trading: Testing a Blockchain Smart Contract Based Control


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.

Agent-Based Modeling and Simulation of Multidimensional Impacts of Construction Labor Productivity Factors


Despite numerous attempts to quantify the impacts of factors influencing productivity in the construction industry, such factors are still perceived as static and independent, resulting in unrealistic productivity estimates. Two generic agent-based models were built to simulate the outcomes of a project through varying levels of detail, each investigating a certain set of impacts. Findings proved the accuracy of the proposed comprehensive approach in estimating durations compared to planned durations and to those obtained from the traditional approach.

A Simulation-Optimization Model for Automated Parcel Lockers Network Design in Urban Scenarios in Pamplona (Spain), Zakopane, and Krakow (Poland)


The constant rise of e-commerce coupled with extremely fast deliveries is a significant contributor to saturate city centers’ mobility. To address this issue, the development of a convenient Automated Parcel Lockers (APLs) network improves last-mile distribution by reducing the number of transportation vehicles, the distances driven, and the delivery stops. An agent-based model was implemented in the current paper to forecast parcel demand placed on APLs based on socio-economic factors.

An Agent-Based Simulation Model to Mitigate the Bullwhip Effect via Information Sharing and Risk Pooling


The bullwhip effect, a phenomenon of progressively larger distortion of demands across a supply chain, can cause chaos and disorder with amplified supply and demand misalignment. An agent-based simulation model was developed to evaluate how risk pooling and information sharing between distinct entities in a supply chain can reduce the bullwhip effects. In agent-based paradigm different components of a system were described as agents which interact with each other in an environment.