Urban logistics is becoming increasingly important due to the global rise of e-commerce with home deliveries of small but frequent orders from consumers. The introduction of self-collection delivery systems is an innovation for last mile delivery operations in urban areas and brings new benefits. This paper introduces the application of hybrid modeling approach for the self-collection delivery costs optimization and estimation of future demand based on several socio-economic parameters.
This paper provides an overview for agent-based modeling and simulation tutorial that covers key concepts, the modeling process and implementation using AgentPy - an open-source library for ABM development in Python.
Physical distancing is recommended as the most efficient strategy for defending individuals from long-term global pandemics. It lowers the risk of community spreading, especially for indoor spaces. This paper aims to model physical-distancing behaviors in an educational facility, using agent-based simulation, and evaluate the impact of measures (e.g., controlling classroom capacity, breaktime scheduling) on physical distance violation risks.
In the last few years, there has been an increase in accidents involving pedestrians in the Mexico City subway. A proposed solution is to install physical barriers between platforms and tracks. The research team built an agent-based pedestrian flow simulation model to prove the effectiveness of such barriers.
The Regional Biorefinery Impact Assessment (REBIA) simulation tool allows easy impact assessment for waste stream sources and biorefinery locations. REBIA is based on a supply chain model, where waste is transported via the road network from its various sources to the biorefinery.
A proof-of-concept model demonstrates how the development of a circular economy can impact energy use and the environment. The aim is to consider several aspects that contribute to a thriving community: energy requirements, jobs, tourism, supply lines, and the impact of waste on water resources and the land (landfill).
In this paper, the researchers study the operations of an imaginary coffee shop with a focus on the barista’s actions. They also show how the sequence of actions affects the overall performance of the coffee shop by using reinforcement learning and simulation as its policy training environment. This model acts as a guiding example that shows the ease of applying RL in AnyLogic models using the Pathmind Library.
The study of friendship formation is fundamental to the study of human beings. In this paper, the research team presents an agent-based model of friendship networks grounded in the existing empirical research literature on friendship formation. The goal is to better understand what mechanisms might be influential in the formation of friendships as well as how such modeling might inform (and potentially advance) our understanding of existing empirical work.
This study uses agent-based modeling as a proof of concept tool to investigate the applicability of the green performance bond framework to provide insights into the potential benefits of implementing it within the construction industry. The research also evaluates its feasibility and effectiveness in discouraging opportunistic bidding behaviors.