A multi-agent-based real-time truck scheduling model for cross-docking problems with single inbound and outbound doors

Cross-docking is a warehousing method that allows goods to move quickly from inbound suppliers directly to outbound customers, minimizing storage time. This study focuses on developing a real-time multi-agent truck scheduling model to optimize the process of cross-docking in warehouses, aiming for quick and efficient synchronization of incoming and outgoing freight.

Simulated-Based Analysis of Recovery Actions under Vendor-Managed Inventory Amid Black Swan Disruptions in the Semiconductor Industry: a Case Study from Infineon Technologies Ag

Through simulation modeling, this research highlighted the interactions of key system parameters in a disruption phase under different scenarios. A multi-period, multi-echelon serial supply chain was studied with agent-based and discrete-event simulation.

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.