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My research is focused on the use of ABM in logistics activities
He is an experienced Lecturer with a demonstrated history of working in the education management industry. He was skilled in Agent-based Modeling and Simulation, Competency Assessing and Fundamental Supply Chain Management. Strong research background and analyst with a Master’s degree focused in Logistics and Supply Chain Management from Institut Teknologi Sepuluh Nopember Surabaya and Certified Supply Chain Analyst from ISCEA International.
My research focused on pricing strategy and its impact on Supply Chain (SC) using the Agent-Based Modeling and Simulation (ABMS) approach. Currently, I’m working on an ABMS model to analyze the impact of SC Coordination on SC performance when intelligent retailers may offer price discounts based on the market’s states using Q-learning algorithm.
The main research area is operation research in logistics with a focus on logistic cluster development and innovative technology usage. Due to mathematical background, Gružauskas focuses on quantitative analysis by conducting simulations, stochastic and dynamic models and other analytical approaches to amplify the developed theories. Gružauskas also is working as a freelance data analyst with a focus on statistical analysis, web scraping and machine learning.
My academic interests involve public choice and the development of social norms for cooperation in the marketplace and the behavior of voting blocks. Recent work looks at the emergence of property rights “norms” among zero intelligence agents in an evolutionary context, and the dynamics of legislative party creation in an environment of stochastically voting voters.
I develop simulation tools for generating what-if scenarios for decision making. I predominantly use Agent-Based Modelling (ABM) technique as most of my simulations model complex systems. In some cases, I have extended existing tools with modifications to model the given system. Although the tools are meant for research purposes, I have followed industry friendly delivery mechanisms, such as unit-tests, automated builds and delivery on cloud platforms.
I work in the field of complex adaptive systems, specializing in multi-agent systems, simulation, machine learning, collective intelligence, self-organization, and self-adaptation. I am interested in contributing to innovative projects and research in these domains.
My experience spans across multiple large-scale international research projects in areas such as green urban logistics, blockchain for nuclear applications, autonomous robotics systems and simulation of biological neural networks.
I am an Associate Professor of Data Analytics at Trinity Business School, Trinity College Dublin, The University of Dublin and a Senior Fellow of the Higher Education Academy. I was the Director of Postgraduate Teaching at the Department of Management Science, Lancaster University Management School overseeing MSc programmes in Business Analytics, Management Science and Marketing Analytics, Logistics and Supply Chain Management, e-Business and Innovation, and Project Management.
My research interests lie in the areas of predictive analytics using simulation. I am particularly interested in simulation modelling methodology (symbiotic simulation, hybrid modelling, agent-based simulation, discrete-event simulation) with applications in operations and supply chain management (e.g. hospital, manufacturing, transportation, warehouse) and social dynamics (e.g. diffusion of perception). Currently, I am the associate editor of the Journal of Simulation and the secretary of The OR Society‘s Special Interest Group in Simulation. I am the track coordinator of Agent-Based Simulation for the Winter Simulation Conference 2018.