学术活动发布与订制系统

Simulation of Service Systems (By Peer-Olaf Siebers)

Many countries around the world are seeing a shift in the percentage of GDP from manufacturing to services. In service systems quality and timeliness of “good service” becomes more and more important for the success of businesses.

Systems simulation can be used as a tool to help assessing the current service quality of a system and to suggest improvements to system operation in order to enhance the service provided. In Operations Research two competing simulation methods can be used for such investigations: process oriented (top down) discrete event simulation and individual centric (bottom up) agent based simulation.

In my talk I will introduce both simulation methods and discuss their applicability to service system modelling and simulation. This will be followed by the presentation of two case studies that show how to apply these simulation methods to real world problems. In the first case study we analyse the cargo screening process at a seaport and in the second case study we look at the impact of different management practices on customer satisfaction in a retail environment.

Modelling Office Electricity Consumption: An Agent Based Approach (By Tao ZHANG)

Complexity science is a newly emergent scientific area studying complex systems. It is a broad multi-disciplinary subject which blends social sciences and natural sciences. Agent-based simulation is one of the most important research methods in complexity science. In this seminar, I will use a case study to demonstrate how agent-based simulation can be used to a tackle practical real-world problem: office electricity consumption.

The agent-based simulation case study is based on the School of Computer Science, University of Nottingham, UK. With the case study, we can understand the effectiveness of different energy management technologies and scenarios in office energy management. The study shows the robustness of agent-based simulation in energy research.

Biography

Peer-Olaf Siebers is a Senior Research Fellow at the School of Computer Science, University of Nottingham, UK. He received his PhD from Cranfield University, UK in 2004. The central theme in his work is the development of human behaviour models which can be used to better represent people and their behaviours in Operational Research simulation. Dr. Siebers is a committed advocate of agent-based simulation. For his PhD he studied the impact of human performance variation on the accuracy of manufacturing system simulation models of manual assembly lines. His recent activities include the simulation of human resource management practices in retail, simulation of cargo screening processes at seaports, and monitoring the impact of different governmental and energy supplier interventions on consumer behaviour. He has published his research in various high ranking journals and presented his work at the top national and international simulation conferences.

Zhang Tao is a Research Fellow in the Intelligent Modelling and Analysis Group, School of Computer Science, University of Nottingham, UK. He received his PhD from the University of Cambridge, UK in 2011. His research interests are in the areas of complexity science and energy economics, for example, agent-based modelling and system dynamics modelling for the energy market, energy policy design, energy consumer behaviour, and modelling technology policy and energy innovation diffusion (e.g. smart metering, micro-generation, photovoltaic). He is particularly interested in consumer decision-making, modelling human behaviour based on psycho-behavioural theories and social network theories, artificial energy market and policy design based on system dynamics models, and energy demand-side management.