Dr Li ZhengPing and Dr Tan Puay Siew

Singapore Institute of Manufacturing Technology

Friday 18th October, 15:30
INET Oxford Seminar Room,
Eagle House, Walton Well Road, OX2 6ED

Supply chain risks have been garnering more attention and many published works acknowledge the increasing vulnerability to disruptions in supply chains. While traditional approaches have limitations on modelling and managing complex dynamical behaviours, few researches, however, explicitly embrace complex systems approach as a holistic, system-wide perspective to supply chain risk management. In this research, we attempt to develop technologies for investigating the performance impacts of random disruptions and design algorithms to mitigate risks related to demand variations in supply chains. First, we model a supply chain as a complex adaptive system – a collection of autonomous agents representing firms that seek to maximize their individual profit by exchanging information, products and services with one another. We then investigate the impact of random disruptions to the supply chain using agent-based simulation. In addition, we develop a built-in learning mechanism for the agents to adapt and mitigate uncertainties using evolutionary algorithms and model predictive control techniques. Finally, we propose validation to the models based on benchmarking and an industry case.


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