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【Mingli Lecture 2021, Issue 76】 Associate Prof. Zhu Ning: Two-stage Uncertainty Optimization Techniques and Their Applications

Time: Thursday 30 December, 14:00-16:00 pm


Tencent Conference Number: 577 365 094


Brief Description of Report.


In many application scenarios, decision makers face a two-stage decision problem, namely the first stage decision (Here-and-now decision) and the second stage decision (Wait-and-see decision). In addition to this, decision makers are also faced with the challenge of uncertainty. This presentation will introduce some common techniques for two-stage uncertainty optimisation, such as two-stage stochastic program and two-stage robust optimisation, and discuss modelling ideas and methods for some specific application scenarios and design He also discusses the modelling ideas and methods, and designs corresponding solution algorithms for some specific application scenarios.


About the speaker.


Ning Zhu is an Associate Professor in the Department of Management and Economics of Tianjin University, and a National Merit Scholar. His main research interests are in transportation system operation management and optimisation. He uses mixed integer optimisation, stochastic optimisation, robust optimisation, stochastic processes and other technical tools to study the problems of site selection, vehicle path optimisation and resource allocation in transportation and logistics systems. Specific research problems include optimal traffic detector siting, public transport system optimisation and modelling, UAV route optimisation, public bicycle system siting and rebalancing problems, and route optimisation in disaster relief. He has published more than 30 papers, including many papers as first author/corresponding author in IJOC, TS, TR-Part B/C/E, EJOR, Journal of Scheduling, Theory and Practice of Systems Engineering, Journal of Systems Engineering, etc. He has presided over 4 projects of the National Natural Science Foundation of China and 2 projects of the Ministry of Education.


(Organizer: Department of Management Science and Logistics, Research and Academic Exchange Centre)


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