报告人：Prof. Peter Luh, Head, Dept. of Electrical & Computer Engineering, University of Connecticut (Peter Luh教授是国际著名的生产制造调度专家,清华大学自动化系特聘教授) 报告题目： Optimal Auctions for Deregulated Electricity Markets 报告题目：From Manufacturing Scheduling to Supply Chain Coordination: The Control of Complexity and Uncertainty
时间：6月19日（星期二）下午2: 30； 3: 30 地点：工业工程系会议室，舜德楼北510 参加人员：欢迎感兴趣的教师和学生准时参加
报告摘要： Optimal Auctions for Deregulated Electricity Markets In deregulated electricity markets, auction mechanisms are used to select supply bids for energy and ancillary services. Currently, most Independent System Operators in the US use a “bid cost minimization” auction mechanism that minimizes total supply bid costs to select bids, and afterwards settle the market based on market-clearing prices. Consequently, the consumer payments could be significantly higher than the minimized bid cost from the auction. This gives rise to “payment cost minimization,” an alternative auction mechanism that directly minimizes consumer payments. A review of literature shows that with the same set of supply bids, payment cost minimization leads to reduced consumer payments as compared to bid cost minimization. While methods for minimizing offer costs abound, limited approaches for minimization of payment costs have been reported. This talk presents an effective method for directly minimizing payment costs. In view of the specific features of the problem including the non-separability of its objective function, the discontinuity of offer curves, and the maximum term in defining MCPs, our key idea is to use augmented Lagrangian relaxation, and to form and solve offer and MCP subproblems by using the surrogate optimization framework. Numerical testing results demonstrate that the method is effective, and the resulting payment costs are significantly lower than what are obtained by minimizing the offer costs for a given set of offers. Additionally, strategic behaviors of suppliers are studied within the game theoretic framework for the two auction mechanisms. General matrix games are solved by using the approximate Nash concept and with our auction algorithms developed as the core. Testing results demonstrate the cost savings for consumers under payment cost minimization as compared to bid cost minimization.
报告摘要： From Manufacturing Scheduling to Supply Chain Coordination: The Control of Complexity and Uncertainty
With time-based competition and rapid technology advancements, effective manufacturing scheduling and supply chain coordination are critical to quickly respond to changing market conditions. These problems, however, are difficult in view of inherent complexity and various uncertainties involved. A manufacturing scheduling problem is first formulated within the job shop context with order arrivals, processing times, due dates, and part priorities as a separable optimization problem. A solution methodology that combines Lagrangian relaxation, dynamic programming, and heuristics is developed. Method improvements to consider uncertainties and to effectively solve large problems are highlighted. The approach is then extended to coordinate companies in a decentralized supply chain. By relaxing cross-company constraints, the model is decomposed into company-wise subproblems, and a nested optimization structure is developed based on the job shop scheduling results. Coordination is performed through the iterative updating of cross- company prices without accessing other companies’ private information or intruding their decision-making authorities.
报告人简历及联系方式： Peter B. Luh received his B.S. in Electrical Engineering from National Taiwan University, M.S. in Aeronautics and Astronautics from M.I.T., and Ph.D. in Applied Mathematics from Harvard University. He has been with the University of Connecticut since 1980, and currently is the SNET Professor of Communications & Information Technologies and Head of the Department of Electrical and Computer Engineering. He is a Fellow of IEEE, the founding Editor-in-Chief of the new IEEE Transactions on Automation Science and Engineering, an Associate Editor of IIE Transactions on Design and Manufacturing, was the Editor-in-Chief of IEEE Transactions on Robotics and Automation (1999-2003), and has been elected as the Vice President for Publications for the IEEE Robotics and Automation Society. Email: Peter.Luh@uconn.edu URL: http://www.engr.uconn.edu/msl/
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