全校師生：
我校定于2017年6月20日與6月23日舉辦研究生靈犀學(xué)術(shù)殿堂——李海濤報(bào)告會(huì)，現(xiàn)將有關(guān)事項(xiàng)通知如下：
1.報(bào)告會(huì)簡(jiǎn)介
報(bào)告人：李海濤
報(bào)告一：
時(shí) 間：2017年6月20日（星期二） 下午15：30
地 點(diǎn)：機(jī)電學(xué)院第一會(huì)議室（友誼校區(qū)航空樓B406）
主 題： Data-Driven Optimization and Prescriptive Analytics: Recent Trends, Opportunities and Applications in Supply Chains
內(nèi)容簡(jiǎn)介：
With the fast growth of information technology (IT) and availability of “big-data”, data-driven decision-support is playing a more important role than ever for the success of a company or organization. In this talk, we delineate different paradigms for putting data-driven optimization in action, including rolling horizon approach, sensitivity analysis in math programming, two-stage stochastic programming, integrated simulation-optimization and stochastic dynamic programming. Focus will be put on how the Three-Pillar of Analytics: Descriptive, Predictive and Prescriptive, can be integrated to obtain efficient and high-quality data-driven solutions. We will showcase the state-of-the-art applications of data-driven optimization in supply chains, including Dell’s PC supply chain configuration for mass customization, Amazon’s supply chain network design and inventory control, precision agriculture at Monsanto, and UPS’ recent award-winning ORION project. Finally, we will foresee and discuss promising future research topics and opportunities.
報(bào)告二：
時(shí) 間：2017年6月23日（星期五） 上午9：30
地 點(diǎn)：機(jī)電學(xué)院第一會(huì)議室（友誼校區(qū)航空樓B406）
主 題： Approximate Dynamic Programming and Its Applications
內(nèi)容簡(jiǎn)介：
Real world optimization applications in operations and supply chains are oftensequentialin nature, where decisions are madedynamicallyandadaptivelyduring the course of actions. Examples include multi-period production planning, inventory control, scheduling, routing and various resource allocation applications. While it is theoretically sound to model these problems as a dynamic programming model, or Markov decision process (MDP) for those involving uncertainty, the traditional solution approach based on Bellman’s recursion suffers the well-known curse-of-dimensionality, thus can only handle toy-size stylized problems. In this talk, we introduce the approximate dynamic programming (ADP) methodology as an effective approach to handle reasonably large MDPs. Focus will be on the three main techniques in ADP: value function approximation, forward iteration via simulation, and effective/efficient deterministic optimization methods to deal with sub-problem in each ADP iteration. We will showcase two application examples: one on large-scale stochastic resource-constrained project scheduling (SRCPSP), and the other on multi-period stochastic resource planning.
2.歡迎各學(xué)院師生前來(lái)聽(tīng)報(bào)告。報(bào)告會(huì)期間請(qǐng)關(guān)閉手機(jī)或?qū)⑹謾C(jī)調(diào)至靜音模式。
黨委研究生工作部
機(jī)電學(xué)院
2017年6月19日
報(bào)告人簡(jiǎn)介
李海濤，博士，現(xiàn)任美國(guó)密蘇里大學(xué)圣路易分校副教授、終身教授、博士生導(dǎo)師、商學(xué)院博士學(xué)術(shù)委員會(huì)主任。2000年畢業(yè)于北航工業(yè)外貿(mào)專(zhuān)業(yè)，工程學(xué)士學(xué)位，之后于2002年獲得美國(guó)密西西比大學(xué)經(jīng)濟(jì)學(xué)碩士，200年獲運(yùn)營(yíng)管理博士學(xué)位。李教授具有多年的優(yōu)化建模和算法設(shè)計(jì)的研究經(jīng)驗(yàn)，并長(zhǎng)期致力于與企業(yè)，研究機(jī)構(gòu)在項(xiàng)目調(diào)度、資源分配及供應(yīng)鏈優(yōu)化應(yīng)用的合作。他曾于2004年在位于田納西州米靈頓的美國(guó)海軍人力研究科技所擔(dān)任統(tǒng)計(jì)研究員，2005年加州帕洛阿圖的惠普研究所客座研究員，2010至今任惠普研究咨詢(xún)。在國(guó)際知名學(xué)術(shù)期刊發(fā)表論文20余篇，包括《European Journal of Operational Research》、《Omega》、《Journal of Scheduling》、《Annals of Operations Research》、《IEEE Transactions on Automation Science and Engineering》、《Computers and Operations Research》、《Interfaces》、《Journal of the Operational Research Society》等。李教授于2010年獲得美國(guó)陸軍研究所頒發(fā)的青年研究者獎(jiǎng)、2015年密蘇里大學(xué)商學(xué)院優(yōu)秀研究獎(jiǎng)。李博士擁有兩項(xiàng)美國(guó)專(zhuān)利申請(qǐng)和多項(xiàng)發(fā)明公開(kāi)，獲得密蘇里大學(xué)2015最佳發(fā)明者獎(jiǎng)。
