贾庆山
博士 教授
清华大学 自动化系
基于事件的优化、复杂系统性能评价与优化、随机优化
个性化签名
 姓名：贾庆山
 目前身份：在职研究人员
 担任导师情况：
 学位：博士

学术头衔：
 职称：高级教授

学科领域：
控制理论
 研究兴趣：基于事件的优化、复杂系统性能评价与优化、随机优化
贾庆山，2002年7月于清华大学自动化系获得自动化专业工学学士学位。2006年7月于清华大学自动化系获得控制科学与工程博士学位。2006年8月至2010年11月，留校任教，讲师。2010年12月至今，副教授。2013年8月至今，博士生导师。2006年8月至2007年2月，美国哈佛大学工程与应用科学学院，访问学者。访问：何毓琦教授。2010年4月至6月，香港科技大学电子与计算机工程系，访问学者。访问：曹希仁教授。2013年3月至8月，美国麻省理工学院信息与决策系统实验室，访问学者。访问：Dimitri P. Bertsekas教授。
主要研究方向：基于事件的优化、复杂系统性能评价与优化、随机优化。近年来在国际期刊发表论文30余篇，合作出版专著2部、专著章节1部。2009年获国家自然科学二等奖。2012年获国家自然科学基金优秀青年基金。2013年获教育部高等学校科学研究优秀成果奖（科学技术）自然科学二等奖。
个人主页：http://cfins.au.tsinghua.edu.cn/personalhg/jiaqingshan/homepage_qsj_cn.htm

主页访问
4043

关注数
0

成果阅读
133

成果数
13
贾庆山， Li Xia， Student Member， IEEE， Qianchuan Zhao， Member， and QingShan Jia
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING ，0001，（）：
1年11月30日
The maintenance problem with safetycritical components is significant for the economical benefit of companies. Motivated by a practical asset maintenance project, a new joint replacement maintenance problem is introduced in this paper. The dynamics of the problem are modelled as a Markov decision process, whose action space increases exponentially with the number of safetycritical components in the asset. To deal with the curse of dimensionality, we identify a key property of the optimal solution: the optimal performance can always be achieved in a class of policies which satisfy the socalled shortestremaininglifetime first (SRLF) rule. It reduces the action space from O(2n ) to (On ), where is the number of safetycritical components. To further speed up the optimization procedure, some interesting properties of the optimal policy are derived. Combining the SRLF rule and the neurodynamic programming (NDP) methodology, we develop an efficient online algorithm to optimize this maintenance problem. This algorithm can handle the difficulties of large state space and large action space. Besides the theoretical proof, the optimality and efficiency of the SRLF rule and the properties of the optimal policy are also illustrated by numerical examples. This work can shed some insights to the maintenance problems in a more general situation.
Joint replacement， maintenance actions， Markov decision processes， neurodynamic programming

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【期刊论文】A PotentialBased Method for FiniteStage Markov Decision Processes
贾庆山， QingShan Jia Member， IEEE
，0001，（）：
1年11月30日
FiniteStage Markov Decision Process (MDP) supplies a general framework for many practical problems when only the performance in a finite duration is of interest. Dynamic programming (DP) supplies a general way to find the optimal policies but is usually practically infeasible, due to the exponentially increasing policy space. Approximating the finitestage MDP by an infinitestage MDP reduces the search space but usually does not find the optimal stationary policy, due to the approximation error. We develop a method that finds the optimal stationary policies for the finitestage MDP. The method is based on performance potentials, which can be estimated through sample paths and thus suits practical application.
Performance potentials， policy iteration， stationary policy， finitestage Markov Decision

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贾庆山， QingShan Jia， QianChuan Zhao， and YuChi Ho
Proceedings of the 2006 American Control Conference Minneapolis, Minnesota, USA, June 1416, 2006，0001，（）：
1年11月30日
The pervasive application of digital computer in control and optimization techniques forces us to consider the constraint of limited memory space when dealing with large scale practical systems. As an example, we consider the famous Witsenhausen counterexample with the new constraint of limited memory space in this paper. The main difficulty is how to sample strategies that can be stored in the given memory space efficiently. The concept of Kolmogorov complexity measures the minimal memory space to store a strategy (i.e., simple strategies), but is incomputable. To overcome this difficulty, we propose a method based on ordered binary decision diagram to sample only simple strategies. Besides the high sampling efficiency which is demonstrated by numerical testing, the proposed sampling method can be easily combined with optimization algorithms and performance evaluation techniques. As an example, we show how to combine ordinal optimization, numerical integration, and the proposed sampling method to solve the Witsenhausen problem with the constraint of limited memory space. We hope this work can shed some insights to computerbased optimization problems with memory space constraint in a more general situation.
Kolmogorov complexity， strategy optimization， Witsenhausen problem

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【期刊论文】A SVMBased Method for Engine Maintenance Strategy Optimization
贾庆山， QingShan Jia， QianChuan Zhao
Proceedings of the 2006 IEEE International Conference on Robotics and Automation Orlando, Florida  May 2006，0001，（）：
1年11月30日
Due to the abundant application background, the optimization of maintenance problem has been extensively studied in the past decades. Besides the wellknown difficulty of large state space and large action space, the pervasive application of digital computers forces us to consider the new constraint of limited memory space. The given memory space restricts what strategies can be explored during the optimization procedure. By explicitly quantifying the minimal memory space to store a strategy using support vector machine, we propose to describe simple strategies exactly and only approximate complex strategies. This selective approximation can best utilize the given memory space for any description mechanism. We use numerical results on illustrative examples to show how the selective approximation improves the solution quality. We hope this work sheds some insights to best utilize the memory space for practical engine maintenance strategy optimization problems.
Engine maintenance problem， support vector machine， selective approximation

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贾庆山， Chen Song， Student member， IEEE， Xiaohong Guan， ， Senior Member， Qianchuan Zhao， Qingshan Jia
Proceedings of the WeA15.6 44th IEEE Conference on Decision and Control, and the European Control Conference 2005 Seville, Spain, December 1215, 2005，0001，（）：
1年11月30日
Planning for a complex remanufacturing systems is often an NPhard problem in terms of computational complexity and simulation is usually the only available but very timeconsuming approach in many cases. Ordinal optimization offers an efficient framework for simulation based optimization approaches. In this paper, a new constrained ordinal optimization method is presented for solving remanufacturing planning problems. The scheme of "Horse Race" with Feasibility Model (HRFM) is developed to select the set of good enough plans. The rough set method in machine learning and knowledge discovery is applied to generate rules for feasibility determination. This method is compared with the Blind Picking with Feasibility Model (BPFM) method. Numerical testing of a practical remanufacturing system shows that the HRFM method presented in this paper is more efficient to meet the same required alignment probability.

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【期刊论文】Comparison of selection rules for ordinal optimization
贾庆山， QingShan Jia， YuChi Ho， ， QianChuan Zhao
Mathematical and Computer Modelling 43 (2006) 1150–1171，0001，（）：
1年11月30日
usually very time consuming. Optimizing the system performance becomes even more computationally infeasible. Ordinal optimization (OO) is a technique introduced to attack this difficulty in system design by looking at “order” in performances among designs instead of “value” and providing a probability guarantee for a good enough solution instead of the best for sure. The selection rule, known as the rule to decide which subset of designs to select as the OO solution, is a key step in applying the OO method. Pairwise elimination and round robin comparison are two selection rule examples. Many other selection rules are also frequently used in the ordinal optimization literature. To compare selection rules, we first identify some general facts about selection rules. Then we use regression functions to quantify the efficiency of a group of selection rules, including some frequently used rules. A procedure to predict good selection rules is proposed and verified by simulation and by examples. Selection rules that work well most of the time are recommended.
Ordinal optimization， Selection rules， Comparison

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【期刊论文】How much spare capacity is necessary for the security of resource networks?
贾庆山， QianChuan Zhao， QingShan Jia， Yang Cao
Physica A 373 (2007) 861–873，0001，（）：
1年11月30日
The balance between the supply and demand of some kind of resource is critical for the functionality and security of many complex networks. Local contingencies that break this balance can cause a global collapse. These contingencies are usually dealt with by spare capacity, which is costly especially when the network capacity (the total amount of the resource generated/consumed in the network) grows. This paper studies the relationship between the spare capacity and the collapse probability under separation contingencies when the network capacity grows. Our results are obtained based on the analysis of the existence probability of balanced partitions, which is a measure of network security when network splitting is unavoidable. We find that a network with growing capacity will inevitably collapse after a separation contingency if the spare capacity in each island increases slower than a linear function of the network capacity and there is no suitable global coordinator.
Statistical physics of complex networks， Graph theory， Network splitting， Balanced partition， Network capacity

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【期刊论文】How Topology Affects Security: An Upper Bound of Electric Power Network Security
贾庆山， QingShan Jia， QianChuan Zhao
，0001，（）：
1年11月30日
Electric power network is a fundamental facility in modern society. The importance to ensure and enhance the security of the power network can never be over emphasized. In this paper, we study how the topology of a power network restricts the security. By focusing on the power balanced condition which is necessary for the security after line outage contingencies, we show that a practical power network cannot avoid collapse. Using a method based on ordered binary decision diagram (OBDD) that fast enumerates the line outages causing network collapses, we obtain an upper bound for power network security, and indicate the transmission lines that are critical to power network security. This method is demonstrated on an IEEE 30bus network. We hope this work brings insights to the understanding of why power networks cannot avoid collapse and how to enhance the security of an electric power network.

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【期刊论文】COORDINATION OF SUPPLY CHAINS WITH DOWNSIDERISKAVERSE AGENTS
贾庆山， QingShan Jia
，0001，（）：
1年11月30日
Coordinating supply chains has been a major issue in supply chain management research. This paper focuses on the coordination of supply chains with downsideriskaverse agents. Motivating by the revenue sharing contract, we developed the sufficient conditions for the coordination of the supply chain with one downsideriskaverse agent. Following the sufficient conditions, the downside protection contract thus developed also allows arbitrary allocation of the profit between the supplier and the retailer. We also develop the necessary condition for the coordination of the supply chain when both the supplier and the retailer are downsiderisk averse. We hope this work sheds some insights to the study of the coordination of supply chains with downsideriskaverse agents in more general situations.

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