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Enhancing cut selection through reinforcement learning

science China Mathematics 2024年第6期67卷 1377-1394页

作者： Shengchao Wang Liang Chen Lingfeng Niu Yu-Hong Dai Academy of Mathematics and Systems science Chinese Academy of SciencesBeijing100190China research center on fictitious economy and data science Chinese Academy of SciencesBeijing100190China

With the rapid development of artificial intelligence in recent years,applying various learning techniques to solve mixed-integer linear programming(MILP)problems has emerged as a burgeoning research domain.Apart from constructing end-to-end models directly,integrating learning approaches with some modules in the traditional methods for solving MILPs is also a promising direction.The cutting plane method is one of the fundamental algorithms used in modern MILP solvers,and the selection of appropriate cuts from the candidate cuts subset is crucial for enhancing efficiency.Due to the reliance on expert knowledge and problem-specific heuristics,classical cut selection methods are not always transferable and often limit the scalability and generalizability of the cutting plane method.To provide a more efficient and generalizable strategy,we propose a reinforcement learning(RL)framework to enhance cut selection in the solving process of MILPs.Firstly,we design feature vectors to incorporate the inherent properties of MILP and computational information from the solver and represent MILP instances as bipartite graphs.Secondly,we choose the weighted metrics to approximate the proximity of feasible solutions to the convex hull and utilize the learning method to determine the weights assigned to each metric.Thirdly,a graph convolutional neural network is adopted with a self-attention mechanism to predict the value of weighting factors.Finally,we transform the cut selection process into a Markov decision process and utilize RL method to train the model.Extensive experiments are conducted based on a leading open-source MILP solver SCIP.Results on both general and specific datasets validate the effectiveness and efficiency of our proposed approach.

关键词： reinforcement learning mixed-integer linear programming cutting plane method cut selection

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research on Interest Rate Transmission Mechanism of China’s Bond Market:Empirical Analysis Based on Granger Causality Complex Network

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Journal of Systems science and Information 2023年第5期11卷 604-621页

作者： Xiao CUI Mo YIN Kun GUO Yijing WANG School of Economics and Management University of Chinese Academy of SciencesBeijing 100190China Research Center on Fictitious Economy&Data Science Chinese Academy of ScienceBeijing 100190China

The bond market is an important market for investment and financing in China’s economic sectors,and also an important part of the monetary policy framework.The internal transmission of bond market is an important part of market interest rate transmission,which iscritical to the effectiveness of monetary policy.However,few scholars have studied the characteristics of interest rate transmission in China.An in-depth study of the interest rate transmission mechanism and its dynamic evolution between different bond markets is conducive to clarify the pulse of transmission within Chinese bond market and to further unblock the transmission mechanism of monetary policy.From the perspective of system theory and based on the analysis method of Granger causality complex network,this paper finds that the interest rate transmission among various varieties in China’s bond market is relatively significant.Treasury bonds and CDB bonds are the two core bond varieties of interest rate transmission in the bond market.Simultaneously,this study concludes that the medium and long-term interest rate played a dominant role in the transmission of market interest rate during the easing phase of monetary policy,while the short-term interest rate played a dominant role in the transmission of market interest rate during the tightening phase of monetary policy.This paper also gives enlightenment and suggestions.

关键词： bond market interest rate transmission mechanism Granger causality complex network

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Impacts of Total Energy Consumption Control and Energy Quota Allocation on China′s Regional economy Based on A 30-region Computable General Equilibrium Analysis

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Chinese Geographical science 2015年第6期25卷 657-671页

作者： LI Na SHI Minjun SHANG Zhiyuan YUAN Yongna University of Chinese Academy of sciences research center on fictitious economy & data science Chinese Academy of Sciences

This paper examined the impacts of the total energy consumption control policy and energy quota allocation plans on China′s regional economy. This research analyzed the influences of different energy quota allocation plans with various weights of equity and efficiency, using a dynamic computable general equilibrium(CGE) model for 30 province-level administrative regions. The results show that the efficiency-first allocation plan costs the least but widens regional income gap, whereas the outcomes of equity-first allocation plan and intensity target-based allocation plan are similar and are both opposite to the efficiency-first allocation plan′ outcome. The plan featuring a balance between efficiency and equity is more feasible, which can bring regional economic losses evenly and prevent massive interregional migration of energy-related industries. Furthermore, the effects of possible induced energy technology improvements in different energy quota allocation plans were studied. Induced energy technology improvements can add more feasibility to all allocation plans under the total energy consumption control policy. In the long term, if the policy of the total energy consumption control continues and more market-based tools are implemented to allocate energy quotas, the positive consequences of induced energy technology improvements will become much more obvious.

关键词：能源消费区域经济配额分析控制计算分配方案中国位置

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Analysis on the Effect of Government Investment on Private Investment in Western China——Take Province A as an Example

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Journal of Systems science and Information 2023年第3期11卷 297-313页

作者： Ming CHEN Yingjie TIAN School of Economics and Management University of Chinese Academy of SciencesBeijing 100190China research center on fictitious economy and data science Chinese Academy of SciencesBeijing 100190China Key Laboratory of Big data Mining and Knowledge Management Chinese Academy of SciencesBeijing 100190China

Since China began reforming and opening up its economy,and especially since the launch of development projects in western China,province A has attracted an increasing amount of investment,which is the main driving force for provincial economic growth.Hence,this study uses a state space model to examine how government investment has affected economic growth in province A in western China,and explains whether there is a crowding-in effect or a crowding-out effect of local government investment on private investment.The findings indicate that both government and private investments have a positive,stimulating influence on economic growth in province A,with the latter being more impactful than the former.Productive and non-productive investments have different effects on province A’s economic growth.From the perspective of the trajectory of government investment elasticity,the elasticity of government and private investments in province A presents a very large spatio-temporal change.That is,from 1994 to 2009,government investment in province A had a crowding-in effect on private investment,but from 2010 to 2017,a crowding-out effect was observed.

关键词： province A in western China government investment private investment state space model

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New technology foresight method based on intelligent knowledge management

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Frontiers of Engineering Management 2020年第2期7卷 238-247页

作者： Lingling ZHANG Siting HUANG School of Economics and Management University of Chinese Academy of SciencesBeijing 100190China Research Center on Fictitious Economy&Data Science Key Laboratory of Big Data Mining and Knowledge ManagementChinese Academy of SciencesBeijing 100190China School of Economics and Management University of Chinese Academy

The increasing importance of technology foresight has simultaneously raised the significance of methods that determine crucial areas and technologies.However,qualitative and quantitative methods have shortcomings.The former involve high costs and many limitations,while the latter lack expert experience.Intelligent knowledge management emphasizes human–machine integration,which combines the advantages of expert experience and data mining.Thus,we proposed a new technology foresight method based on intelligent knowledge management.This method constructs a technological online platform to increase the number of participating experts.A secondary mining is performed on the results of patent analysis and bibliometrics.Thus,forward-looking,innovative,and disruptive areas and relevant experts must be discovered through the following comprehensive process:Topic acquisition→topic delivery→topic monitoring→topic guidance→topic reclamation→topic sorting→topic evolution→topic conforming→expert recommendation.

关键词： technology foresight intelligent knowledge management technological online platform

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Challenges to Engineering Management in the Big data Era

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工程管理前沿：英文版 2015年第3期2卷 293-303,322-323页

作者： Yong Shi research center of fictitious economy & data science University of the Chinese Academy of Sciences and Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences

This paper presents a review of the challenges to engineering management in the Big data Era as well as the Big data applications. First, it outlines the definitions of big data, data science and intelligent knowledge and the history of big data. Second, the paper reviews the academic activities about big data in China. Then, it elaborates a number of challenging big data problems, including transforming semi-structured and non-structured data into"structured format" and explores the relationship of data heterogeneity, knowledge heterogeneity and decision heterogeneity. Furthermore, the paper reports various real-life applications of big data, such as financial and petroleum engineering and internet business.

关键词： big data data science intelligent knowledge engineering management real-life applications

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A grid-based clustering algorithm for wild bird distribution

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Frontiers of Computer science 2013年第4期7卷 475-485页

作者： Yuwei WANG Yuanchun ZHOU Ying LIU Ze LUO Danhuai GUO Jing SHAO Fei TAN Liang WU Jianhui LI Baoping YAN Computer Network Information center Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of sciences Beijing 100049 China research center on fictitious economy and data science Chinese Academy of Sciences Beijing 100190 China

Advanced satellite tracking technologies provide biologists with long-term location sequence data to understand movement of wild birds then to find explicit correlation between dynamics of migratory birds and the spread of avian influenza. In this paper, we propose a hierarchical clustering algorithm based on a recursive grid partition and kernel density estimation （KDE） to hierarchically identify wild bird habitats with different densities. We hierarchically cluster the GPS data by taking into account the following observations： 1） the habitat variation on a variety of geospatial scales; 2） the spatial variation of the activity patterns of birds in different stages of the migration cycle. In addition, we measure the site fidelity of wild birds based on clustering. To assess effectiveness, we have evaluated our system using a large-scale GPS dataset collected from 59 birds over three years. As a result, our approach can identify the hierarchical habitats and distribution of wild birds more efficiently than several commonly used algorithms such as DBSCAN and DENCLUE.

关键词： hierarchical clustering bird migration kerneldensity estimation grid partition

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Water-saving Technologies,Solar Green House and Ecological Rehabilitation in Minqin Oasis of Gansu Province,China

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Chinese Journal of Population,Resources and Environment 2008年第3期6卷 73-82页

作者： Tao Weichun Shi Minjun Zhao Xuetao Graduate University of Chinese Academy of sciences CAS Beijing 100049 China research center on fictitious economy and data science CAS Beijing 100080 China

Land degradation and desertification have becom severe environmental problems in arid areas due to excessive use of water resources. It is urgent to reduce agricultural water use fo ecological rehabilitation, which may result in a decrease in agri cultural production and farmer's welfare. This paper focused on the impacts of some main measures including extensions of water saving irrigation, expanding solar green house and increasing off farm employment, which are generally recognized to be importan to alleviate water shortage and poverty. A bio-economic model i applied taking Minqin Oasis in Gansu Province as a case study site. Simulation results showed that the effect of expanding sola greenhouse was more positive than other ones so it drew more attention. On the view of the different effects between each irriga tion zone, mixed policy patterns suitable for them are suggested In Baqu, expanding solar greenhouse should be the most impor tant, auxiliary with encouraging pipe irrigation. Inversely, with regard to Quanshan, the major attention should be paid to subsidy for pipe irrigation and it would be better to supply the off-farm employment opportunities to the households in Huqu, where the expanding of solar greenhouse should also be summoned. Finally it should be noted that farmer's income would only resume to 90% of the current level in the short run by putting more effort into lo cal policies. Thus, the ecological compensation is needed to ensure farmer's welfare.

关键词：节水技术日光大棚生态修复环境保护

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Forecasting Container Throughput of Qingdao Port with a Hybrid Model

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Journal of Systems science & Complexity 2015年第1期28卷 105-121页

作者： HUANG Anqiang LAI Kinkeung LI Yinhua WANG Shouyang School of economy and Management Beihang University Department of Management sciences City University of Hong Kong research center on fictitious economy and data science Chinese Academy of Sciences Academy of Mathematics and Systems science Chinese Academy of Sciences

This paper proposes a hybrid forecasting method to forecast container throughput of Qingdao Port.To eliminate the influence of outliers,local outlier factor(lof) is extended to detect outliers in time series,and then different dummy variables are constructed to capture the effect of outliers based on domain knowledge.Next,a hybrid forecasting model combining projection pursuit regression(PPR) and genetic programming(GP) algorithm is proposed.Finally,the hybrid model is applied to forecasting container throughput of Qingdao Port and the results show that the proposed method significantly outperforms ANN,SARIMA,and PPR models.

关键词：集装箱吞吐量预测模型混合模式青岛港 PPR模型局部异常因子投影寻踪回归时间序列

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Kernel Regularized Multiple Criteria Linear Programming

Kernel Regularized Multiple Criteria Linear Programming

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第三届最优化与系统生物学国际研讨会

作者： Wen-Jing Chen Ying-Jie Tian School of Mathematical sciences of GUCAS research center on fictitious economy and data science CAS

＜正＞Based on our proposed regularized multiple criteria linear programming（RMCLP） for binary classification problems,this paper extends this method to treat with nonlinear case.By applying dual theory,we derived the dual problem of optimization problem constructed in RMCLP, and then proved the solution of RMCLP can be computed by the solution of its dual problem,finally, we constructed Algorithm Kernel RMCLP by introducing Kernel functions in RMCLP.A series of experimental tests are conducted to illustrate the performance of the proposed Kernel RMCLP with the outstanding support vector machine（SVM）.The results of several publicly available datasets and a real-life credit dataset all show that our Kernel RMCLP is a competitive method in classification.

关键词： multiple criteria linear programming Regularize Kernel support vector machine classification

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