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第26届中国控制与决策会议

作者： Guang-fan Xu Xiao-jia Wang Yan-yan Wu Shan-lin Yang School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education

ISBN: (纸本)9781479937097

Periodic replenishment inventory models are widely used in practice, especially for inventory systems in which many different goods are purchased from the same supplier. However, most of periodic replenishment inventory models have assumed a fixed length of the replenishment periods. In practice, it is possible that the replenishment periods are of a stochastic length. This paper presents an inventory control model for deteriorating items in the case of random replenishment intervals and stock-dependent selling rate. The replenishment interval is assumed to obey from two different distributions, namely, exponential and uniform distributions. Also, shortages are allowed in the term of partial backordering. For this model, we provide the necessary and sufficient conditions of the existence and uniqueness of the optimal solutions and a procedure is also developed to determine the optimal solution for the proposed models. At last, numerical example is shown to illuminate the presented model.

关键词： stochastic replenishment interval,stock-dependent selling rate,inventory control,partial backlogging,deteriorating items

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Security evaluation model for the enterprise cloud services based on grey fuzzy AHP

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Computer Modelling and New Technologies 2014年第10期18卷 239-244页

作者： Bengong, Yu Liu, Wang Fengyi, Guo School of Management Hefei University of Technology Hefei China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei China

This paper analyses the application status of cloud services to identify four factors that affect the security of enterprise cloud services (ECSs), including platform facilities, operational safety, operations management, and legal factors. Based on the four factors, the grey fuzzy analytic hierarchy process (GFAHP) is used to construct an evaluation model for the security of ECSs. An example is investigated to demonstrate the proposed model.

关键词： Web services

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A novel hybrid dynamic programming algorithm for a two-stage supply chain scheduling problem

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8th International Conference on Learning and intelligent optimization, LION 2014

作者： Pei, Jun Liu, Xinbao Fan, Wenjuan Pardalos, Panos M. Liu, Lin School of Management Hefei University of Technology Hefei 230009 China Center for Applied Optimization Department of Industrial and Systems Engineering University of Florida Gainesville FL 32601 United States Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education Hefei 230009 China Department of Computer Science North Carolina State University Raleigh NC 27695-7534 United States

ISBN: (纸本)9783319095837

This study addresses a two-stage supply chain scheduling problem, where the jobs need to be processed on the manufacturer's serial batching machine and then transported by vehicles to the customer for further processing. The size and processing time of the jobs are varying due to the differences of types, and setup time is needed before processing one batch. For the problem with minimizing the makespan, we formalize it as a mixed integer programming model. In addition, the structural properties and lower bound of the problem are provided. Based on the analysis above, a novel hybrid dynamic programming algorithm, combining dynamic programming and heuristics, is proposed to solve the problem. Furthermore, its time complexity is also analyzed. By comparing the experimental results of our proposed algorithm with the heuristics B F F and L F F , we demonstrate that our proposed algorithm has better performance and can solve the problem in a reasonable time. © 2014 Springer International Publishing.

关键词： Dynamic programming

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Research of Information Organization Based on Folksonomy

Research of Information Organization Based on Folksonomy

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第五届复杂科学管理国际研讨会

作者： YU Bengong GU Jiawei School of Management Hefei University of Technology P.R.China China Key Laboratory of Process Optimization and Intelligent Decision Making of Ministry of Education Hef

This paper proposes a method which uses RDF to express resources, tags and users of Folksonomy and allows users to assign tags freely by achieving the storage and query of RDF *** provides a means for completely open and sharing of information between *** it is also applied in the manufacture enterprises' website that it widens the application range of *** method can not only improve the degree of users' participation, but also realize the efficient management of mass data and the quick query of Information.

关键词： Folksonomy RDF Information Organization Information Representation

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A study on generalising bayesian inference to evidential reasoning

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8764卷 180-189页

作者： Yang, Jian-Bo Xu, Dong-Ling Decision and Cognitive Sciences Research Centre The University of Manchester ManchesterM15 6PB United Kingdom Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education HefeiAnhui230009 China

In this paper the relationship between Bayes’ rule and the Evidential Reasoning (ER) rule is explored. The ER rule has been uncovered recently for inference with multiple pieces of uncertain evidence profiled as a belief distribution and takes Dempster’s rule in the evidence theory as a special case. After a brief introduction to the ER rule the conditions under which Bayes’ rule becomes a special case of the ER rule are established. The main findings include that the normalisation of likelihoods in Bayesian paradigm results in the degrees of belief in the ER paradigm. This leads to ER-based probabilistic (likelihood) inference with evidence profiled in the same format of belief distribution. Numerical examples are examined to demonstrate the findings and their potential applications in probabilistic inference. It is also demonstrated that the findings enable the generalisation of Bayesian inference to evidential reasoning with inaccurate probability information with weight and reliability. © Springer International Publishing Switzerland 2014.

关键词： decision making

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A mixture of HMM,GA,and Elman network for load prediction in cloud-oriented data centers

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Journal of Zhejiang University-Science C(Computers and Electronics) 2013年第11期14卷 845-858页

作者： Da-yu XU Shan-lin YANG Ren-ping LIU MOE Key Laboratory of Process Optimization and Intelligent Decision-Making Hefei University of Technology Information and Communication Technologies Centre CSIRO

The rapid growth of computational power demand from scientific,business,and Web applications has led to the emergence of cloud-oriented data *** centers use pay-as-you-go execution environments that scale transparently to the *** prediction is a significant cost-optimal resource allocation and energy saving approach for a cloud computing *** linear or nonlinear prediction models that forecast future load directly from historical information appear less *** classification before prediction is necessary to improve prediction *** this paper,a novel approach is proposed to forecast the future load for cloud-oriented data ***,a hidden Markov model(HMM) based data clustering method is adopted to classify the cloud *** Bayesian information criterion and Akaike information criterion are employed to automatically determine the optimal HMM model size and cluster *** HMMs are then used to identify the most appropriate cluster that possesses the maximum likelihood for current *** the data from this cluster,a genetic algorithm optimized Elman network is used to forecast future *** results show that our algorithm outperforms other approaches reported in previous works.

关键词： Cloud computing Load prediction Hidden Markov model Genetic algorithm Elman network

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A BSC-ANP Model for Evaluation of Strategic Fit of New Product Development Projects

A BSC-ANP Model for Evaluation of Strategic Fit of New Produ...

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第25届中国控制与决策会议

作者： Ying Yang ShanLin Yang Jian Yang School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education

ISBN: (纸本)9781467355339

New product development (NPD) projects have been major forces driving company competitive advantage. All of them should align with corporate strategy so that the limited resources may be allocated effectively. However, few studies have been conducted to measure the extent that the NPD project matches with strategy. The paper identifies the cause-effect relationships between the strategy BSC measures for NPD projects based on strategy map and presents a BSC-ANP model to evaluate the strategic fit of projects. The causal relationships and interdependencies between projects and criteria are integrated with ANP model to produce the final priorities of projects with respect to their strategic fit. The proposed model was tested against empirical data drawn from NPD projects in an automobile company.

关键词： Evaluation, Strategic fit, New product development project, BSC-ANP

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Research of large scale manifold learning based on MapReduce

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Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice 2014年 34卷 151-157页

作者： Xue, Yong-Jian Ni, Zhi-Wei School of Management Hefei University of Technology Hefei230009 China The MOE Key Laboratory of Process Optimization and Intelligent Decision-Making Hefei230009 China

With the rapid development of the information technology, it is challenging for the traditional machine learning and data mining algorithms to deal with large scale explosive growth data. Manifold learning is a dimensionality reduction algorithm which can overcome some shortages of traditional linear dimensionality reduction methods. However, it is not useful for large scale data because of high complexity. In order to deal with the dimensionality reduction of large scale data, a distributed manifold learning algorithm is proposed based on MapReduce. Local sensitive hash functions are used to map the similarity points to the same bucket, then the geodesic distance between points in the same bucket can be computed by Euclidean norm according to the local homeomorphisms of Euclidean spaces of manifold and the geodesic distance among points between buckets can be computed by the modified geodesic distance formula which takes use of central points and edge points. Experiments on large scale of manmade dataset and real dataset show that this distributed manifold learning algorithm can approximate the geodesic distance between points effectively and it is useful for large scale dimensionality reduction.

关键词： MapReduce

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Research of enterprise knowledge portal system for product R&D

Research of enterprise knowledge portal system for product R...

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2nd International Conference on Information Engineering and Applications, IEA 2012

作者： Yu, Ben-Gong Zhao, Shu Ping School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-making Hefei 230009 China

ISBN: (纸本)9781447148463

Knowledge Management has become one of the core competitions in the enterprise. In order to minimize product development cycle and promote market competitiveness, we need to optimize the level of knowledge management in complex product development processes based on the analysis of the characteristics of enterprise knowledge management for product R&D process, and make use of knowledge management theory and information technology. This paper put forward the knowledge management process of the product R&D enterprise and the architecture model of enterprise knowledge portal (EKP) system, which can provide the theoretical basis and the reference model for the implementation of Enterprise Knowledge Management for product R&D. Finally, the EKP system for product R&D based on the platform of sharepoint is constructed. © 2013 Springer-Verlag.

关键词： Knowledge management

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RS-LSSVM: A new ensemble method for sentiment classification based on random subspace

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ICIC Express Letters, Part B: Applications 2014年第6期5卷 1773-1778页

作者： Wang, Gang Yang, Shanlin Ma, Jian School of Management Hefei University of Technology No. 193 Tunxi Road Hefei China Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Hefei University of Technology No. 193 Tunxi Road Hefei China Department of Information Systems City University of Hong Kong Tat Chee Avenue Kowloon Hong Kong

As analyzing and predicting the polarity of the sentiment plays an important role in understanding social phenomena and general society trends, sentiment classification problem has become a popular topic in academia and industry in recent years. However, comparing with Bagging and Boosting, another popular ensemble method, i.e., Random Subspace, is paid much less attention to the sentiment classification problem. In this research, we propose a new ensemble method, RS-LSSVM, for sentiment classification based on Random Subspace and LSSVM. Ten public sentiment classification datasets are used to verify the effectiveness of the proposed RS-LSSVM. Experimental results reveal that RS-LSSVM can get the better results than the four base learners, Bagging, and Boosting. All these results indicate that RS-LSSVM can be used as an alternative method for sentiment classification.

关键词： Support vector machines

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