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

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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An efficient method for improving query efficiency in data warehouse

Journal of Software

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Journal of Software 2011年第5期6卷 857-865页

作者： Ni, Zhiwei Guo, Junfeng Wang, Li Gao, Yazhuo School of Management Hefei University of Technology Hefei Anhui China Key Lab of Process Optimization and Intelligent Decision-making Ministry of Education Hefei Anhui China

There are lots of performance bottlenecks for real-time queries in mass data. Many methods can only improve the efficiency for frequently used queries, but it is not advisable to neglect the non-frequently used queries. This paper proposes a new integrated index model called BBI and illustrates the application of this model. Based on the feature of data warehouse and OLAP queries, this index model is built with inverted index, aggregation table, bitmap index and b-tree. It greatly promotes not only the efficiency of frequently used queries, but also the performance of other queries. The analytical and experimental results demonstrate the utility of BBI. © 2011 ACADEMY PUBLISHER.

关键词： Data warehouses

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Service-oriented partner selection process model and algorithm for dynamic virtual enterprise

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Journal of Computational Information Systems 2011年第14期7卷 5159-5166页

作者： Zhang, Yiwen Ni, Zhiwei Song, Jie Wang, Li Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei University of Technology Hefei 230009 China School of Computer Science and Technology Anhui University Hefei 230009 China

The key link of constructing a virtual enterprise is to choose a cooperation partner who has the characteristics of sensitive, competitive and compatible. To solve the large scale partner selection under the environment of networked collaborative manufacturing, this paper puts forward a service-oriented dynamic virtual enterprise partner selection process model. Based on this, it further combining parallel genetic algorithm (PGA) with interactive genetic algorithm (IGA), and put forward a kind of phases of partner selection strategy. Use of each enterprise service enterprise constraint of preliminary screening to reduce problem solving space, top-k kinds of optimizing enterprise service composition can be achieved using PGA. Then, the optimal partner composition is acquired using IGA under mutual cooperation of group decision-making and evolution mechanism conditions. Finally, through the experiments proved its rationality and feasibility. © 2011 Binary Information Press December, 2011.

关键词： Problem solving

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A Two-Dimensional Time-Aware Cloud Service Recommendation Approach with Enhanced Similarity and Trust

SSRN

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SSRN 2023年

作者： Tang, Chunhua Zhao, Shuangyao Chen, Binbin Lu, Xiaonong Zhang, Qiang School of Management Hefei University of Technology Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei230009 China

Owing to an increasing number of functionally equivalent services on the cloud computing platform, quality-of-service (QoS) prediction and service recommendation have been developed using collaborative filtering (CF) techniques. However, each individual QoS is related to service status and user perceptions and thus instantly varies over time. QoS instantaneity often makes service predicted QoS deviate from actual values in traditional CF approaches. In addition, existing CF approaches ignore inauthentic QoS values given by untrustworthy users. To address these problems, we develop a two-dimensional time-aware and trust-aware service recommendation approach (TaTruSR). First, considering QoS instantaneity, both time weight (time dimension) and temporal certainty (QoS dimension) are designed to determine the contribution of co-invoked services. Second, a set of most similar and trusted neighbors can be identified from the view of the time-aware similarity model and trust model. In models, the direct similarity and local trust are calculated based on the QoS ratings and contribution of co-invoked services to improve the prediction accuracy and eliminate unreliable QoS. The indirect similarity and global trust are estimated based on the social network to alleviate the data sparsity problem. Finally, missing QoS prediction and service recommendation for the active user can be achieved based on enhanced similarity and trust. A case study and experimental evaluation on real-world datasets demonstrate the practicality and accuracy of the proposed approach. © 2023, The Authors. All rights reserved.

关键词： Forecasting

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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 method based on manifold learning and Bagging for text classification

A method based on manifold learning and Bagging for text cla...

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International Conference on Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC)

作者： FengGang Li JiLi Fan Li Wang HuLin Zhang Rui Duan Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei University of Technology Hefei China Hefei University of Technology Hefei Anhui CN

In order to solve the problem of high dimension in text classification, the paper proposes a method based on manifold learning and Bagging for text classification which imports manifold learning algorithm for dimension reduction. And Bagging algorithm is introduced when training classifier to improve the accuracy of text classification. Experimental results demonstrate that effect of text dimension reduction by manifold learning algorithm in the pretreatment of text classification is better, and the performance of the classifier has improved significantly.

关键词： Classification algorithms Text categorization Manifolds Training Bagging Support vector machine classification Euclidean distance

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Dynamic Topic Model for Tracking Topic Evolution and Measuring Popularity of Scientific Literature

Dynamic Topic Model for Tracking Topic Evolution and Measuri...

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IEEE International Conference on Data Science in Cyberspace (DSC)

作者： Yezheng Liu Jicheng Wang Yang Qian Yuanchun Jiang Jianshan Sun Yidong Chai School of Management Hefei University of Technology National Engineering Laboratory for Big Data Distribution and Exchange Technologies Key Laboratory of Process Optimization and Intelligent Decision Making Ministry of Education

ISBN: (纸本)9781665418164

With the progress of science and technology, a large number of scientific papers are published every year. Faced with such large data, identifying high-value research and hot research directions has become an interesting and important task. Previous studies focus less on the popularity measurement of research papers. In this paper, we use a dynamic topic model (DTM) for tracking the topic evolution trend and measuring the popularity of research papers based on the topic hotness. To test our model effectiveness, we conduct experiments on 5,964 research papers in the category of management. Our results show that DTM can help to monitor topic evolution and measuring popularity for scientific literature.

关键词： Current measurement Conferences Cyberspace Data science Market research Data models Time factors

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Strategic project selection based on evidential reasoning approach for high-end equipment manufacturing industry 3

Strategic project selection based on evidential reasoning ap...

引用

3rd International Conference on Mechanical, Electronic and Information Technology Engineering, ICMITE 2017

作者： Lu, Guangyan Xue, Min Liu, Yin Chang, Wenjun Department of Operation Management CRRC Qishuyan Institute Co. Ltd Changzhou Jiangsu213011 China School of Management Hefei University of Technology Hefei Box 270 Hefei Anhui230009 China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei Box 270 Hefei Anhui230009 China

With the rapid development of science and technology, emerging information technologies have significantly changed the daily life of people. In such context, strategic project selection for high-end equipment manufacturing industries faces more and more complexities and uncertainties with the consideration of several complex criteria. For example, a group of experts rather than a single expert should be invited to select strategic project for high-end equipment manufacturing industries and the experts may feel difficulty to express their preferences towards different strategic projects due to their limited cognitive capabilities. In order to handle these complexities and uncertainties, the criteria framework of strategic project selection is firstly constructed based on the characteristics of high-end equipment manufacturing industries and then evidential reasoning (ER) approach is introduced in this paper to help experts express their uncertain preferences and aggregate these preferences to generate an appropriate strategic project. A real case of strategic project selection in a high-speed train manufacturing enterprise is investigated to demonstrate the validity of the ER approach in solving strategic project selection problem. © The Authors, published by EDP Sciences, 2017.

关键词： decision making

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Face Tracking Strategy of 7-DOF Manipulator Using optimization Algorithm Based on Velocity Analysis

Face Tracking Strategy of 7-DOF Manipulator Using Optimizati...

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IEEE International Conference on Robotics and Biomimetics

作者： Shuai Zhang Cancan Zhao Xian He Bo Ouyang Shanlin Yang The School of Management Hefei University of Technology Hefei China The Key Laboratory of Process Optimization and Intelligent Decision-Making(Ministry of Education) Hefei University of Technology Hefei China

ISBN: (纸本)9781665481106

Patients' facial expressions can reflect their condition, but expressions cannot be captured like ECG or EEG monitor. Long-term monitoring will increase the workload of nurses. To tackle this issue, we develop a face tracking strategy using a 7-DOF robot manipulator with a camera mounted on the end-effector. First, we analyze the relationship between the manipulator's workspace and optimal tracking pose and design an optimization function to initialize the head position. By comparing the speed of the head and manipulator, knowledge of the maximum tracking limit of the head and the manipulator in the tracking process is given. Moreover, a configuration-based optimization algorithm is proposed to minimize the error with theoretical optimal pose by converting radian to arc length. We calculate the optimal configuration of the camera with the feedback of the head configuration while minimizing the difference between theoretical optimal pose. Simulation experimental results verified that the proposed face tracking strategy outperforms the visual servoing control strategy only based on the pseudo-inverse of the Jacobian matrix.

关键词： Jacobian matrices Tracking Robot kinematics Manipulators Cameras Visual servoing Trajectory

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Manipulating Constrained Soft Tissue while Avoiding Obstacles using Reinforcement Learning with Self-Attention

Manipulating Constrained Soft Tissue while Avoiding Obstacle...

引用

IEEE International Conference on Robotics and Biomimetics

作者： Xian He Shuai Zhang Shanlin Yang Bo Ouyang The School of Management Hefei University of Technology Hefei China The Key Laboratory of Process Optimization and Intelligent Decision-Making (Ministry of Education) Hefei University of Technology Hefei China

ISBN: (纸本)9781665481106

The complexity of dynamics raises challenges in deformable object manipulation, particularly the soft tissue shape control in in vivo environment. Previous studies assume the soft tissue is in an obstacle-free space, and the constraints are constant. To go one step further, a Soft Actor-Critic (SAC) algorithm is presented to manipulate the soft tissue under external disturbances while avoiding obstacles. K-Means is applied to reduce the dimension of the state space. Furthermore, self-attention is introduced to focus on the external forces and the constraints. Experiment results show that the agent can shape the soft tissue into the target deformation with the proposed approach under unknown external force, where the agent can automatically increase attention to the external force. The agent can find an obstacle-free path while manipulating the soft tissue. Compared with the SAC algorithm, the proposed approach with self-attention requires less training time, and the critic network is more stable.

关键词： Training Shape control Shape Biological tissues Force Surgery Reinforcement learning

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