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SSRN 2024年

作者： Xing, Ligang Hu, Xiaoxuan Zhu, Waiming Zhu, Xutong Xia, Wei School of Management Hefei University of Technology Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei230009 China Engineering Research Center for Intelligent Management of Aerospace System Hefei230009 China

After natural disasters such as floods and earthquakes, Earth observation satellites (EOSs) often need to revisit affected areas multiple times to acquire multitemporal images. Such observation tasks are referred to as multitemporal revisit tasks. In this paper, we study the Earth observation satellite scheduling problem for multitemporal revisit tasks, which is a combinatorial optimization problem in continuous space. This problem exhibits more complex constraints and is more challenging to solve than the traditional Earth observation satellite scheduling problem. Firstly, we formally define the problem and formulate it with a mixed integer nonlinear programming model. Secondly, we develop a variable neighborhood search algorithm to search for the optimal solution. This algorithm embeds a dynamic greedy heuristic, which can efficiently generate a schedule for satellites. Thirdly, computational experiments demonstrate the efficiency and stability of the algorithm. Moreover, the CPU time of the algorithm increases linearly with both task count and revisit number, indicating good scalability. © 2024, The Authors. All rights reserved.

关键词： Integer programming

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Single-valued neutrosophic entropy and similarity measures to solve supplier selection problems

Single-valued neutrosophic entropy and similarity measures t...

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作者： Jin, Feifei Ni, Zhiwei Chen, Huayou Langari, Reza Zhu, Xuhui Yuan, Hongjun School of Management Hefei University of Technology Hefei Anhui China Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Hefei Anhui China Department of Mechanical Engineering Texas AandM University College StationTX United States School of Mathematical Sciences Anhui University Hefei Anhui China School of Statistics and Applied Mathematics Anhui University of Finance and Economics Bengbu Anhui233030 China

The single-valued neutrosophic sets (SVNSs) are useful tools to describe uncertainty and inconsistent information that exist in real world. For SVNSs theory, two important topics are single-valued neutrosophic entropy and single-valued neutrosophic similarity measurer. This paper investigates a multi-attribute decision-making (MADM) method by using single-valued neutrosophic entropy and similarity measure. First, the concepts of single-valued neutrosophic entropy and similarity measure are presented. Then, based on the trigonometric functions (i.e., sine function and cosine function), we introduce two information measure formulas and prove that they satisfy the requirements of the single-valued neutrosophic entropy and similarity measure, respectively. Furthermore, we study the inter-relationship between single-valued neutrosophic entropy and similarity measure. By using Lagrange Multiplier Method and closeness degree, we develop a novel single-valued neutrosophic MADM method. Finally, a numerical example of selecting the desirable supplier is provided, and the comparison with existing approaches is performed to validate the rationality and effectiveness of the proposed method. © 2018 - IOS Press and the authors. All rights reserved.

关键词： Entropy

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Effectiveness Evaluation Method of Constellation Satellite Communication System with Acceptable Consistency and Consensus Under Probability Hesitant Intuitionistic Fuzzy Preference Relationship

Research Square

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Research Square 2022年

作者： Wang, Yanjun Hu, Xiaoxuan Wang, Lidong School of Management Hefei University of Technology Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision Making Ministry of Education Hefei230009 China Department of Mathematics Dalian Maritime University Dalian116026 China

System effectiveness evaluation is an important part of constellation satellite communication system research, with applications in project verification and optimization as well as tactical and technical measurement argumentation. This paper presents a systematic and comprehensive effectiveness evaluation method for a constellation satellite communication system under a probabilistic hesitant intuitionistic fuzzy preference relationship (PHIFPR), aiming to better address the fuzziness and uncertainty in effectiveness evaluation. First, a proposed definition of PHIFPR describes the hesitancy of evaluators, provides hesitancy distribution information, and depicts the worst negative information and risk preferences in effectiveness evaluation. Then, we deduce the approximate consistency index of PHIFPR and establish a mathematical programming model to increase individual consistency when the approximate consistency index does not reach a predetermined level. In the sequel, a proposed group consensus index uses the PHIFPR-based Hausdorff distance to measure the closeness between evaluators’ judgements. Afterwards, a consistency and consensus improvement model is designed to retain the original opinions of evaluators to make the consistency and consensus of PHIFPRs acceptable. Moreover, a goal programming model is established to gain the reliable scheme priority weights by regarding the approximate consistency condition of a PHIFPR as a fuzzy constraint. Finally, an experimental example is offered to highlight the practicability and feasibility of the proposed method, and some comparative analyses with other methods offer insights into the designed method. © 2022, CC BY.

关键词： Satellites

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Improved algorithm for single machine scheduling with release dates

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Zhongguo Jixie Gongcheng/China Mechanical Engineering 2008年第8期19卷 929-932页

作者： Li, Kai Ma, Huawei Yang, Shanlin Hefei University of Technology Hefei 230009 China Key Laboratory of Process Optimization and Intelligent Decision-making Hefei 230009 China

This paper considered the single machine scheduling problem with unequal release dates so as to minimize total completion times. This problem was proved to be as an NP-hard problem. Traditional heuristics for the problem were analyzed, and then we presented an improved algorithm. A numerical example and its computational result were given. The performance of the algorithm was also analyzed by experiments and the experimental results show that the algorithm is more effective than the existing heuristics.

关键词： Heuristic algorithm Release date Single machine scheduling Total completion times

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Multi-Objective optimization of Cloud Manufacturing Service Combination Based on Manufacturing and Logistics Coordinate

Multi-Objective Optimization of Cloud Manufacturing Service ...

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Chinese Control and decision Conference, CCDC

作者： Sining Han Bingfeng Ge Wanying Wei Xiaonong Lu Zeqiang Hou Yuming Huang College of Systems Engineering National University of Defense Technology National University of Defense Technology Changsha China Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education University of Science and Technology of China Hefei China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

With the continuous emergence of new technologies, the manufacturing industry is facing unprecedented challenges. Manufacturing services typically involve various types of production equipment, diverse suppliers, and varied customer demands. optimization in this context often encompasses multi pie objectives, necessitating timely adjustments in service comb ¡nations to meet customer needs. Traditional manufacturing models evidently fall short in resource allocation within manufacturing supply chains. Cloud manufacturing, proposed as a novel manufacturing model, aims to optimize resource allocation through the combination and configuration of resources, there by enhancing the efficiency of manufacturing supply chains. Logistics, as a crucial component within manufacturing supply chains, underscores the significance of coordinating the optimizad on of manufacturing and logistics services. This research focus es on the multi-objective optimization problem of cloud manufacturing service combinations. Building upon the execution process of manufacturing and logistics services for complex product manufacturing tasks, a novel mathematical model for the optimization of manufacturing resources and logistics resources i s constructed. The model utilizes the NSGA-H algorithm to coordinate the optimization processes of manufacturing and legistics resources. Finally, a case study demonstrates the effectiveness of the proposed model.

关键词： Costs Supply chains Production equipment Pareto optimization Mathematical models Manufacturing Resource management

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The construction of performance management system based on balanced scorecard

The construction of performance management system based on b...

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International Conference on Computer Science and Service System (CSSS)

作者： Dengzhou Zhang Zhanglin Peng Yuanyuan Gao finance Department China electronics technology group corporation Beijing China Institute of Computer Network System Hefei University of Technology Hefei China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei China

ISBN: (纸本)9781424497621

In China, there are many actual problems in some enterprises' performance management, such as the target dislocation, the unscientific assessment indicator, the assessment results' not linking to rewards and punishments, assessment system solidification and so on. All these problems have affected the effectiveness display of performance management to a great extent. In view of this, this article has constructed performance management system based on the balanced scorecard, taking advantage of balanced scorecard in the strategic management and the performance management. Finally, the article demonstrates the validity and rationality of the research through the case study of Company A.

关键词： Companies Marketing and sales Finance Qualifications Military communication

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A Multimodal Data-driven Framework for Anxiety Screening

arXiv

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arXiv 2023年

作者： Mo, Haimiao Ding, Shuai Hui, Siu Cheung The School of Management Hefei University of Technology Anhui Hefei23009 China The Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education China The School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore

Early screening for anxiety and appropriate interventions are essential to reduce the incidence of self-harm and suicide in patients. Due to limited medical resources, traditional methods that overly rely on physician expertise and specialized equipment cannot simultaneously meet the needs for high accuracy and model interpretability. Multimodal data can provide more objective evidence for anxiety screening to improve the accuracy of models. The large amount of noise in multimodal data and the unbalanced nature of the data make the model prone to overfitting. However, it is a non-differentiable problem when high-dimensional and multimodal feature combinations are used as model inputs and incorporated into model training. This causes existing anxiety screening methods based on machine learning and deep learning to be inapplicable. Therefore, we propose a multimodal data-driven anxiety screening framework, namely MMD-AS, and conduct experiments on the collected health data of over 200 seafarers by smartphones. The proposed framework’s feature extraction, dimension reduction, feature selection, and anxiety inference are jointly trained to improve the model’s performance. In the feature selection step, a feature selection method based on the Improved Fireworks Algorithm is used to solve the non-differentiable problem of feature combination to remove redundant features and search for the ideal feature subset. The experimental results show that our framework outperforms the comparison methods. © 2023, CC BY-NC-SA.

关键词： Feature Selection

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Forecasting of electricity price subsidy based on installed cost of distributed photovoltaic in China

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Energy Procedia 2019年 158卷 3393-3398页

作者： Changhui Yang Rui Yao Kaile Zhou School of Management Hefei University of Technology Baohe District Hefei 230009 China Key Laboratory of Process Optimization and Intelligent Decision-Making ( Ministry of Education) Hefei University of Technology Baohe District Hefei 230009 China Department of Public Policy City University of Hong Kong Kowloon Hong Kong

In China, the installed cost of distributed photovoltaic (DPV) is declining rapidly. However, the level of subsidy per kWh for DPV is adjusted less frequently by the Chinese government. This paper proposed a linkage model to forecast subsidy per kWh of DPV based on net present value (NPV) method. The results show that the increase of subsidy duration, internal consumption proportion and sunshine hours will reduce subsidy level. Therefore, it is suggested that the Chinese government should take varied and targeted measures, such as reducing different subsidies for new DPV users who install DPV in different years, choosing a longer subsidy duration and setting different subsidy levels in different regions. These varied and targeted measures are beneficial to both government and users, because they can reduce the annual financial burden for the government and the surcharges of electricity purchase for users.

关键词： Distributed photovoltaic subsidy NPV method China

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An Empirical Analysis of Carbon Emission Price in China

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Energy Procedia 2018年 152卷 823-828页

作者： Kaile Zhou Yiwen Li School of Management Hefei University of Technology Hefei 230009 China Key Lab of Process Optimization and Intelligent Decision-making Ministry of Education Hefei 230009 China Department of Public Policy City University of Hong Kong Kowloon Hong Kong SAR China

Carbon emission trading, as an effective economic tool to deal with climate change issues, has received widespread attention in recent years. As a major carbon emitter, China plays an important role in global climate change. This paper uses the Vector Error Correction (VEC) model to explore the dynamic relationship between energy price, macroeconomic indicators, air quality, and carbon emission trading price. The results show that there is a long-term equilibrium relationship between these selected indicators and carbon emission trading price. In addition, this paper also uses the Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) model to analyze the carbon price fluctuation characteristics. It is found that there is a positive leverage effect on the price fluctuation of the selected carbon emission return series. External bad news will have a greater impact on carbon price fluctuation than good news.

关键词： Carbon market Carbon emission trading GARCH model Price fluctuation

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A study on DS-SVM-based forecast model from the view of information fusion

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International Journal of u- and e- Service, Science and Technology 2015年第2期8卷 395-404页

作者： Zhu, Weidong Sun, Yibo Wu, Yong Liu, Jingyu School of Economics Hefei University of Technology HefeiAnhui China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education HefeiAnhui China Institute of Industrial Information Hefei University of Technology HefeiAnhui China School of Management Hefei University of Technology HefeiAnhui China School of Management Hefei University of Technology HefeiAnhui China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education HefeiAnhui China School of Management Hefei University of Technology HefeiAnhui China

Dempster-Shafer Theory is specially advantaged in information fusion, while Support Vector Machine (SVM) can well deal with high-dimensional limited sample data. This Article firstly forecasts the data samples by categories with multiple SVMs, and hence based thereon, fuses the resulting information from multiple SVM models by using DS theory. At the end, Anderson's Iris data set is used to simulate the system of the created DS-SVM model, which shows that the approaches proposed in this Article can not only increase the accuracy rate of the SVM forecasting model, but also improve the propensity scores of the SVM forecasting model. © 2015 SERSC.

关键词： Support vector machines

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