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Performance evaluation of China’s industry: a generalized equilibrium data envelopment analysis approach with fixed-sum undesirable output

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INFOR: Information Systems and Operational Research 2021年第2期59卷 290-308页

作者： Min Yang Qingxian An Dan Hu Liang Liang a School of Management Hefei University of Technology Hefei P.R. China b Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Hefei University of Technology Hefei P.R.China c School of Business Central South University Changsha P.R. China

With the rapid development of economy, China faces a considerable challenge from environmental problems especially with the waste of gas pollution emitted by China’s industry. To assess the environmental performance of China’s industry, this paper proposes a new generalized equilibrium efficiency frontier data envelopment analysis (GEEFDEA) approach that considers waste gases as undesirable outputs. It is assumed that the total amount of waste gases that the industry is permitted to emit is limited (or fixed), that is, increasing air pollution of one area should reduce that of other areas for offset. Compared with the prior evaluation approaches, the proposed approach is the only one that satisfies the following conditions simultaneously. 1) The approach considers the property of the “fixed sum” of undesirable outputs. 2) The approach avoids the case in prior approaches (e.g., fixed sum output and zero sum gains DEA approaches) that an infeasible solution may occur when accessing decision making unites (DMUs) with fixed-sum undesirable outputs. 3) The proposed approach inherits all advantages of the GEEFDEA approach such as achieving an equilibrium state by only one step and obtaining a complete ranking order. Finally, the proposed approach is applied to evaluate the performance in China’s industry from 2008 to 2013. Results show China’s industry has significant regional characteristics.

关键词： Generalized equilibrium efficient frontier data envelopment analysis fixed-sum undesirable outputs China’s industry

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Financing constraints, principal-agent and Chinese listed firms’ output efficiency

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International Journal of u- and e- Service, Science and Technology 2016年第8期9卷 189-200页

作者： Zhu, Weidong Wang, Yiling Liu, Jingyu School of Economics Hefei University of Technology HefeiAnhui230009 China School of Management Hefei University of Technology HefeiAnhui230009 China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education HefeiAnhui230009 China

It is shown that output under financing constraints and principal-agent can be modeled as a one-side deviation from a frictionless output level. The effects of financing constraints and principal-agent can be identified and quantified by imposing a distribution assumption on the effects. Panel data on Chinese listed firms between 2008 and 2013 are used in the estimation. It is found that: (1) the output efficiency of Chinese listed firms is significantly affected by financing constraints and principal-agent;(2) the severity of financing constraints and principal-agent of firms in different regions varies;(3) firms’ output efficiency in east China varies greatly, and the mean efficiency is the lowest of the three regions. © 2016 SERSC.

关键词： Efficiency

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A Lite Fireworks Algorithm for optimization

arXiv

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arXiv 2023年

作者： Mo, Haimiao Zeng, Min 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 College of Computer Science Guangdong University of Science and Technology Guangdong Province Dongguan China

The fireworks algorithm is an optimization algorithm for simulating the explosion phenomenon of fireworks. Because of its fast convergence and high precision, it is widely used in pattern recognition, optimal scheduling, and other fields. However, most of the existing research work on the fireworks algorithm is improved based on its defects, and little consideration is given to reducing the number of parameters of the fireworks algorithm. The original fireworks algorithm has too many parameters, which increases the cost of algorithm adjustment and is not conducive to engineering applications. In addition, in the fireworks population, the unselected individuals are discarded, thus causing a waste of their location information. To reduce the number of parameters of the original Fireworks Algorithm and make full use of the location information of discarded individuals, we propose a simplified version of the Fireworks Algorithm. It reduces the number of algorithm parameters by redesigning the explosion operator of the fireworks algorithm and constructs an adaptive explosion radius by using the historical optimal information to balance the local mining and global exploration capabilities. The comparative experimental results of function optimization show that the overall performance of our proposed LFWA is better than that of comparative algorithms, such as the fireworks algorithm, particle swarm algorithm, and bat algorithm. © 2023, CC BY.

关键词： Scattering parameters

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Optimal Sizing of Ev Charging Stations Considering Charging Scheduling and Renewable Energy

SSRN

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SSRN 2022年

作者： Zhou, Kaile Hu, Dingding Yang, Shanlin School of Management Hefei University of Technology Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education Hefei University of Technology Hefei230009 China National Engineering Laboratory for Big Data Distribution and Exchange Technologies Shanghai China

The construction of electric vehicle (EV) charging stations is critical for the widespread use of EVs. Appropriate design of EV charging stations should fulfill charging requests while considering various economic issues. In this regard, we present an optimization model to address the sizing problem of EV charging stations with integration of renewable energy resources, energy storage system and multi-types of chargers. The proposed model aims at reducing the investment cost and improving the profitability of EV charging stations. In order to accurately estimate EV charging demand, the characteristics of EV charging behaviors are derived based on real-world charging data. Furthermore, a charging scheduling strategy that responds to time-of-use (TOU) price and charging demand levels is proposed to improve the utilization efficiency of chargers. Results show that the design of EV charging stations with integrated consideration of these components and charging scheduling strategy can achieve optimal economic efficiency. © 2022, The Authors. All rights reserved.

关键词： Renewable energy resources

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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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Integration scheduling optimization problem of production and transportation in supply chain

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Nanjing Li Gong Daxue Xuebao/Journal of Nanjing University of Science and Technology 2012年第SUPPL.2期36卷 292-298页

作者： Pei, Jun Liu, Xin-Bao Fan, Wen-Juan Liu, Lin Zhang, Yu-Lei School of Management Hefei University of Technology Hefei 230009 China Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of Education Hefei 230009 China

To study two-tier supply chain scheduling models comprised by multi suppliers and multi manufacturers, the scheduling optimization theory is applied into the supply chain domain. A math model is built by taking the minimization of total flow time of work pieces and total cost of delivery as optimization objectives. The dynamic programming algorithm is used to solve the problem based on analyzing the features of its optimum solution. Multi-objectives fusion is realized through analytic hierarchy process in the algorithm iterative process. The feasibility of this model and algorithm is illustrated by a numerical example.

关键词： Analytic hierarchy process

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Media Attention and ESG Greenwashing: Evidence from Chinese Listed Companies

SSRN

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SSRN 2023年

作者： Jiang, Cuixia Li, Xiuxiu Xu, Qifa Liu, Junhang School of Management Hefei University of Technology Anhui Hefei230009 China Philosophy and Social Sciences Laboratory of Data Science and Smart Society Governance Ministry of Education Anhui Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Anhui Hefei230009 China Ministry of Education Engineering Research Center for Intelligent Decision-Making & Information System Technologies Anhui Hefei230009 China

We investigate the relationship between media attention and environmental, social, and governance (ESG) greenwashing using the data of Chinese A-share listed companies from 2011 to 2020. Our results show that media attention can inhibit corporate ESG greenwashing behavior. Moreover, this inhibiting effect is mainly caused by paper media and becomes more prominent in non-state-owned enterprises (non-SOEs). The mediation analysis proves that media attention plays an important role in improving investor attention, thereby inhibiting corporate ESG greenwashing. The moderation analysis indicates that the effect of media attention on inhibiting ESG greenwashing is weakened in companies with more analyst following and higher quality of internal control. Our study provides a new view on the governance of ESG greenwashing in China. © 2023, The Authors. All rights reserved.

关键词： Quality control

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Probabilistic Electricity Price Forecasting and Uncertainty Estimation Using Deep Bayesian Model with Multi-Distribution Fusion

SSRN

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SSRN 2024年

作者： Shao, Zhen Han, Yating Fu, Chao Zha, Jianrui Yang, Shanlin School of Management Hefei University of Technology Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Anhui Hefei230009 China Philosophy and Social Sciences Laboratory of Data Science and Smart Society Governance Hefei University of Technology Ministry of Education Hefei230009 China Ministry of Education Engineering Research Center for Intelligent Decision-Making & Information System Technologies Hefei230009 China

Probabilistic electricity price forecasting (EPF) is paramount for stakeholder scheduling and trading in deregulated energy markets. However, during the process of establishing a probability prediction model, the consequential aleatoric and epistemic uncertainties are indistinguishable. Moreover, identifying epistemic uncertainty rather than aleatoric uncertainty is significant for conducting credible probabilistic EPF in cases with expected and unexpected fluctuations. This article proposes a hybrid approach under a Bayesian probability framework for performing reliable and accurate probabilistic forecasting. Specifically, it applies Bayesian deep learning model to convey the latent probability distribution of electricity prices, which represents the desirable epistemic uncertainty and inevitable aleatoric uncertainty. The embedded architecture employs a multi-head attention mechanism (MHAM) to allocate previous hidden states of long short-term memory (LSTM) cells, detecting both the local and global price patterns simultaneously. Considering the forecasting bias arising from aleatoric uncertainty in the process of establishing Bayesian networks, a new Wasserstein distance-based multi-distribution fusion mechanism driven by evidence theory is proposed and employed to identify and mitigate the aleatoric uncertainty of credible probabilistic EPF problems. The effectiveness of the proposed approach is evaluated on two real-world electricity price datasets and compared with twelve state-of-the-art models. © 2024, The Authors. All rights reserved.

关键词： Bayesian networks

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Case-based safety assessment of thermal power plants: A framework

Case-based safety assessment of thermal power plants: A fram...

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International Conference on Business management and Electronic Information (BMEI)

作者： Changyong Liang Dongxiao Gu Isabelle Bichindaritz Chunrong Zuo Fei Cheng School of Management Hefei University of Technology Hefei Anhui China Research Center of Intelligent Decision Making and Information System Technologies Ministry of Education of China Hefei Anhui China Department of Computer Science University of Illinois Chicago Chicago IL USA Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education of China Hefei Anhui China Institute of Technology University of Washington Tacoma WA USA

Security assessment of Thermal Power Plants (TPPs) is one of the important means to guarantee the safety of production in thermal power production enterprises. Essentially, the evaluation of power plant systems relies to a large extent on the knowledge and length of experience of the experts. Therefore in this domain Case-Based Reasoning (CBR) is introduced for the security assessment of TPPs since this methodology models expertise through experience management. Taking the management system of TPPs as breakthrough point, this paper presents a case-based approach for the security assessment decision support of TPPs (SATPP). First, this paper reviews commonly used approaches for TPPs security assessment and the current general evaluation process of TPPs security assessment. Then a framework for the management System Security Assessment of Thermal Power Plants (MSSATPP) is constructed and an intelligent decision Support System for MSSATPP (IDSS-MSSATPP) is functionally designed. MSSATPP involves several key technologies and methods such as knowledge representation and case matching.

关键词： Security Safety Production Power generation Power systems decision making Indexes

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Impacts of Cross-Channel Recommendation for Online-Niche Products

SSRN

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SSRN 2022年

作者： Qiu, Ju Zhao, Ju Hu, Xiaojian Zhou, Yongwu Min, Jie School of Management Hefei University of Technology Anhui Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Hefei230009 China Ministry of Education Engineering Research Center for Intelligent Decision-Making & Information System Technologies Hefei230009 China School of Business Administration South China University of Technology Guangdong Guangzhou510640 China Department of Mathematics Anhui Jianzhu University Anhui Hefei230601 China

This paper investigates a newly emerging recommendation strategy for online niche products, that is, a multichannel retailer recommends online niche products for instore shoppers. Such cross-channel recommendations make more customers aware of niche products, generating a positive information effect for the online channel. It also increases the interaction between online and offline channels. However, it is unclear how the provision of cross-channel recommendations influences the channel relationship when online and offline channels sell common products. Our analysis reveals that the cross-channel recommendation can increase the offline price and sales of common products, which benefits the offline channel. But the online sales of common products are decreased, causing a cannibalization effect on the online channel. The negative effect on common products can be dominated by the positive information effect on niche products when recommending a high-price niche product. In such case, the online channel benefits from cross-channel recommendations and channel synergy is achieved. From the perspective of a multichannel retailer, recommending high-price niche products to in-store shoppers can increase the retailer’s overall profit although the market for common product might shrink. Focusing on the target market with a high potential market scale of recommended customers and increasing the recommendation precision can make cross-channel recommendations more effective. © 2022, The Authors. All rights reserved.

关键词： Sales

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