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A fast bidirectional method for mining maximal frequent itemsets

A fast bidirectional method for mining maximal frequent item...

3rd International Joint Conference on Computational Sciences and optimization, CSO 2010: Theoretical Development and Engineering Practice

作者： Wang, Chao Ni, Zhi-Wei Guo, Jun-Fen Key Laboratory of Process Optimization and Intelligent Decision-making Hefei University of Technology Ministry of Education Heifei Hefei Anhui China

ISBN: (纸本)9780769540306

In this paper, a fast bidirectional method and an efficient data compression method for mining maximal frequent itemsets is proposed. A flexible search method is given, which exploits the advantages of bottom-up and up-bottom strategies. The compression technique use the Prime number characteristics to transform transaction data into a positive integer and can efficiently reduce the size of transaction database. This method can mine maximal frequent itemsets according to different user-defined mininum support with only one scan of original database. Theoretical and experimental analysis shows that the proposed method is scalable and efficient for mining maximal frequent itemsets. © 2010 IEEE.

关键词： Data compression

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A novel centralized cross-efficiency evaluation via explainable artificial intelligence in the context of big data

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European Journal of Operational Research 2025年

作者： Yang, Min Wang, Zixuan Liang, Liang Management School Hefei University of Technology Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-Making Ministry of Education Hefei230009 China Intelligent Interconnection System Anhui Provincial Laboratory Hefei230009 China NSFC Fundamental Research Center on Smart Interconnected System Engineering Hefei230009 China

Cross-efficiency evaluation in data envelopment analysis (DEA) assumes that decision making units (DMUs) have full flexibility in choosing weights according to their individual preferences. However, this total autonomy may be inapplicable in some centralized organizational scenarios. To address this problem, this paper introduces a novel centralized cross-efficiency evaluation which considers both individual and organizational preferences with assistance of explainable artificial intelligence (XAI) in the context of big data. Specifically, XAI is first applied to approach the organizational efficiency function and then calculate the marginal contribution of each variable as the variable importance, which represents the organizational preference. Furthermore, we propose a centralized secondary goal model to select the unique optimal weight profile from the candidate weights that remain self-efficiency as Pareto-optimal, such that the deviation between individual and organizational preferences is minimized. In addition, a centralization factor is introduced to ensure that the model's centralization degree corresponds to the actual centralization level in organizational management. Finally, the proposed method is applied to evaluate the efficiency of DMUs within three different centralized organizations sequentially. The results verify that the proposed method yields more discriminative and robust efficiency scores within organizations compared to several previous cross-efficiency evaluation methods. © 2025 Elsevier B.V.

关键词： Risk perception

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Exploring the impact of COVID-19 on travel behavior based on EV charging big data 5

Exploring the impact of COVID-19 on travel behavior based on...

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5th IEEE Conference on Energy Internet and Energy System Integration, EI2 2021

作者： Zhou, Kaile Hu, Dingding Li, Fangyi Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education School of Management Hefei University of Technology Hefei230009 China

ISBN: (纸本)9781665434256

The COVID-19 pandemic has forced many governments around the world to implement strict lockdown measures and order citizens to stay at home, which has caused a major change in travel patterns. This study leveraged electric vehicle charging big data in Hefei, Anhui Province, China to estimate electric vehicle charging demand in the absence of the COVID-19 pandemic using multi-layer perceptron model, which quantified the impact of the COVID-19 pandemic. In addition, we employed the vector autoregressive model to investigate the dynamic relationships between the changes in charging demand and various explanatory factors. The results suggest that the daily average charging demand in Hefei decreased by 78.3% compared to the predicted value during the pandemic. Furthermore, according to the variance decomposition and impulse response function analysis, national confirmed COVID-19 cases play a dominant role in reducing charging demand. The number of daily hospitalizations and Migration Scale Index also have significant and robust effect on the decrease in charging demand. The Air Quality Index and Baidu Index are susceptible to external factors and do not have a direct impact on the change in charging demand. Findings support a better understanding of changes in travel behavior during the pandemic and provide policy makers with references to deal with similar events. © 2021 IEEE

关键词： COVID-19

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Competition in durable goods markets with product failures into consideration 9

Competition in durable goods markets with product failures i...

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9th International Symposium on Project Management, ISPM 2021

作者： Tian, Jianfei Qian, Xiaofei School of management Hefei University of Technology Anhui China Key Laboratory of Process Optimization and Intelligent Decision-making of the Ministry of Education China

ISBN: (纸本)9781921712777

Few studies on competition in dual channel for durable goods take the product failures into consideration. However, the factors related to preventive maintenance (PM) and minimal maintenance (MM) have an important impact on the optimal profits of the manufacturer and retailer. Consequently, we develop three game models (Single Selling channel (SS), Manufacturer Stackelberg (MS) and Cooperation Model (CM)) to study the players’ equilibrium solutions and analyze the impact of the initial point, numbers and level of preventive maintenance on equilibrium price and profits. We find that the equilibrium wholesale and retail price under SS tend to increase when the manufacturer decides to raise the repair charge, while in MS the manufacturer and retailer will select a higher level for the wholesale price, retail price and rental charge when manufacturer chooses to put off the initial point for PM. In addition, numerical examples are provided to supplement our conclusions. The results show that the manufacturer in MS will set the numbers and level of PM to the maximum threshold in order to maximize its profit. © ISPM *** right reserved.

关键词： Preventive maintenance

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Distributed Event-Triggered Bandit Convex optimization With Time-Varying Constraints

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IEEE Transactions on Control of Network Systems 2025年

作者： Zhang, Kunpeng Yi, Xinlei Wen, Guanghui Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China Ministry of Education Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Shanghai201210 China Southeast University School of Automation Nanjing210096 China University of Groningen Engineering and Technology Institute Groningen Faculty of Science and Engineering GroningenAG 9747 Netherlands KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm10044 Sweden KTH Royal Institute of Technology Digital Futures Stockholm10044 Sweden

This paper considers the distributed bandit convex optimization problem with time-varying inequality constraints over a network of agents, where the goal is to minimize network regret and cumulative constraint violation. Existing distributed online algorithms solving this problem require that each agent broadcasts its decision to its neighbors at each iteration. However, communication resources are often limited. To better utilize communication resources, we propose a distributed event-triggered online primal-dual algorithm with two-point bandit feedback. Under several classes of appropriately chosen decreasing parameter sequences and non-increasing event-triggered threshold sequences, we establish dynamic network regret and network cumulative constraint violation bounds. These bounds are comparable to the results achieved by distributed event-triggered online algorithms with full-information feedback. Finally, a numerical example is provided to verify the theoretical results. © 2014 IEEE.

关键词： optimization algorithms

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Joint optimization of Production and Shipping for Small Orders Considering Less-Than-Container Loading 4th

Joint Optimization of Production and Shipping for Small Orde...

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4th International Conference on Resources and Environmental Research, ICRER 2022

作者： Tian, Yajing Wang, Guoqiang Chen, Yingying Luo, He School of Management Hefei University of Technology Hefei China Key Laboratory of Process Optimization & Intelligent Decision-Making Ministry of Education Hefei China

ISBN: (纸本)9783031318078

This paper introduces a joint optimization problem of production and shipping for overseas small orders considering less-than-container loading (LCL) in manufacturing enterprises. The problem consists of finding a production schedule together with a LCL shipping scheme simultaneously to minimize the total cost. An integer programming model is developed, and the genetic algorithm of enhanced elite reservation (SEGA) is used to solve large-sized instances. Besides, the performance of SEGA is compared with the classical genetic algorithm (SGA) and stallion genetic algorithm (stud GA). It is statistically shown that SEGA outperforms other algorithms in finding near-optimal solutions. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Loading

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Data stream closed frequent itemsets mining in blend window

Data stream closed frequent itemsets mining in blend window

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2012 International Conference on Computer Science and Service System, CSSS 2012

作者： Wu, Hao Wang, Huiying Li, Huaiying Jiang, Miao School of Management Hefei University of Technology India Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Hefei 230009 China

ISBN: (纸本)9780769547190

In data stream mining, sliding window can record the latest and most useful patterns, but the best size can not be accurately determined. To aim at data with the characteristics of data flow in some simulation systems, this paper proposes a method for mining the closed frequent patterns in the mixed window of data stream. The pattern of data stream could be completely recorded by scanning the stream only once. And the pruning method of T-Moment could reduce the space complexity of sliding window tree and the maintenance cost of the closed frequent patterns tree. To differentiate the historical and the latest patterns, a time decaying model was applied. The experimental results show that the algorithm has good efficiency and accuracy. © 2012 IEEE.

关键词： Forestry

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A hybrid ant colony algorithm for the Cutting Stock Problem

A hybrid ant colony algorithm for the Cutting Stock Problem

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2010 International Conference on Future Information Technology and Management Engineering, FITME 2010

作者： Peng, Jin Chu, Zhang Shu School of Management Hefei University of Technology Key Laboratory Process Optimization and Intelligent Decision-Making Ministry of Education Hefei Anhui Province China

ISBN: (纸本)9781424490882

This study presents a new hybrid ant colony algorithm (HACO) to solve an in integer linear programming formulation of the Cutting Stock Problem(CSP). The CSP is an important class combinatorial problem. It is appropriate to minimize the raw material used by industries for fulfilling customer's demands. In such cases, classic models for solving the cutting stock problem are useless. HACO consists of GDCP procedure and modified ACO (MACO). GDCP procedure provides dominative cutting patterns as MACO solution components, in MACO the pheromone trail is put on cutting patterns instead of items. MACO preserves cutting patterns and frequencies information under ants building solution procedure. Results obtained from computational experiments for ten benchmarks demonstrate that the performance of MACO is compared to that obtained using existing mete-heuristic algorithm. © 2010 IEEE.

关键词： Heuristic algorithms

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Multi agent negotiation model for distributed task allocation

Multi agent negotiation model for distributed task allocatio...

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2010 2nd IEEE International Conference on Information Management and Engineering, ICIME 2010

作者： Luo, He Hu, Xiao-Jian Hu, Xiao-Xuan School of Management Hefei University of Technology Hefei China Key Laboratory of Ministry of Education on Process Optimization and Intelligent Decision Making Hefei China

ISBN: (纸本)9781424452644

In the multi agent system, negotiation between different agents becomes more and more complex when the distributed tasks need to be allocated among them. Usually, this process has been done in the centralized way where agents have all the information of both the tasks and the environment. However, in the real application such as satellite scheduling problem or production scheduling problem, not all the information can be acquired, some of them even cannot be known. Therefore, in this paper, we propose a multi agent negotiation model for distributed task allocation in a priority based environment. This process is modeled as a finite Markov decision process (F-MDP), and a coordinated negotiation protocol is also suggested to support the model. The experiments show that tasks are allocated in an efficient way, and it can also reduce the communication cost. © 2010 IEEE.

关键词： Multi agent systems

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POLYNOMIAL DYNAMIC PROGRAMMING ALGORITHMS FOR LOT SIZING MODELS WITH BOUNDED INVENTORY AND STOCKOUT AND/OR BACKLOGGING

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Journal of Systems Science and Systems Engineering 2016年第3期25卷 370-397页

作者： Jinhong Zhong Feng Chu Chengbin Chu Shanlin Yang School of Management Hefei University of Technology Hefei 230009 China Laboratoire IBISC Universite d'Evry-Val d'Essone France Laboratoire Genie Industriel Ecole Centrale Paris France Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education Hefei China

This paper addresses a dynamic lot sizing problem with bounded inventory and stockout where both no backlogging and backlogging allowed cases are considered. The stockout option means that there is outsourcing in a period only when the inventory level at that period is non-positive. The production capacity is unlimited and production cost functions are linear but with fixed charges. The problem is that of satisfying all demands in the planning horizon at minimal total cost. We show that the no backlogging case can be solved in O（T^2） time with general concave inventory holding and outsourcing cost functions where T is the length of the planning horizon. The complexity can be reduced to O（T） when the inventory holding cost functions are also linear and have some realistic properties, even if the outsourcing cost functions remain general concave functions. When the inventory holding and outsourcing cost functions are linear, the backlogging case can be solved in O（ T^3 logT） time whether the outsourcing level at each period is bounded by the sum of the demand of that period and backlogging level from previous periods, or only by the demand of that period.

关键词： Dynamic lot sizing problem bounded inventory outsourcing backlogging stockout,dynamic programming

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