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Hierarchical method of task assignment for multiple cooperating UAV teams

Journal of Systems Science & Complexity 2015年第5期28卷 1000-1009页

作者： Xiaoxuan Hu Huawei Ma Qingsong Ye He Luo School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education

The problem of task assignment for multiple cooperating unmanned aerial vehicle(UAV) teams is considered. Multiple UAVs forming several small teams are needed to perform attack tasks on a set of predetermined ground targets. A hierarchical task assignment method is presented to address the problem. It breaks the original problem down to three levels of sub-problems: target clustering, cluster allocation and target assignment. The first two sub-problems are centrally solved by using clustering algorithms and integer linear programming, respectively, and the third sub-problem is solved in a distributed and parallel manner, using a mixed integer linear programming model and an improved ant colony algorithm. The proposed hierarchical method can reduce the computational complexity of the task assignment problem considerably, especially when the number of tasks or the number of UAVs is large. Experimental results show that this method is feasible and more efficient than non-hierarchical methods.

关键词： unmanned aerial vehicle （UAV） task assignment clustering integer linear programming ant colony optimization（ACO） algorithm

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The selection of project management software by FAHP and FMCDM in automobile R&D process

The selection of project management software by FAHP and FMC...

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2nd International Conference on Networking and Digital Society, lCNDS 2010

作者： Fu, Lei Shi, Li Yang, Ying Yu, Bengong Key Laboratory of Process Optimization and Intelligent Decision-making School of Management Hefei University of Technology Hefei China

ISBN: (纸本)9781424451616

The selection of project management (PM) software is a complex issue and has significant impacts to the efficiency of the automobile research & development (R&D) process. Given two alternatives based on critical path method (CPM) and critical chain project management (CCPM) respectively, decision-makers usually cause confusion. This paper analyzed the characteristic of automobile R&D project and developed an evaluation model based on the fuzzy analytic hierarchy process (FAHP) and fuzzy multiple criteria decision making (FMCDM) methods, which can help the managers in automobile industry to select more appropriate software in the course of product R&D. In particular, the FAHP method is used to obtain the weights of evaluation criteria, and the FMCDM method is used to determine the final rank of the software. The uncertainty and vagueness in evaluation procedure were presented as the fuzzy triangular numbers. The proposed method is applied to the case study of evaluating the performance of PM software based on CPM and CCPM respectively for a car manufacturer. The result of evaluation not only assisted managers in choosing suitable software but also outline the trend in development of CCPM software. ©2010 IEEE.

关键词： Managers

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Heuristic algorithms for scheduling on uniform parallel machines with heads and tails

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Journal of Systems Engineering and Electronics 2011年第3期22卷 462-467页

作者： Kai Li Shanlin Yang School of Management Hefei University of TechnologyHefei 230009P.R.China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of EducationHefei University of TechnologyHefei 230009P.R.China

This paper considers the uniform parallel machine scheduling problem with unequal release dates and delivery times to minimize the maximum completion *** this NP-hard problem,the largest sum of release date,processing time and delivery time first rule is designed to determine a certain machine for each job,and the largest difference between delivery time and release date first rule is designed to sequence the jobs scheduled on the same machine,and then a novel algorithm for the scheduling problem is *** evaluate the performance of the proposed algorithm,a lower bound for the problem is *** accuracy of the proposed algorithm is tested based on the data with problem size varying from 200 jobs to 600 *** computational results indicate that the average relative error between the proposed algorithm and the lower bound is only 0.667%,therefore the solutions obtained by the proposed algorithm are very accurate.

关键词： scheduling parallel machine uniform release date/head delivery time/tail.

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Pricing and production strategies in remanufacturing from the perspectives of supply chain: Review and future directions

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Frontiers of Engineering management 2024年第1期11卷 1-15页

作者： Kai LI Yan LI Nenggui ZHAO School of Management Hefei University of TechnologyHefei 230009China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of EducationHefei 230009China

Remanufacturing is widely recognized as beneficial to the environment and a circular economy. However, remanufacturing is more complex than traditional manufacturing due to the effects of government policy, uncertainty of consumer preferences, competition and cooperation among firms, and so on. These factors motivate academics to optimize remanufacturing outcomes, especially for product pricing and production. This study reviews the published literature on pricing and production strategies in remanufacturing from four perspectives of supply chain, namely, government policy, consumer characteristics, relationships among firms, and supply chain structures. Review results can benefit scholars/practitioners in the future by highlighting the challenges and opportunities in remanufacturing strategies.

关键词： remanufacturing reverse and closed-loop supply chain circular economy

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A Credit management Mechanism for Peer-to-Peer Electricity Trading in Blockchain Environment 5

A Credit Management Mechanism for Peer-to-Peer Electricity T...

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

作者： Guo, Jinhuan Zhou, Kaile Chong, Jie Key Laboratory of Process Optimization and Intelligent Decision-making School of Management Hefei University of Technology Hefei230009 China

ISBN: (纸本)9781665434256

With the rapid development of distributed generation, peer-to-peer (P2P) electricity trading between microgrids in blockchain environment has become one of the indispensable ways to consume the local renewable energy. The existing credit management for P2P electricity trading generally realized through the smart contract of penalty, which cannot show the risk identification and risk aversion behaviors of each microgrid. Therefore, this study proposes a newly credit management mechanism to reduce the defaults, which achieves credit-based risk control optimization and credit-based continuous double auctions. In the first stage, microgrids make robust control optimize to submit a trading strategy that follows contracts as far as possible. In the second stage, which realizes rewards and penalties through credit-based equivalent price conversion. The experimental results show that the proposed credit management mechanism can improve microgrids' interests and ensure fair environment. © 2021 IEEE

关键词： Blockchain

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Optimal Operation Of Battery Energy Storage System In Industrial Park 5

Optimal Operation Of Battery Energy Storage System In Indust...

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

作者： Zhou, Kaile Zhang, Zenghui Lu, Xinhui Key Laboratory of Process Optimization and Intelligent Decision-making School of Management Hefei University of Technology Hefei230009 China

ISBN: (纸本)9781665434256

An industrial park containing distributed generations (DCs) can be seen as a microgrid. Due to the uncertainty and intermittency of the output of DGs, it is necessary to add battery energy storage system (BESS) in industrial parks. The battery state of health (SOH) is an important indicator of battery life. It is necessary to fully consider the battery SOH during the energy optimization of industrial parks. In this work, a two-stage model suitable for charge and discharge optimization of BESSs in industrial park microgrids is proposed. The first stage of the model is a charge and discharge scheduling of a BESS considering the SOH. This stage mainly schedules the charge and discharge time and the total amount of time. The second stage of the model is employed to further determine the charge and discharge allocation of all battery packs to achieve BESS life prolongation. The experimental results show that the introduction of SOH makes the scheduling results more realistic. Also, it balances the changes in the SOHs of all battery packs. © 2021 IEEE

关键词： Scheduling

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Multi-CODP decision models for supplier selection and order allocation in customized logistics service supply chain

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Neural Computing and Applications 2024年第19期36卷 11097-11119页

作者： Hu, Xiaojian Xu, Liangcheng Yao, Gang Wu, Zhening School of Management Hefei University of Technology Tunxi Anhui Hefei230009 China Key Laboratory of Process Optimization and Intelligent Decision-making Ministry of Education Tunxi Anhui Hefei230009 China

To address the problem of positioning customer order decoupling point (CODP) in customized logistics service supply chain and to provide logistics service integrators (LSI) with various CODP decision-making and supplier selection solutions. We consider LSI, logistics service providers (LSPs) and customers and propose multiobjective nonlinear team optimization models for multi-CODP location, including minimizing the cost to the LSI and maximizing the synthetic satisfaction of LSPs and customers. This paper adopts an improved nondominated sorting genetic algorithm (NSGA-II), in which the key modules such as the crossover operations, chromosome structure and mutation operations are reconstructed, to solve the team models and investigate the Pareto-optimal front for the two objectives. To demonstrate the validity of NSGA-II and the reliability of mathematical models, cases from a specific dataset are generated and solved. Moreover, a classic genetic algorithm (GA) is applied to solve for the two objectives separately. The optimal solutions found by GA are f1 = 2027.491, f2 = 0.7704 and f1 = 2454.512, f2 = 0.8909. The corresponding optimal solutions in the Pareto-optimal solution set are f1 = 2053.675, f2 = 0.7715 and f1 = 2427.114, f2 = 0.8843. We find that the optimal solutions provided by GA cannot dominate any solution in the Pareto-optimal solution set, indicating that the results are valid and sufficiently convergent. In summary, the results of this paper provide LSI with easy access to various supplier selection schemes with multi-CODP, which is essential to reduce the cognitive burden on decision makers and address the diverse customization needs of many challenging real-world logistics issues. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Genetic algorithms

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Compression of OLAP cubes for aggregate queries based on Copula approach

Compression of OLAP cubes for aggregate queries based on Cop...

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International Conference on Business Intelligence and Financial Engineering

作者： Gao, Yazhuo Ni, Zhiwei Ni, Liping School of Management Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-making Hefei 230009 China

ISBN: (纸本)9780769541167

This paper introduces Copula approach, which has been widely used in statistical field, to the construction of OLAP cubes for the first time. Based on this approach, a novel scheme is proposed to compress data and answer any OLAP query without accessing raw data. The procedure of this scheme can be generally divided into three steps. Firstly, find the proper distribution functions to fit the marginal distribution of each attribute. Secondly, employ Copula approach to catch the intra relationship among attributes in a data set. Finally, use the probability density function of joint distribution to calculate the aggregation function. Empirical evidence shows that this Copula-based model can not only drastically reduce storage requirements but also save the query response time, while the accuracy is bounded under a given level. © 2010 IEEE.

关键词： Distribution functions

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A Multi-dimensional Trust-aware Cloud Service Selection Mechanism Based on Evidential Reasoning Approach

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International Journal of Automation and computing 2015年第2期12卷 208-219页

作者： Wen-Juan Fan Shan-Lin Yang Harry Perros Jun Pei School of Management Hefei University of Technology Department of Computer Science North Carolina State University The Ministry of Education Key Laboratory of Process Optimization and Intelligent Decision Making Department of Industry and System Engineering University of Florida

In the last few years, cloud computing as a new computing paradigm has gone through significant development, but it is also facing many problems. One of them is the cloud service selection problem. As increasingly boosting cloud services are offered through the internet and some of them may be not reliable or even malicious, how to select trustworthy cloud services for cloud users is a big challenge. In this paper, we propose a multi-dimensional trust-aware cloud service selection mechanism based on evidential reasoning(ER) approach that integrates both perception-based trust value and reputation based trust value, which are derived from direct and indirect trust evidence respectively, to identify trustworthy services. Here, multi-dimensional trust evidence, which reflects the trustworthiness of cloud services from different aspects, is elicited in the form of historical users feedback ratings. Then, the ER approach is applied to aggregate the multi-dimensional trust ratings to obtain the real-time trust value and select the most trustworthy cloud service of certain type for the active users. Finally, the fresh feedback from the active users will update the trust evidence for other service users in the future.

关键词： Cloud service selection multi-dimensional trust evidence trust and reputation evaluation evidential reasoning(ER) clond service

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Two-stage charge and discharge optimization of battery energy storage systems in microgrids considering battery state of health 8

Two-stage charge and discharge optimization of battery energ...

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8th International Conference on Power and Renewable Energy, ICPRE 2023

作者： Zhang, Zenghui Zhou, Kaile Yang, Shanlin Hefei University of Technology Key Laboratory of Process Optimization and Intelligent Decision-Making School of Management Hefei230009 China

ISBN: (纸本)9798350328813

An important figure-of-merit for battery energy storage systems (BESSs) is their battery life, which is measured by the state of health (SOH). In this study, we propose a two-stage model to optimize the charging and discharging process of BESS in an industrial park microgrid (IPM). The first stage is used to optimize the charging and discharging time and the corresponding amount of the charging and discharging energy from the BESS, in which the SOH is considered. Subsequently, all battery packs need to be coordinated to ensure a reasonable BESS operation. In order to prolong the service life of the BESS, the second stage of the model allocates the charging and discharging of all battery packs on the basis of the first stage scheduling results. The proposed loss-calculation method is used to calculate the battery pack loss and then to calculate the SOHs of battery packs. It can be seen from the simulation results that the scheduling results considering the SOH are more realistic. Furthermore, the proposed charging and discharging allocation strategy can effectively coordinate the SOH change of all battery packs without causing a significant increase in the battery pack loss of the battery packs. © 2023 IEEE.

关键词： Battery energy storage system Charging and discharging optimization Industrial park microgrid State of health

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