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检索条件"主题词=Quantum evolutionary algorithm"

共 65 条记录，以下是51-60 订阅

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Research on multi-vehicle scheduling problem based on dynamic demand

Research on multi-vehicle scheduling problem based on dynami...

引用

International Conference on Intelligent Transportation, Big Data and Smart City (ICITBS)

作者： Nie, Jun GuangDong Coll Sci & Technol Dept Comp Sci Dongguan 523083 Peoples R China

ISBN: (纸本)9781509004645

After analyzing the dynamic vehicle scheduling problem (DVSP), the DVSP is transformed into the static vehicle scheduling problem (SVSP) at different times of the time axis, and the dynamic demand of the DVSP model is established.A quantum inspired evolutionary algorithm based on DVSP is designed, and the two phase decoding strategy of "first line grouping" is used to construct the quantum chromosome, and the crossover operator is designed by using the genetic code of two 0. Finally, the algorithm is verified and analyzed. The results show that the algorithm has better convergence ability, convergence speed and high efficiency.

关键词： Dynamic demand vehicle scheduling quantum evolutionary algorithm

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Scheduling a Fuzzy Flowshop Problem to Minimize Weighted Earliness-tardiness

Scheduling a Fuzzy Flowshop Problem to Minimize Weighted Ear...

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第25届中国控制与决策会议

作者： Ping Yan Ming-hai Jiao Li-qiang Zhao School of Economics and Management Shenyang Aerospace University Computing Center Northeastern University

ISBN: (纸本)9781467355339

The flowshop scheduling problem with fuzzy processing times is concerned in this paper. A triangular fuzzy number is used to represent the uncertainty processing times of jobs. The due windows have been assigned to all jobs. If a job is completed within its due window, then it incurs no scheduling cost. Otherwise, an earliness or tardiness cost is incurred. The objective is to find a job schedule such that the weighted sum of earliness and tardiness penalties of jobs is minimized. Schedules are generated by a proposed hybrid algorithm in the context of quantum evolutionary algorithm and particle swarm optimization approach. Three novel coding schemes are designed for transforming an individual into a sequence of jobs. Furthermore, a velocity disturbance strategy is also introduced into the proposed algorithm to improve the diversity of the swarm. The simulation results show that the proposed algorithm is able to obtain higher quality solutions stably and efficiently in the fuzzy flowshop scheduling problem.

关键词： Flowshop scheduling Fuzzy processing time Particle swarm optimization quantum evolutionary algorithm

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An evolutionary Approach for Probabilistic Temporal Fuzzy Controllers

An Evolutionary Approach for Probabilistic Temporal Fuzzy Co...

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2nd International Conference on Computer and Automation Engineering (ICCAE)

作者： Bazrafshan, Fazel Mojallali, Hamed Islamic Azad Univ Qazvin Branch Dept Elect & Comp Engn Qazvin Iran Univ Guilan Fac Engn Dept Elect Engn Rasht Iran

ISBN: (纸本)9781424455690

Temporal fuzzy systems are powerful systems that use temporal information in their reasoning process. Probabilistic fuzzy systems are the systems that combine the advantages of probabilistic and fuzzy uncertainty with each other. In this paper, we propose a novel approach, which combines the advantages of probabilistic fuzzy systems with temporal fuzzy systems. The proposed algorithm uses an evolutionary algorithm to find the parameters of the system. In order to examine the proposed method, a fuzzy controller for an overhead crane system is designed. Simulation results show that the proposed method has better performance than other methods.

关键词： Probabilistic fuzzy system Temporal fuzzy system quantum evolutionary algorithm

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A Free-Weighting Matrix Approach to Wide-area Coordinated Control among Multiple FACTS Devices 36

A Free-Weighting Matrix Approach to Wide-area Coordinated Co...

引用

36th Chinese Control Conference (CCC)

作者： Xu Shiyun Yi Jun Ma Shicong Chu Xiaojie Dong Zichen Chen Zhanming China Elect Power Res Inst State Key Lab Power Grid Safety & Energy Conserva Beijing 100192 Peoples R China Heibei Port Grp Int Hong Kong Co Ltd Hong Kong 999077 Hong Kong Peoples R China Renmin Univ China Beijing 100872 Peoples R China

ISBN: (纸本)9789881563934

With the wide application of flexible AC transmission system (FACTS) in power system, one of the major directions of FACTS development is the research of multi-FACTS coordinated control (MFCC) based on wide-area measurement system (WAMS). Since time-delay is unavoidable in WAMS, this study concentrates on the anti-delay coordinated control algorithm based on free-weighting matrix approach which utilizes the output feedback signals from WAMS. By taking time delay into consideration, the proposed algorithm ensures the minimum ratio of time-delay system, and the optimal gain of MFCC can be obtained through the quantum evolutionary algorithm. The validity and applicability of the proposed coordinated control algorithm is demonstrated in a four-machine, two-area system.

关键词： FACTS wide-area coordinated control linear matrix inequality (LMI) quantum evolutionary algorithm time delay

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A Secure Computing Offload Approach for Power Services Based on 5G Edge Computing 6

A Secure Computing Offload Approach for Power Services Based...

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6th IEEE Advanced Information Technology, Electronic and Automation Control Conference (IEEE IAEAC)

作者： Yu, Yue Wang, Wei Wu, Hao Qiu, Lanxin Xu, Yangzhou State Grid Smart Grid Res Inst Co Ltd Beijing Peoples R China State Grid Lab Elect Power Commun Network Technol Beijing Peoples R China State Grid Ningbo Elect Power Supply Co Ningbo Peoples R China State Grid Zhejiang Elect Power Co Informat & Telecommun Branch Zhenjiang Jiangsu Peoples R China

ISBN: (数字)9781665458641

ISBN: (纸本)9781665458641

The integration of 5G and energy Internet has enriched the type of electric power business and improved the quality of electric power business bearing. The power business under the new situation puts forward higher requirements on the communication delay and data security of 5G network. A power multi-service computational offloading method with the assistance of data security transmission is proposed. First, the communication model, computational offloading model and security model under 5G edge computing scenario are constructed, followed by the establishment of computational offloading and resource allocation strategy optimization function for business requirements, and finally, an improved offloading algorithm based on quantum evolutionary algorithm is proposed to solve the problem. The simulation results show that the proposed service offloading method can reduce the total system overhead as much as possible while ensuring security, effectively improving the security problem and service delay optimization problem brought by the open 5G capability, and comparing with the offloading strategies proposed in two related works, the results prove that the proposed improved offloading algorithm based on quantum evolutionary algorithm can effectively reduce the system energy consumption and delay.

关键词： energy interconnection 5G mobile edge computing computation offloading data security quantum evolutionary algorithm

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Solving a Single Machine Scheduling Problem with Uncertain Demand Using QPSO algorithms

Solving a Single Machine Scheduling Problem with Uncertain D...

引用

第25届中国控制与决策会议

作者： Ping Yan Ming-hai Jiao Xu Yao School of Economics and Management Shenyang Aerospace University Computing Center Northeastern University Institute Scientific & Technical Information of Liaoning Province

ISBN: (纸本)9781467355322

By considering the imprecise or fuzzy nature of the data in real-world problems, a single machine scheduling problem with uncertainty demand is investigated. A triangular fuzzy number is used to represent the uncertainty demand, and a half-trapezoid one is employed to represent fuzzy duedate. On the basis of the agreement index of fuzzy duedate and fuzzy completion time, this problem is formulated with the objective to maximize the total weighting agreement indexes for all the customer orders. We presented a hybrid algorithm QPSO of particle swarm optimization （PSO） and quantum evolutionary algorithm （QEA） to solve this problem. In the proposed QPSO, some novel coding schemes are designed for transforming a particle into a feasible process sequence of customer orders. Moreover, a mutation mechanism is also introduced into the QPSO and improves the diversity of the swarm greatly. The feasibility and effectiveness of the proposed QPSO is demonstrated by some simulation experiments.

关键词： Single machine scheduling Fuzzy demand Particle swarm optimization quantum evolutionary algorithm

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Multi-objective quantum-inspired Cultural algorithm 2

Multi-objective Quantum-inspired Cultural Algorithm

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2nd International Conference on Soft Computing and Machine Intelligence (ISCMI)

作者： Guo, Yi-nan Zhang, Pei China Univ Min & Technol Sch Informat & Elect Engn Xuzhou Peoples R China

ISBN: (纸本)9781467398190

It had been proved that the knowledge may promote more efficient evolution. Considering the knowledge defined in different form, we present multi-objective quantum-inspired cultural algorithms so as to effectively utilize the implicit information embodied in the evolution to promote more efficient search. The dual structure derived from cultural algorithm was adopted. In population space, the rectangle's height of each allele in quantum individuals was calculated in terms of non-dominated rank by sorting among individuals, instead of the relative fitness values. In belief space, the knowledge memorized the distribution and location about the non-dominated individuals' objective values in the objective space and directed the mutation and selection operations so as to influence the update of quantum individuals further. The statistical simulation results for five benchmark functions indicated that the proposed algorithm keeps the diversity of population better and obtains more uniform pareto-optimal solutions near the true pareto front.

关键词： knowledge the crowding degree quantum evolutionary algorithm cultural algorithm multi-objective optimization

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quantum Binary Shuffled Frog Leaping algorithm

Quantum Binary Shuffled Frog Leaping Algorithm

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3rd International Conference on Instrumentation & Measurement, Computer, Communication and Control (IMCCC)

作者： Wang, Lianguo Gong, Yaxing Gansu Agr Univ Coll Informat Sci & Technol Lanzhou Peoples R China Gansu Agr Univ Coll Engn Lanzhou Peoples R China

ISBN: (纸本)9780769551227

A quantum binary shuffled frog leaping algorithm (QBSFLA) is proposed through integrating the theories of the quantum evolutionary algorithm and the shuffled frog leaping algorithm (SFLA). Firstly, the superposition state characteristic of quantum makes the separate individual expresses more states, and the probability expression characteristic makes individuals' states are expressed with certain probability for increasing the diversity of the population potentially. Then, SFLA is used to regulate the phrase of the quantum bit to achieve a balance of the local and global search and improve the run speed. The experimental results of three 0-1 knapsack problems solved by QBSFLA with the greedy algorithm show that QBSFLA has several advantages such as fast convergence, powerful global search ability and good stability.

关键词： swarm intelligence shuffled frog leaping algorithm quantum evolutionary algorithm knapsack problem greedy algorithm binary system

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A Multi-horizon, Multi-objective Training Planner: Building the Skills for Manufacturing

A Multi-horizon, Multi-objective Training Planner: Building ...

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25th International Workshop on Neural Networks (WIRN)

作者： Pinzone, Marta Fantini, Paola Fiasche, Maurizio Taisch, Marco Politecn Milan Dept Management Econ & Ind Engn Piazza Leonardo da Vinci 32 I-20100 Milan Italy

ISBN: (纸本)9783319337470

Fast technological progress and the dynamics generated by economic, ecological and societal mega-trends are putting manufacturing companies under strong pressure to radically change the way in which they operate and innovate. Consequently, human work in manufacturing is also visibly changing and the need to up-skill and re-skill workers is rapidly increasing in order to sustain industry competitiveness and innovativeness as well as employability. Life-long training is therefore crucial to achieve the vision of a successful and socially sustainable manufacturing ecosystem in which industry, society and individuals can thrive together. In this paper we present a novel training planner, which provides worker-specific training recommendations based on workers' knowledge, skills and preferences, job content and allocation statistics, and factory demands. Multiple objectives, related to economic and social performances are taken into account.

关键词： Training Manufacturing Worker-centric Mathematical model MOLP Multi-objective Multi-horizon quantum evolutionary algorithm

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QoS Routing Based on Parallel Elite Clonal quantum Evolution for Multimedia Wireless Sensor Networks

QoS Routing Based on Parallel Elite Clonal Quantum Evolution...

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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Zhou, Jie Dutkiewicz, Eryk Liu, Ren Ping Fang, Gengfa Liu, Yuanan Macquarie Univ Dept Engn N Ryde NSW 2109 Australia Beijing Univ Posts & Telecommun Sch Elect Engn Beijing Peoples R China CSIRO Canberra ACT Australia

ISBN: (纸本)9781479930838

Quality of Service (QoS) routing is one of the key enabling techniques for multimedia wireless sensor networks (WSNs). However, the multi-constraints QoS routing problem is an NP-hard problem, and the computational complexity of an exhaustive search over all the paths is too high for large scale multimedia WSNs. In this paper, a novel parallel elite clonal quantum evolutionary algorithm is proposed to solve the multi-constraints QoS routing problem. The proposed algorithm minimizes the energy consumption, while guaranteeing QoS performance, including delay, bandwidth, delay jitter and packet loss rate, in multimedia WSNs. The algorithm is tested by extensive simulations and its performance is compared with the genetic algorithm and ant colony optimization. Simulation results demonstrate that the proposed algorithm achieves lower energy consumption at a faster convergence rate than the other two evolutionary algorithms.

关键词： multimedia wireless sensor networks quality of service unicast routing quantum evolutionary algorithm

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