检索结果-内蒙古大学图书馆

Global Conference on Digital Design and Manufacturing Technology

作者： Zhao, Y. W. Zhang, J. L. Peng, D. J. Zhejiang Univ Technol MOE Key Lab Mech Mfg & Automat Hangzhou 310014 Zhejiang Peoples R China

ISBN: (纸本)087849278X

Open vehicle routing problem is a kind of special vehicle routing problem, in which the vehicles do not return the depots after completing the task. Aiming at open vehicle routing problem, the mathematical model was founded by introducing virtual depots. A quantum evolutionary algorithm combined with local optimization algorithms was proposed in this paper, in which 0-1 matrix encoding was used to construct chromosomes, rotation gate with adaptively adjusting rotation angle was used to realize evolution, nearest neighbors and 2-Opt were incorporated to further improve solutions. Based on benchmark problems, the algorithm's parameters were discussed, and the computation result was compared to those of other algorithms. The Computation results indicated that the proposed algorithm was an efficient method for solving open vehicle routing problem.

关键词： Open vehicle routing problem quantum evolutionary algorithm Rotation gate Local optimization algorithm

来源：评论

学校读者我要写书评

暂无评论

A hybrid quantum evolutionary algorithm for solving engineering optimization problems

引用

International Journal of Hybrid Intelligent Systems 2010年第3期7卷 225-235页

作者： Mani, Ashish Patvardhan, C. Department of Electrical Engineering Faculty of Engineering Dayalbagh Educational Institute Dayalbagh Agra India

evolutionary algorithms (EA) have been successfully employed for solving difficult constrained engineering optimization problems. However, EA implementations often suffer from premature convergence due to the lack of proper balance between exploration and exploitation in the search process. This paper proposes a Hybrid quantum inspired EA, which balances the exploration and exploitation in the search process by adaptively evolving the populations. It employs an adaptive quantum rotation based crossover operator designed by hybridizing a conventional crossover operator with the principles of quantum Mechanics. The degree of rotation in this operator is determined adaptively. The proposed algorithm does not require either a mutation operator, to avoid premature convergence, or a local heuristic to improve convergence rate. Further, a parameter-tuning free hybrid technique is employed for handling constraints, which overcomes some limitations in the traditional techniques like penalty factor methods, by hybridizing Feasibility Rules method with Adaptive Penalty Factor method. It is implemented by using two populations, each evolving by applying one of the constraints handling techniques and swapping a part of the populations. A standard set of six diverse benchmark engineering design optimization problems have been used for testing the proposed algorithm. The algorithm exhibits superior performance than the existing state-of-the-art approaches.

关键词： quantum evolutionary algorithm constrained optimization hybrid constraint handling Adaptive

来源：评论

学校读者我要写书评

暂无评论

Multi-objective quantum-inspired Cultural algorithm 2

Multi-objective Quantum-inspired Cultural Algorithm

引用

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

来源：评论

学校读者我要写书评

暂无评论

Self-organizing quantum evolutionary algorithm Based on quantum Dynamic Mechanism

Self-organizing Quantum Evolutionary Algorithm Based on Quan...

引用

International Conference on Artificial Intelligence and Computational Intelligence

作者： Liu, Sheng You, Xiaoming Shanghai Univ Engn Sci Sch Management Shanghai 200065 Peoples R China

ISBN: (纸本)9783642052521

A novel self-organizing quantum evolutionary algorithm based on quantum Dynamic mechanism for global optimization (DQEA) is proposed. Firstly, population is divided into subpopulations automatically. Secondly, by using co-evolution operator each subpopulation can obtain optimal solutions. Because of the quantum evolutionary algorithm with intrinsic adaptivity it can maintain quite nicely the population diversity than the classical evolutionary algorithm. In addition, it can help to accelerate the convergence speed because of the co-evolution by quantum dynamic mechanism. The searching technique for improving the performance of DQEA has been described;self-organizing algorithm has advantages in terms of the adaptability;reliability and the learning ability over traditional organizing algorithm. Simulation results demonstrate the superiority of DQEA in this paper.

关键词： quantum evolutionary algorithm quantum dynamic mechanism Self-organizing and co-evolution

来源：评论

学校读者我要写书评

暂无评论

Improved quantum evolutionary algorithm Combined with Chaos and Its Application

引用

6th International Symposium on Neural Networks

作者： Xiao, Jianhua Nankai Univ Res Ctr Logist Tianjin 300071 Peoples R China

ISBN: (纸本)9783642015120

quantum evolutionary algorithm (QEA) has been developed rapidly and has been applied widely during the past decade. In this paper, an improved quantum evolutionary algorithm (IQEA) is presented based on particle swarm optimization (PSO) and chaos. The simulation results in solving DNA encoding demonstrate that the improved quantum evolutionary algorithm is valid and outperforms the quantum chaotic swarm evolutionary algorithm and conventional evolutionary algorithm. abstract environment.

关键词： quantum evolutionary algorithm Particle swarm optimization Chaos Optimization DNA encoding problem

来源：评论

学校读者我要写书评

暂无评论

A Fast Watermarking algorithm Based on quantum evolutionary algorithm

A Fast Watermarking Algorithm Based on Quantum Evolutionary ...

引用

IEEE International Conference on Intelligent Computing and Intelligent Systems

作者： Wang, Zhiwen Li, Shaozi Cai, Qixian Su, Songzhi Liu, MeiZhen GXU Dept Comp & Engn Liuzhou Peoples R China Xiamen Univ Dept Comp Sci Xiamen Peoples R China Guangxi Univ Library Liuzhou Peoples R China Xiamen Univ Dept Cognit Sci Xiamen Peoples R China

ISBN: (纸本)9781424447541

There are limitations in smaller embedded information capacity, lower accurate rate for positioning embedded location and detection, slower running speed in traditional watermarking algorithm which combines spatial domain and transform domain based on characteristics of human visual system A Fast Watermarking algorithm based on quantum evolutionary algorithm is proposed and implemented We carry through simulation experiments by using the new algorithm brought forward in this article Results of experiments show that the new algorithm owns not only faster watermark image generation, but also have good sensitivity and robustness for all kinds of attacks The new algorithm is more flexible in application, can be embedded more information, can quicken computing speed, can easily operate and so on

关键词： quantum evolutionary algorithm wavelet transform quantification robustness Watermark Detection

来源：评论

学校读者我要写书评

暂无评论

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

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

A Fast Watermarking algorithm Based on quantum evolutionary algorithm

A Fast Watermarking Algorithm Based on Quantum Evolutionary ...

引用

2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(ICIS2009)

作者： Zhiwen WANG 1,2 1.Department of Computer & Engineering,GXU 2.Cognitive Science Department of Xiamen University T Liuzhou,China Shaozi LI 1 Cognitive Science Department of Xiamen University Xiamen,China Qixian CAI 2 Department of Computer & Engineering,GXUT Liuzhou,china Songzhi SU 1 Cognitive Science Department of Xiamen University Xiamen,China MeiZhen LIU 3 Library,Guangxi University of Technology Liuzhou,china

There are limitations in smaller embedded information capacity,lower accurate rate for positioning embedded location and detection,slower running speed in traditional watermarking algorithm which combines spatial domain and transform domain based on characteristics of human visual system.A Fast Watermarking algorithm based on quantum evolutionary algorithm is proposed and *** carry through simulation experiments by using the new algorithm brought forward in this *** of experiments show that the new algorithm owns not only faster watermark image generation,but also have good sensitivity and robustness for all kinds of *** new algorithm is more flexible in application,can be embedded more information,can quicken computing speed;can easily operate and so on.

关键词： quantum evolutionary algorithm wavelet transform quantification robustness Watermark Detection

来源：评论

学校读者我要写书评

暂无评论

A Novel quantum Immune algorithm for Multiobjective Flexible Job Shop Scheduling

引用

INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS 2014年第5期23卷 1450006-1450006页

作者： Davarzani, Zohreh Akbarzadeh-T, Mohammad-R. Payame Noor Univ Dept Comp Engn Tehran 193954697 Iran Ferdowsi Univ Mashhad Ctr Excellence Soft Comp & Intelligent Informat P Dept Elect & Comp Engn Mashhad Iran

In this study, a hybrid of quantum evolutionary and Artificial Immune algorithms (QIA) is proposed for solving Multiobjective Flexible Job Shop Scheduling Problem (MFJSSP). This problem is formulated as three-objective problem which minimizes completion time (makespan), critical machine workload and total work load of all machines. The quantum coding is shown to improve the immune strategy. The proposed algorithm overcomes the problem by increasing the speed of convergence and diversity of population. Three benchmarks of Kacem and Brandimart are examined to evaluate the performance of the proposed algorithm. The experimental results show a better performance in comparison to other approaches.

关键词： Flexible job shop scheduling immune algorithm (IA) quantum evolutionary algorithm

来源：评论

学校读者我要写书评

暂无评论

Parallel quantum evolutionary algorithms with Client-Server Model for Multi-Objective Optimization on Discrete Problems

Parallel Quantum Evolutionary Algorithms with Client-Server ...

引用

IEEE Congress on evolutionary Computation (CEC)

作者： Wei, Xin Fujimura, Shigeru Waseda Univ Grad Sch Informat Prod & Syst Wakamatsu Ku Kitakyushyu Fukuoka 8080135 Japan

ISBN: (纸本)9781467315098

This paper proposes a parallel quantum evolutionary algorithm (PQEA) using Client-Server model for multi-objective optimization problems. Firstly, the PQEA uniformly decomposes a multi-objective optimization problem into a number of scalar optimization sub-problems. All the sub-problems are classified into several groups according to their similarities. Each "Client" processes the evolution for a group of neighbor sub-problems in parallel. There is a quantum individual used to address the sub-problems of a group in a "Client". Since the quantum individual is a probabilistic representation, it can share evolutionary information of the neighbor sub-problems in one group, while the sub-problems are orderly solved using a same q-bit individual. The "Server" maintains non-dominated solutions that are generated by every "Client". The current best solution for each sub-problem can be found in the "Server", when the quantum individual updated its states for evolution. Experimental results have demonstrated that PQEA obviously outperforms the most famous multi-objective optimization algorithms MOEA/D on the bi-objectives. For the more objectives, the PQEA obtains the similar results with MOEA/D, even with the same evaluation times. Furthermore, in this paper, the scalability and sensitivity of PQEA have also been experimentally investigated.

关键词： quantum evolutionary algorithm Parallel Multi-Objective Optimization Pareto Front

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：