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Solving traveling salesman problems by genetic algorithms

自然科学进展（英文版） 2003年第2期13卷 135-141页

作者： LIANG Yanchun GE Hongwei Zhou Chunguang LEE Heow Pueh LIN Wuzhong LIM Siak Piang LEE Kwok Hong College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Institute of High Performance Computing Singapore 117528 Singapore College of Mathematics Science Jilin University Changchun 130012 China College of Computer Science and Technology Jilin University Changchun 130012 China Institute of High Performance Computing Singapore 117528 Singapore Department of Mechanical Engineering National University of Singapore Singapore 119260 Singapore

The gene section ordering on solving traveling salesman problems is analyzed by numerical experiments. Some improved crossover operations are presented. Several combinations of genetic operations are examined and the functions of these operations are analyzed. The essentiality of the ordering of the gene section and the significance of the evolutionary inversion operation are discussed. Some results and conclusions are obtained and given, which provide useful information for the implementation of the genetic operations for solving the traveling salesman problem.

关键词： genetic algorithms traveling salesman problem gene section evolutionary inversion genetic operations

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Coverage and Exposure Paths in Wireless Sensor Networks

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Journal of computer science & Technology 2006年第4期21卷 490-495页

作者：黄刘生徐宏力汪炀吴俊敏李虹 Department of Computer Science and Technology University of Science & Technology of China Hefei 230027 P.R. China Anhui Province-Most Co-Key Laboratory of High Performance Computing and Its Application Hefei 230027 P.R. China

Wireless sensor networks have posed a number of challenging problems such as localization, deployment and tracking, etc. One of the interesting problems is the calculation of the coverage and exposure paths for the sensor networks. This paper presents a fully localized algorithm to solve the worst coverage problem first introduced by Meguerdichian et al. The nodes of the sensor network cooperate to construct the worst coverage path only by the one-hop neighbor＇s information, thus avoiding the massive communication and conserving the energy. The correctness of the proposed algorithm is proved formally under the sensing diminishing model. Moreover, this algorithm can be easily extended to solve the minimal exposure problem with local information as well.

关键词： coverage wireless sensor networks localized algorithm exposure

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Impact of selfish rate adaptation on the performance in IEEE 802.11-based wireless multi-hop networks

Impact of selfish rate adaptation on the performance in IEEE...

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28th International Conference on Distributed computing Systems Workshops, ICDCS Workshops 2008

作者： Li, Pei Xu, Yinlong Zhang, Chunpeng Department of Computer Science and Technology University of Science and Technology China Anhui Province High Performance Computing Key Laboratory

ISBN: (纸本)9780769531731

Multiple physical layer rates are supported in IEEE 802.11-based wireless networks, where links can adopt joint transmission power control and rate adaptation to achieve energy efficiency. This paper studies the selfish rate adaptation behavior under throughput requirement. A round-based non-cooperative game is proposed assuming there is only one link which can adjust its transmission strategy in each unit time. It is shown that there is an optimal transmission strategy for a link, and a greedy algorithm is presented to select a near-optimal transmission strategy. It is observed that scheduling order affects the feasibility and the total power consumption. To alleviate the influence of scheduling order, pricing function is introduced, which motivates selfish links to share the channel fairly and efficiently. Simulation results show the proposed approach leads to not only more feasible solutions, but also power efficiency. © 2008 IEEE.

关键词： Scheduling

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Towards design of a file location selection system in grid environments

Towards design of a file location selection system in grid e...

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1st International Conference on Hybrid Information Technology

作者： Wu, Tsung-Ying Li, Kuan-Ching Wang, Hsiao-Hsi Hsu, Ching-Hsien Cheng, Kuo-Yang Su, Wei-Shun Lee, Ming-Hsiao National Center of High-performance Computing Taiwan Department of Computer Science and Information Engineering Providence University Taiwan Department of Computer Science and Information Engineering Chung Hua University Taiwan

ISBN: (纸本)9780769526744

Data Grid is one of key factors to build up large-scale dataset storage system and providing high performance computing capacity, by connecting distributed resources in the Grid. One major challenge in data grids is how to provide good and timely access to huge amount of data in distributed locations, given the high latency of interconnection networks. Parallel downloading methods can improve download efficiency and performance, but the download process should have started from appropriate locations for such achievement. In this paper, we present the design of Location Selection System (LSS) for data grid environments, aiming at the problem of downloading locations. The proposed Location Selection System (LSS) not only provides users for setting their own priority strategies, but also provides two downloading modes, manual and automatic. The proposed techniques included as middleware over data grid platforms optimize Me downloads, by improving its efficiency and performance.

关键词： data grid SRB data location selection file selection

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Accumulative Time Based Ranking Method to Reputation Evaluation in Information Networks

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Journal of computer science & Technology 2022年第4期37卷 960-974页

作者： Hao Liao Qi-Xin Liu Ze-Cheng Huang Ke-Zhong Lu Chi Ho Yeung Yi-Cheng Zhang National Engineering Laboratory on Big Data System Computing Technology College of Computer Science and SoftwareEngineeringShenzhen UniversityShenzhen 518060China Guangdong Province Key Laboratory of Popular High Performance Computers Shenzhen UniversityShenzhen 518060China Guangdong Province Engineering Center of China-Made High Performance Data Computing System College of ComputerScience and Software EngineeringShenzhen UniversityShenzhen 518060China Institute of Big Data Intelligent Management and Decision Shenzhen UniversityShenzhen 518060China Department of Science and Environmental Studies The Education University of Hong KongHong Kong 999077China Department of Physics University of FribourgFribourg 1700Switzerland

Due to over-abundant information on the Web, information filtering becomes a key task for online users to obtain relevant suggestions and how to extract the most related item is always a key topic for researchers in various fields. In this paper, we adopt tools used to analyze complex networks to evaluate user reputation and item quality. In our proposed Accumulative Time Based Ranking (ATR) algorithm, we take into account the growth record of the network to identify the evolution of the reputation of users and the quality of items, by incorporating two behavior weighting factors which can capture the hidden facts on reputation and quality dynamics for each user and item respectively. Our proposed ATR algorithm mainly combines the iterative approach to rank user reputation and item quality with temporal dependence compared with other reputation evaluation methods. We show that our algorithm outperforms other benchmark ranking algorithms in terms of precision and robustness on empirical datasets from various online retailers and the citation datasets among research publications. Therefore, our proposed method has the capability to effectively evaluate user reputation and item quality.

关键词： temporal network behavior dynamics reputation evaluation ranking algorithm

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SPACE-TIME DISCONTINUOUS GALERKIN METHOD FOR MAXWELL EQUATIONS IN DISPERSIVE MEDIA

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Acta Mathematica Scientia 2014年第5期34卷 1357-1376页

作者：汪波谢资清张智民 College of Mathematics and Computer Science and Key Laboratory of High Performance Computing and Stochastic Information Processing (Ministry of Education of China) Hunan Normal University Beijing Computational Science Research Center Department of Mathematics Wayne State University

In this paper, a unified model for time-dependent Maxwell equations in dispersive media is considered. The space-time DG method developed in [29] is applied to solve the un-derlying problem. Unconditional L2-stability and error estimate of order O？τr＋1＋hk＋1/2？ are obtained when polynomials of degree at most r and k are used for the temporal dis-cretization and spatial discretization respectively. 2-D and 3-D numerical examples are given to validate the theoretical results. Moreover, numerical results show an ultra-convergence of order 2r＋1 in temporal variable t.

关键词： Maxwell equations dispersive media space-time DG method L2-stability L2-error estimate

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Finding tree symmetries using continuous-time quantum walk

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Chinese Physics B 2013年第5期22卷 124-131页

作者：吴俊杰张百达唐玉华强晓刚会权 State Key Laboratory of High Performance Computing National University of Defense Technology School of Computer National University of Defense Technology Center for Quantum Photonics H. H. Wills Physics Laboratory and Department of Electrical and Electronic EngineeringUniversity of Bristol

Quantum walk, the quantum counterpart of random walk, is an important model and widely studied to develop new quantum algorithms. This paper studies the relationship between the continuous-time quantum walk and the symmetry of a graph, especially that of a tree. Firstly, we prove in mathematics that the symmetry of a graph is highly related to quantum walk. Secondly, we propose an algorithm based on the continuous-time quantum walk to compute the symmetry of a tree. Our algorithm has better time complexity O（N3） than the current best algorithm. Finally, through testing three types of 10024 trees, we find that the symmetry of a tree can be found with an extremely high efficiency with the help of the continuous-time quantum walk.

关键词： quantum walk tree symmetry automorphism

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Study on optimization of agent initial positions in land combat simulation

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自然科学进展(英文版) 2004年第3期14卷 257-261页

作者： WU Chunguo LIANG Yanchun LEE Heow Pueh LU Chun Yang Xiaowei College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun 130012 China Institute of High Performance Computing Singapore 117528 Singapore Institute of High Performance Computing Singapore 117528 Singapore Department of Applied Mathematics South China University of Technology Guangzhou 510640 China Centre for ACES Department of Mechanical Engineering National University of Singapore 119260 Singapore

The use of computational-intelligence-based techniques in the optimization of agent initial positions in land combat simulations is studied. A novel method for the reduction of support vectors in the support vector machine (SVM) is presented. The optimization on the width of the Gaussian kernel function and the combination of the SVM with the radial basis function neural network are performed in the proposed method. Simulation results show that the proposed method can improve the running efficiency drastically compared with that using the traditional SVM with the same precision. We also summarize and present some experiences and trends in the study on the optimization problem in land combat simulation.

关键词： multi-agent support vector machine radial basis function genetic algorithm regression

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FaiResGAN: Fair and robust blind face restoration with biometrics preservation

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Image and Vision computing 2025年 160卷

作者： George Azzopardi Antonio Greco Mario Vento Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen The Netherlands Department of Information and Electrical Engineering and Applied Mathematics (DIEM) University of Salerno Italy National Research Council of Italy Institute for High Performance Computing and Networking Italy

Modern computer vision technologies enable systems to detect, recognize, and analyze facial features, but challenges arise when images are noisy, blurred, or low quality. Blind face restoration, which aims to recover high-quality facial images without prior knowledge of degradation, addresses this issue. In this paper, we introduce Fair Restoration GAN (FaiResGAN), a novel Generative Adversarial Network (GAN) designed to balance face restoration with the preservation of soft biometrics (identity, ethnicity, age, and gender). Our model incorporates a pseudo-random batch composition algorithm to promote fairness and mitigate bias, alongside a realistic degradation model simulating corruptions typical in surveillance images. Experimental results show that FaiResGAN outperforms state-of-the-art blind face restoration methods, both quantitatively and qualitatively. A user study involving 40 participants showed that FaiResGAN-restored images were preferred by 70% of users. Additionally, tests on VGGFace2, UTKFace, and FairFace datasets demonstrate FaiResGAN’s superior performance in preserving soft biometric attributes and ensuring fair restoration across different genders and ethnicities.

关键词： Blind face restoration Facial soft biometrics Face analysis Generative adversarial networks

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Research on Effectiveness of Contrastive Learning with Adversarial Examples for Different Downstream Tasks 3

Research on Effectiveness of Contrastive Learning with Adver...

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3rd IEEE International Conference on Frontiers Technology of Information and computer, ICFTIC 2021

作者： Zhang, Bin Sun, Yuxia Chen, Zhao Luo, Liang Xu, Yingmei Jinan University Guangdong Provincial Key Laboratory of High-Performance Computing Department of Computer Science Guangzhou China Jinan University Department of Computer Science Guangzhou China Guangdong Science Technology Infrastructure Center Guangdong Provincial Key Laboratory of High-Performance Computing Guangzhou China

ISBN: (纸本)9781665406055

Contrastive learning is a new self-supervised representation learning technique, which is considered to have great potential to improve the performance of downstream learning tasks. Recently, some researchers have conducted experiments on some datasets and found that contrastive learning based on adversarial examples can improve the performance of some image classification tasks. However, does contrastive learning with adversarial examples really benefit the performance of various downstream tasks? At present, there is still a lack of in-depth research on this issue. In this paper, we introduce a contrastive learning method with adversarial examples based on different adversarial perturbations intensities, and establish a variety of downstream image classification tasks. Experiments on different types of downstream tasks show that contrastive learning based on adversarial examples may not improve the performance of downstream tasks. We also find that the adversarial perturbation intensity and the proportion of the adversarial perturbation loss in contrastive loss are important factors affecting the above performance. © 2021 IEEE.

关键词： Image classification

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