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Hidden influential node selection based on cost-benefit analysis for harmful information propagation control

JOURNAL OF INFORMATION SCIENCE 2025年第3期51卷 539-555页

作者： Liu, Zhaoli Sun, Qindong Li, Shancang Yang, Zhihai Zhang, Beibei Xian Univ Technol Sch Comp Sci & Engn Xian Peoples R China Xian Univ Technol Shaanxi Key Lab Network Comp & Secur Xian Peoples R China Univ West England Dept Comp Sci & Creat Technol Bristol England Xian Univ Technol Xian 710048 Peoples R China

The quick development of mobile network and smart devices provides a convenience way for information sharing in online social networks, which also accelerates the propagation of harmful information, thus how to select the hidden influential nodes with lower management cost for reducing the propagation speed of harmful information is an important task. In this article, we propose a greedy hidden influential node selection algorithm based on the epidemic model and cost-benefit analysis. First, we investigate the user behaviour dynamic characteristics from two perspectives of social relationships and interaction behaviours, and then susceptible and infected (SI) epidemic model is applied and user influence is estimated. Second, considering the management cost and benefit of different users, a greedy hidden influential node selection algorithm based on the cost-benefit analysis is proposed. Finally, a series of experiments are conducted using the public social network data set and the data set collected from Sina Weibo, to verify the performance and practicality of the developed method. The experimental results demonstrate that our method outperforms other related methods in harmful information propagation control.

关键词： Cost-benefit analysis epidemic model greedy algorithm propagation control

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Research on path smoothing optimisation based on improved RRT-Connect algorithm and third-order Bezier curve

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE 2025年第7期239卷 2544-2561页

作者： Zheng, Zhu-an Xie, Shuangjian Ye, Zimo Zheng, Xiangyu Yu, Zhiwei Yancheng Inst Technol Sch Automot Engn 1 Middle Hope Ave Yancheng 224000 Jiangsu Provinc Peoples R China

Aiming at the deficiencies of the original RRT-Connect path planning algorithm in dealing with obstacle avoidance, planning efficiency and path smoothing in static environments, an improved path optimisation method is proposed by fusing the RRT-Connect path planning algorithm with the greedy search strategy and using a third-order Bezier curve for path smoothing. Firstly, a greedy algorithm is added to the path planning process of the original RRT-Connect algorithm to guide the search direction, so as to make the path search more goal oriented, reduce the time of path planning and improve the efficiency. Secondly, the generated paths are smoothed with third-order Bezier curves to ensure the generation of smooth paths with continuous curvature and improve the quality of the planned paths. Finally, the improved RRT-Connect smoothing optimisation algorithm is simulated with the original RRT-Connect, A* and Dijkstra algorithms in different simulation environments to check the performance of the optimised algorithm. The results show that the success rate of obstacle avoidance in planning paths of the optimised algorithms are all 100%, and compared with the original RRT-Connect algorithm, the improved RRT-Connect smoothing optimisation algorithm has an overall reduction of 12.02% in planning path length, an overall reduction of 40.22% in computation time and an overall improvement of 69.15% in path smoothness. Compared to the A* algorithm, which is based on the graph search shortest path planning algorithm and takes the shortest time, there is an overall reduction of 62.46% in computation time. The improved RRT-Connect smoothing optimisation algorithm has shorter path planning lengths, smoother paths and shortest computation time in different simulation environments. Meanwhile, the stability of the optimisation algorithm is effectively improved in different environments and different running times.

关键词： Static obstacle avoidance improved RRT-Connect greedy algorithm Bezier curve smoothing process

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Crosstalk Delay and Reliability Analysis of Carbon Nanotube On-Chip Interconnects: Modelling and Optimization using Metaheuristic algorithm

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IETE JOURNAL OF RESEARCH 2025年第2期71卷 603-615页

作者： Sharma, Ritika Rai, Mayank Kumar Khanna, Rajesh Thapar Inst Engn & Technol Dept Elect & Commun Engn Patiala 147004 India

In the field of VLSI technology, the miniaturization of ICs poses significant challenges to overall interconnect performance, particularly due to the rising concerns of crosstalk-induced reliability and durability issues. This work explores graphene-based randomly mixed carbon nanotube bundle (RMCB) interconnects as a viable solution for advanced reliable VLSI applications. Employing metaheuristic algorithms (Maximum Hole Degree, Particle Swarm Optimization, Stoyan and Yaskov algorithm), this study seeks to optimize RMCB structures, maximizing carbon nanotube density within a fixed area. Notably, this study explores the effectiveness of algorithms' performance in optimizing RMCB structures at a nano-technology node. Extensive signal integrity and reliability assessments, considering both rugged and pristine substrates, reveal that Stoyan and Yaskov (SY)-based optimization excels over PSO and MHD-based counterparts in terms of on-chip interconnect performance and reliability. The SY structure significantly dominates MHD-based (and PSO) counterparts by reducing crosstalk delay by 50% (30%), enhancing the average failure rate by 40% (37%), and improving electromigration reliability by 170% (63%).

关键词： Average Failure Rate (AFR) greedy algorithm Particle Swarm Optimization (PSO) Randomly mixed carbon nanotube bundle (RMCB) VLSI Technology

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Design of Novel Auxetic Bi-Materials Using Convolutional Neural Networks

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MATERIALS 2025年第8期18卷 1772-1772页

作者： Coropetchi, Iulian Constantin Constantinescu, Dan Mihai Vasile, Alexandru Indres, Andrei Ioan Sorohan, Stefan Natl Univ Sci & Technol POLITEHN Bucharest Dept Strength Mat Splaiul Independetei 313 Bucharest 060042 Romania Mil Tech Acad Ferdinand I Fac Aircraft & Mil Vehicles George Cosbuc Blvd 39-49 Bucharest 050141 Romania Romanian Acad Inst Solid Mech Str Constantin Mille 15 Bucharest 010141 Romania

A convolutional neural network (CNN) was developed to predict the Poisson's ratio of representative volume elements (RVEs) composed of a bi-material system with soft and hard phases. The CNN was trained on a dataset of binary microstructure configurations, learning to approximate the effective Poisson's ratio based on spatial material distribution. Once trained, the network was integrated into a greedy optimization algorithm to identify microstructures with auxetic behavior. The algorithm iteratively modified material arrangements, leveraging the CNN's rapid inference to explore and refine configurations efficiently. The results demonstrate the feasibility of using deep learning for microstructure evaluation and optimization, offering a computationally efficient alternative to traditional finite element simulations. This approach provides a promising tool for the design of advanced metamaterials with tailored mechanical properties.

关键词： convolutional neural networks bi-material microstructures auxetic materials deep learning microstructure optimization greedy algorithm

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greedy algorithms for the single-demand facility location problem

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OPERATIONS RESEARCH LETTERS 2017年第5期45卷 452-455页

作者： Cheung, Sin-Shuen Williamson, David P. Cornell Univ Sch Operat Res & Informat Engn Ithaca NY 14853 USA

In this note, we give greedy approximation algorithms for the single-demand facility location problem inspired by the greedy algorithms for the min-knapsack problem originally given by Gens and Levner (1979) and later analyzed by Csirik et al. (1991). The simplest algorithm is a 2-approximation algorithm running in O(n log n) time;in general, we give a k+1/k-approximation algorithm running in O(n(k) log n) time. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Facility location Approximation algorithm greedy algorithm

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Research on the water-ground multimodal transport emergency scheduling model and decision-making method considering the actual road network inundation situation

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RISK ANALYSIS 2025年第3期45卷 600-622页

作者： Song, Yan Sun, Baiqing Han, Yunwu Xing, Zhenming Harbin Inst Technol Sch Management Harbin 150001 Peoples R China Jiangsu Vocat Coll Elect & Informat Dept Automobile Engn Huaian Peoples R China Harbin Inst Technol State Key Lab Robot & Syst Harbin Peoples R China

As urbanization continues to accelerate worldwide, urban flooding is becoming increasingly destructive, making it important to improve emergency scheduling capabilities. Compared to other scheduling problems, the urban flood emergency rescue scheduling problem is more complicated. Considering the impact of a disaster on the road network passability, a single type of vehicle cannot complete all rescue tasks. A reasonable combination of multiple vehicle types for cooperative rescue can improve the efficiency of rescue tasks. This study focuses on the urban flood emergency rescue scheduling problem considering the actual road network inundation situation. First, the progress and shortcomings of related research are analyzed. Then, a four-level emergency transportation network based on the collaborative water-ground multimodal transport transshipment mode is established. It is shown that the transshipment points have random locations and quantities according to the actual inundation situation. Subsequently, an interactive model based on hierarchical optimization is constructed considering the travel length, travel time, and waiting time as hierarchical optimization objectives. Next, an improved A* algorithm based on the quantity of specific extension nodes is proposed, and a scheduling scheme decision-making algorithm is proposed based on the improved A* and greedy algorithms. Finally, the proposed decision-making algorithm is applied in a practical example for solving and comparative analysis, and the results show that the improved A* algorithm is faster and more accurate. The results also verify the effectiveness of the scheduling model and decision-making algorithm. Finally, a scheduling scheme with the shortest travel time for the proposed emergency scheduling problem is obtained.

关键词： emergency rescue greedy algorithm improved A* algorithm scheduling scheme decision-making urban flooding water-ground multimodal transport

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greedy algorithms for packing unequal circles into a rectangular container

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2005年第5期56卷 539-548页

作者： Huang, WQ Li, Y Akeb, H Li, CM Univ Picardie LaRIA F-80039 Amiens France Huazhong Univ Sci & Technol Wuhan 430074 Peoples R China

In this paper, we study the problem of packing unequal circles into a two-dimensional rectangular container. We solve this problem by proposing two greedy algorithms. The first algorithm, denoted by B1.0, selects the next circle to place according to the maximum-hole degree rule, that is inspired from human activity in packing. The second algorithm, denoted by B1.5, improves B1.0 with a self-look-ahead search strategy. The comparisons with the published methods on several instances taken from the literature show the good performance of our approach.

关键词： circle packing problem combinatorial optimization greedy algorithm heuristic

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Hartree-Fock approximation for bosons with symmetry-adapted variational wave functions

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2025年 664卷

作者： Que, B. R. Zhang, J. M. Song, H. F. Liu, Y. Fujian Normal Univ Coll Phys & Energy Fujian Prov Key Lab Quantum Manipulat & New Energy Fuzhou Peoples R China Fujian Prov Collaborat Innovat Ctr Optoelect Semic Xiamen Peoples R China Inst Appl Phys & Computat Math Lab Computat Phys Beijing Peoples R China

The Hartree-Fock approximation for bosons employs variational wave functions that are a combination of permanents. These are bosonic counterpart of the fermionic Slater determinants, but with the significant distinction that the single-particle orbitals used to construct a permanent can be arbitrary and do not need to be orthogonal to each other. Typically, the variational wave function may break the symmetry of the Hamiltonian, resulting in qualitative and quantitative errors in physical observables. A straightforward method to restore symmetry is projection after variation, where we project the variational wave function onto the desired symmetry sector. However, a more effective strategy is variation after projection, which involves first creating a symmetry-adapted variational wave function and then optimizing its parameters. We have devised a scheme to realize this strategy and have tested it on various models with symmetry groups ranging from Z2, CL, to DL. In all the models and symmetry sectors studied, the variational wave function accurately estimates not only the energy of the lowest eigenstate but also the single-particle correlation function, as it approximate the target eigenstate very well on the wave function level. We have applied this method to study few-body bound states, superfluid fraction, and Yrast lines of some Bose-Hubbard models. This approach should be valuable for studying few-body or mesoscopic bosonic systems.

关键词： Hartree-Fock Variational wave function Permanent state Variation after projection greedy algorithm Bose-Hubbard model

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greedy algorithms for eigenvalue optimization problems in shape design of two-density inhomogeneous materials

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INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS 2011年第1期88卷 183-195页

作者： Zhang, Zheng-Fang Liang, Ke-Wei Cheng, Xiao-Liang Zhejiang Univ Dept Math Hangzhou 310027 Peoples R China

This paper studies the eigenvalue optimization problems in the shape design of the two-density inhomogeneous materials. Two types of greedy algorithms are proposed to solve three optimization problems in finite element discretization. In the first type, the whole domain is initialized by one density. For each problem of the eigenvalue optimizations, we define a measurement of the element, which is the criterion to determine the 'best' element. We change the density of the 'best' element to the other density. Then the algorithm repeats the procedure until the area constraint is satisfied. In the second type, the algorithm begins with the density distribution satisfying the area constraint. Also, according to the measurement of the element, the algorithm finds a pair of the 'best' elements and exchanges their densities between each other. Furthermore, the accelerating greedy algorithms are proposed to speed up both two types. Three numerical examples are provided to illustrate the results.

关键词： greedy algorithm inhomogeneous drum the eigenvalue optimization problem finite element method measurement

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Covering segments on aline with drones

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INFORMATION PROCESSING LETTERS 2025年 188卷

作者： Bereg, Sergey Diaz-Banez, Jose-Miguel Kasiuk, Alina Perez-Cutino, Miguel-Angel Rodriguez, Fabio Univ Texas Dallas Dept Comp Sci Richardson TX 75080 USA Univ Seville Dept Appl Math Seville Spain

Covering a set of segments in a plane with vehicles of limited autonomy is a problem of practical interest. The limited battery endurance imposes periodical visits to a static base station. Typically, two optimization problems are considered: minimize the number of tours, and minimize the total traveled distance. In a general setting, the problems are NP-hard and in this letter, we study the one-dimensional version. For covering segments on a line, we design efficient solutions for both optimization problems. First, we design a greedy algorithm that is optimal for the first task, and for both tasks when only one segment is considered. Being n and m the number of segments and tours of an optimal solution, respectively, our algorithm runs in O(m + n) time. For the second criterion, our solution is based on Dynamic Programming and runs in O(n2m) time.

关键词： Covering segments Autonomous vehicles greedy algorithm Dynamic programming

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