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Smart Bubble Sort:A Novel and Dynamic Variant of Bubble Sort Algorithm 认领 引用
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作者 Mohammad Khalid Imam Rahmani 《Computers, Materials & Continua》 SCIE EI 2022年第6期4895-4913,共19页
In the present era,a very huge volume of data is being stored in online and offline databases.Enterprise houses,research,medical as well as healthcare organizations,and academic institutions store data in databases an... In the present era,a very huge volume of data is being stored in online and offline databases.Enterprise houses,research,medical as well as healthcare organizations,and academic institutions store data in databases and their subsequent retrievals are performed for further processing.Finding the required data from a given database within the minimum possible time is one of the key factors in achieving the best possible performance of any computer-based application.If the data is already sorted,finding or searching is comparatively faster.In real-life scenarios,the data collected from different sources may not be in sorted order.Sorting algorithms are required to arrange the data in some order in the least possible time.In this paper,I propose an intelligent approach towards designing a smart variant of the bubble sort algorithm.I call it Smart Bubble sort that exhibits dynamic footprint:The capability of adapting itself from the average-case to the best-case scenario.It is an in-place sorting algorithm and its best-case time complexity isΩ(n).It is linear and better than bubble sort,selection sort,and merge sort.In averagecase and worst-case analyses,the complexity estimates are based on its static footprint analyses.Its complexity in worst-case is O(n2)and in average-case isΘ(n2).Smart Bubble sort is capable of adapting itself to the best-case scenario from the average-case scenario at any subsequent stages due to its dynamic and intelligent nature.The Smart Bubble sort outperforms bubble sort,selection sort,and merge sort in the best-case scenario whereas it outperforms bubble sort in the average-case scenario. 展开更多
关键词 Sorting algorithms smart bubble sort footprint dynamic footprint time complexity asymptotic analysis
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SORT目标检测算法研究 认领 引用
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作者 朱萌博 《软件》 2026年第2期28-30,共3页
SORT(Simple Online and Realtime Tracking)算法作为一种经典的基于检测的多目标跟踪算法,凭借简单高效、实时性的特点受到广泛关注。本文对SORT目标检测算法进行研究,首先,剖析了算法的核心原理,包括卡尔曼滤波器、匈牙利算法和IOU等... SORT(Simple Online and Realtime Tracking)算法作为一种经典的基于检测的多目标跟踪算法,凭借简单高效、实时性的特点受到广泛关注。本文对SORT目标检测算法进行研究,首先,剖析了算法的核心原理,包括卡尔曼滤波器、匈牙利算法和IOU等关键组件;其次,梳理了算法的完整流程,并进行SORT算法的性能分析与实验验证;最后,梳理了SORT算法的改进思路与优化策略。研究表明,SORT算法在平稳运动目标跟踪场景中表现优异,在目标遮挡、快速运动等复杂场景中仍需改进。未来可通过融合多特征和优化数据关联策略等方式,进一步提升其鲁棒性和准确性。 展开更多
关键词 SORT算法 目标检测 多目标跟踪 卡尔曼滤波器 匈牙利算法
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Improved non-dominated sorting genetic algorithm (NSGA)-II in multi-objective optimization studies of wind turbine blades 认领 引用 被引量：33
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作者 王珑 王同光 罗源 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2011年第6期739-748,共10页
The non-dominated sorting genetic algorithm （NSGA） is improved with the controlled elitism and dynamic crowding distance. A novel multi-objective optimization algorithm is obtained for wind turbine blades. As an exa... The non-dominated sorting genetic algorithm （NSGA） is improved with the controlled elitism and dynamic crowding distance. A novel multi-objective optimization algorithm is obtained for wind turbine blades. As an example, a 5 MW wind turbine blade design is presented by taking the maximum power coefficient and the minimum blade mass as the optimization objectives. The optimal results show that this algorithm has good performance in handling the multi-objective optimization of wind turbines, and it gives a Pareto-optimal solution set rather than the optimum solutions to the conventional multi objective optimization problems. The wind turbine blade optimization method presented in this paper provides a new and general algorithm for the multi-objective optimization of wind turbines. 展开更多
关键词 wind turbine multi-objective optimization Pareto-optimal solution non-dominated sorting genetic algorithm （NSGA）-II
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Multi-objective optimization of water supply network rehabilitation with non-dominated sorting Genetic Algorithm-II 认领 引用 被引量：4
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作者 Xi JIN Jie ZHANG +1 位作者 Jin-liang GAO Wen-yan WU 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS 2008年第3期391-400,共10页
Through the transformation of hydraulic constraints into the objective functions associated with a water supply network rehabilitation problem, a non-dominated sorting Genetic Algorithm-II (NSGA-II) can be used to sol... Through the transformation of hydraulic constraints into the objective functions associated with a water supply network rehabilitation problem, a non-dominated sorting Genetic Algorithm-II (NSGA-II) can be used to solve the altered multi-objective optimization model. The introduction of NSGA-II into water supply network optimal rehabilitation problem solves the conflict between one fitness value of standard genetic algorithm (SGA) and multi-objectives of rehabilitation problem. And the uncertainties brought by using weight coefficients or punish functions in conventional methods are controlled. And also by in-troduction of artificial inducement mutation (AIM) operation, the convergence speed of population is accelerated;this operation not only improves the convergence speed, but also improves the rationality and feasibility of solutions. 展开更多
关键词 Water supply system Water supply network Optimal rehabilitation Multi-objective Non-dominated sorting Ge-netic Algorithm （NSGA）
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PMS-Sorting:A New Sorting Algorithm Based on Similarity 认领 引用
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作者 Hongbin Wang Lianke Zhou +4 位作者 Guodong Zhao Nianbin Wang Jianguo Sun Yue Zheng Lei Chen 《Computers, Materials & Continua》 SCIE EI 2019年第4期229-237,共9页
Borda sorting algorithm is a kind of improvement algorithm based on weighted position sorting algorithm,it is mainly suitable for the high duplication of search results,for the independent search results,the effect is... Borda sorting algorithm is a kind of improvement algorithm based on weighted position sorting algorithm,it is mainly suitable for the high duplication of search results,for the independent search results,the effect is not very good and the computing method of relative score in Borda sorting algorithm is according to the rule of the linear regressive,but position relationship cannot fully represent the correlation changes.aimed at this drawback,the new sorting algorithm is proposed in this paper,named PMS-Sorting algorithm,firstly the position score of the returned results is standardized processing,and the similarity retrieval word string with the query results is combined into the algorithm,the similarity calculation method is also improved,through the experiment,the improved algorithm is superior to traditional sorting algorithm. 展开更多
关键词 Meta search engine result sorting query similarity Borda sorting algorithm position relationship
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An Optimization Approach for Convolutional Neural Network Using Non-Dominated Sorted Genetic Algorithm-Ⅱ 认领 引用
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作者 Afia Zafar Muhammad Aamir +6 位作者 Nazri Mohd Nawi Ali Arshad Saman Riaz Abdulrahman Alruban Ashit Kumar Dutta Badr Almutairi Sultan Almotairi 《Computers, Materials & Continua》 SCIE EI 2023年第3期5641-5661,共21页
In computer vision,convolutional neural networks have a wide range of uses.Images representmost of today’s data,so it’s important to know how to handle these large amounts of data efficiently.Convolutional neural ne... In computer vision,convolutional neural networks have a wide range of uses.Images representmost of today’s data,so it’s important to know how to handle these large amounts of data efficiently.Convolutional neural networks have been shown to solve image processing problems effectively.However,when designing the network structure for a particular problem,you need to adjust the hyperparameters for higher accuracy.This technique is time consuming and requires a lot of work and domain knowledge.Designing a convolutional neural network architecture is a classic NP-hard optimization challenge.On the other hand,different datasets require different combinations of models or hyperparameters,which can be time consuming and inconvenient.Various approaches have been proposed to overcome this problem,such as grid search limited to low-dimensional space and queuing by random selection.To address this issue,we propose an evolutionary algorithm-based approach that dynamically enhances the structure of Convolution Neural Networks(CNNs)using optimized hyperparameters.This study proposes a method using Non-dominated sorted genetic algorithms(NSGA)to improve the hyperparameters of the CNN model.In addition,different types and parameter ranges of existing genetic algorithms are used.Acomparative study was conducted with various state-of-the-art methodologies and algorithms.Experiments have shown that our proposed approach is superior to previous methods in terms of classification accuracy,and the results are published in modern computing literature. 展开更多
关键词 Non-dominated sorted genetic algorithm convolutional neural network hyper-parameter optimization
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Improvement of Counting Sorting Algorithm 认领 引用
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作者 Chenglong Song Haiming Li 《Journal of Computer and Communications》 2023年第10期12-22,共11页
By analyzing the internal features of counting sorting algorithm. Two improvements of counting sorting algorithms are proposed, which have a wide range of applications and better efficiency than the original counting ... By analyzing the internal features of counting sorting algorithm. Two improvements of counting sorting algorithms are proposed, which have a wide range of applications and better efficiency than the original counting sort while maintaining the original stability. Compared with the original counting sort, it has a wider scope of application and better time and space efficiency. In addition, the accuracy of the above conclusions can be proved by a large amount of experimental data. 展开更多
关键词 Sort Algorithm Counting Sorting Algorithms Complexity Internal Features
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A decoupled multi-objective optimization algorithm for cut order planning of multi-color garment 认领 引用
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作者 DONG Hui LYU Jinyang +3 位作者 LIN Wenjie WU Xiang WU Mincheng HUANG Guangpu 《High Technology Letters》 EI CAS 2025年第1期53-62,共10页
This work addresses the cut order planning(COP)problem for multi-color garment production,which is the first step in the clothing industry.First,a multi-objective optimization model of multicolor COP(MCOP)is establish... This work addresses the cut order planning(COP)problem for multi-color garment production,which is the first step in the clothing industry.First,a multi-objective optimization model of multicolor COP(MCOP)is established with production error and production cost as optimization objectives,combined with constraints such as the number of equipment and the number of layers.Second,a decoupled multi-objective optimization algorithm(DMOA)is proposed based on the linear programming decoupling strategy and non-dominated sorting in genetic algorithmsⅡ(NSGAII).The size-combination matrix and the fabric-layer matrix are decoupled to improve the accuracy of the algorithm.Meanwhile,an improved NSGAII algorithm is designed to obtain the optimal Pareto solution to the MCOP problem,thereby constructing a practical intelligent production optimization algorithm.Finally,the effectiveness and superiority of the proposed DMOA are verified through practical cases and comparative experiments,which can effectively optimize the production process for garment enterprises. 展开更多
关键词 multi-objective optimization non-dominated sorting in genetic algorithmsⅡ(NSGAII) cut order planning(COP) multi-color garment linear programming decoupling strategy
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Improving path planning efficiency for underwater gravity-aided navigation based on a new depth sorting fast search algorithm 认领 引用 被引量：1
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作者 Xiaocong Zhou Wei Zheng +2 位作者 Zhaowei Li Panlong Wu Yongjin Sun 《Defence Technology（防务技术）》 SCIE EI CAS CSCD 2024年第2期285-296,共12页
This study focuses on the improvement of path planning efficiency for underwater gravity-aided navigation.Firstly,a Depth Sorting Fast Search(DSFS)algorithm was proposed to improve the planning speed of the Quick Rapi... This study focuses on the improvement of path planning efficiency for underwater gravity-aided navigation.Firstly,a Depth Sorting Fast Search(DSFS)algorithm was proposed to improve the planning speed of the Quick Rapidly-exploring Random Trees*(Q-RRT*)algorithm.A cost inequality relationship between an ancestor and its descendants was derived,and the ancestors were filtered accordingly.Secondly,the underwater gravity-aided navigation path planning system was designed based on the DSFS algorithm,taking into account the fitness,safety,and asymptotic optimality of the routes,according to the gravity suitability distribution of the navigation space.Finally,experimental comparisons of the computing performance of the ChooseParent procedure,the Rewire procedure,and the combination of the two procedures for Q-RRT*and DSFS were conducted under the same planning environment and parameter conditions,respectively.The results showed that the computational efficiency of the DSFS algorithm was improved by about 1.2 times compared with the Q-RRT*algorithm while ensuring correct computational results. 展开更多
关键词 Depth Sorting Fast Search algorithm Underwater gravity-aided navigation Path planning efficiency Quick Rapidly-exploring Random Trees*(QRRT*)
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An improved non-dominated sorting biogeography-based optimization algorithm for multi-objective land-use allocation:a case study in Kigali-Rwanda 认领 引用 被引量：2
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作者 Olive Niyomubyeyi Mozafar Veysipanah +2 位作者 Sam Sarwat Petter Pilesjö Ali Mansourian 《Geo-Spatial Information Science》 SCIE EI CSCD 2024年第4期968-982,共15页
With the continuous increase of rapid urbanization and population growth,sustainable urban land-use planning is becoming a more complex and challenging task for urban planners and decision-makers.Multi-objective land-... With the continuous increase of rapid urbanization and population growth,sustainable urban land-use planning is becoming a more complex and challenging task for urban planners and decision-makers.Multi-objective land-use allocation can be regarded as a complex spatial optimization problem that aims to achieve the possible trade-offs among multiple and conflicting objectives.This paper proposes an improved Non-dominated Sorting Biogeography-Based Optimization(NSBBO)algorithm for solving the multi-objective land-use allocation problem,in which maximum accessibility,maximum compactness,and maximum spatial integration were formulated as spatial objectives;and space syntax analysis was used to analyze the potential movement patterns in the new urban planning area of the city of Kigali,Rwanda.Efficient Non-dominated Sorting(ENS)algorithm and crossover operator were integrated into classical NSBBO to improve the quality of non-dominated solutions,and local search ability,and to accelerate the convergence speed of the algorithm.The results showed that the proposed NSBBO exhibited good optimal solutions with a high hypervolume index compared to the classical NSBBO.Furthermore,the proposed algorithm could generate optimal land use scenarios according to the preferred objectives,thus having the potential to support the decision-making of urban planners and stockholders in revising and updating the existing detailed master plan of land use. 展开更多
关键词 Multi-objective land-use allocation spatial optimization sustainable urban planning Non-dominated Sorting Biogeography-Based Optimization(NSBBO)algorithm
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基于改进BOT-Sort算法的多目标追踪方法 认领 引用
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作者 李书钦 王一凡 《北方工业大学学报》 2025年第6期37-48,共12页
针对社区复杂环境下多目标追踪精度低与轨迹连续性差的问题,本文提出一种基于改进Boosted SORT with Stronger ReID(BOT-Sort)的多目标追踪算法,通过在Split-Attention Networks(ResNeSt)不同层级中加入自适应图通道聚合网络,并将其作为... 针对社区复杂环境下多目标追踪精度低与轨迹连续性差的问题,本文提出一种基于改进Boosted SORT with Stronger ReID(BOT-Sort)的多目标追踪算法,通过在Split-Attention Networks(ResNeSt)不同层级中加入自适应图通道聚合网络,并将其作为BOT-Sort算法的特征提取器,提高模型对于行人的全局和局部特征特征提取能力;同时将基于局部-全局上下文的行人重识别(Partial-Global Context Network for Person Re-Identification, PGCID)算法作为BOT-Sort算法的行人重识别模块,提升模型的特征融合能力。基于MOT17数据集对改进模型进行端到端训练,并在MOT17和MOT20数据集上进行对比实验。结果显示,改进的BOT-Sort算法的多目标跟踪精度(Multiple Object Tracking Accuracy, MOTA)指标、识别(Identification F1 Score, IDF1)指标、高阶跟踪精度(Higher Order Tracking Accuracy, HOTA)指标分别达到了80.6%、80.3%和66.2%,追踪目标身份交换次数(Identity Switches, IDsw)降至1 065次,提升了社区复杂场景下多目标追踪的精度与轨迹连续性。 展开更多
关键词 BOT-Sort算法 行人追踪 多目标追踪
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An Only-Once-Sorting Algorithm 认领 引用
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作者 Xu Xusong Zhou Jianqin Guo Feng 《Wuhan University Journal of Natural Sciences》 CAS 1996年第1期38-41,共4页
This paper provides a new sorting algorithm called 'Only-Once-Sorting' algorithm a mathemati cal formula,this algorithm can put elements in the positions they should be stored only once,then compacts them.The ... This paper provides a new sorting algorithm called 'Only-Once-Sorting' algorithm a mathemati cal formula,this algorithm can put elements in the positions they should be stored only once,then compacts them.The algorithm completes sorting a sequence of n elements in a calculation time of O(n ). 展开更多
关键词 mathematical formula onlv-once-sorting sorting algorithm
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Accelerating Large-Scale Sorting through Parallel Algorithms 认领 引用
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作者 Yahya Alhabboub Fares Almutairi +3 位作者 Mohammed Safhi Yazan Alqahtani Adam Almeedani Yasir Alguwaifli 《Journal of Computer and Communications》 2024年第1期131-138,共8页
This study explores the application of parallel algorithms to enhance large-scale sorting, focusing on the QuickSort method. Implemented in both sequential and parallel forms, the paper provides a detailed comparison ... This study explores the application of parallel algorithms to enhance large-scale sorting, focusing on the QuickSort method. Implemented in both sequential and parallel forms, the paper provides a detailed comparison of their performance. This study investigates the efficacy of both techniques through the lens of array generation and pivot selection to manage datasets of varying sizes. This study meticulously documents the performance metrics, recording 16,499.2 milliseconds for the serial implementation and 16,339 milliseconds for the parallel implementation when sorting an array by using C++ chrono library. These results suggest that while the performance gains of the parallel approach over its serial counterpart are not immediately pronounced for smaller datasets, the benefits are expected to be more substantial as the dataset size increases. 展开更多
关键词 Sorting Algorithm Quick Sort QuickSort Parallel Parallel Algorithms
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基于稀疏贝叶斯的航空发动机风扇声模态重构 认领 引用 被引量：1
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作者 王菲 李行健 +4 位作者 王亚南 杜军 文璧 乔百杰 陈雪峰 《航空动力学报》 EI CAS CSCD 北大核心 2026年第5期227-239,共13页
针对航空发动机风扇管道声模态重构时,均匀环形声阵列所需传感器数量庞大,而传统基于L1范数的压缩感知方法存在幅值低估的问题,研究基于稀疏贝叶斯的航空发动机风扇声模态重构方法,建立稀疏贝叶斯分层先验模型,利用块坐标下降法求解,有... 针对航空发动机风扇管道声模态重构时,均匀环形声阵列所需传感器数量庞大,而传统基于L1范数的压缩感知方法存在幅值低估的问题,研究基于稀疏贝叶斯的航空发动机风扇声模态重构方法,建立稀疏贝叶斯分层先验模型,利用块坐标下降法求解,有效解释并量化测量过程中的不确定性;利用非支配遗传算法优化阵列布局,提高声模态重构精度。开展了某3.5级航空发动机风扇声模态测试试验,结果表明:在相同传声器数目下,稀疏贝叶斯方法的重构平均误差低于L1范数正则化方法;在低速工况下,采用6支传感器最优布局,稀疏贝叶斯方法对周向模态阶数为5的声模态重构误差为0.01 dB;在高速工况下,采用8支传感器最优布局,稀疏贝叶斯方法对周向模态阶数为5和-12的声模态重构误差分别为0.50 dB和0.46 dB。 展开更多
关键词 航空发动机风扇 声模态重构 稀疏贝叶斯 非支配遗传算法 阵列布局优化
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基于非支配遗传算法的双花瓣配电网多故障抢修策略 认领 引用 被引量：3
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作者 徐岩 孙纪领 《电气工程学报》 CSCD 北大核心 2026年第1期327-334,共8页
新型的双花瓣配电网络具有极高的供电可靠性,但是在面对多重故障时,其多环网闭合运行的特性导致缺少适配的算法进行抢修策略的制定。为解决这一问题,建立一种考虑双花瓣配电网合环运行特性,根据抢修时间和负荷等级的配电网多故障抢修目... 新型的双花瓣配电网络具有极高的供电可靠性,但是在面对多重故障时,其多环网闭合运行的特性导致缺少适配的算法进行抢修策略的制定。为解决这一问题,建立一种考虑双花瓣配电网合环运行特性,根据抢修时间和负荷等级的配电网多故障抢修目标优化模型,提出一种针对环网改进的非支配遗传算法(Non-dominated sorting genetic algorithm-II,NSGA-II),实现了在双花瓣环网构型中应用智能优化算法求解抢修方案。最后经过模拟仿真,验证了所提算法在制定抢修恢复策略上表现得更为高效,且适合在实际抢修工作中使用。 展开更多
关键词 花瓣型配电网 多故障抢修 合环运行 回路分析法 非支配遗传算法
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永磁同步电机模型预测转矩控制权重系数设计研究 认领 引用 被引量：1
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作者 李耀华 刘亚辉 +3 位作者 张鑫泉 张茜 黄汉旋 吴步昊 《电机与控制应用》 2026年第1期46-56,共11页
【目的】针对模型预测控制权重系数设计困难的问题,本文采用非支配排序遗传算法II(NSGA-II)和贝叶斯优化算法进行权重系数设计。【方法】基于永磁同步电机(PMSM)模型预测转矩控制(MPTC)系统,针对不考虑开关次数控制和考虑开关次数控制... 【目的】针对模型预测控制权重系数设计困难的问题,本文采用非支配排序遗传算法II(NSGA-II)和贝叶斯优化算法进行权重系数设计。【方法】基于永磁同步电机(PMSM)模型预测转矩控制(MPTC)系统,针对不考虑开关次数控制和考虑开关次数控制两种场景,分别采用NSGA-II和贝叶斯优化算法设计权重系数。不考虑开关次数控制时仅需设计一个权重系数,考虑开关次数控制时需同时设计两个权重系数。基于两种优化算法设计的权重系数,从控制效果、执行时间和内存占用对两种算法进行了对比。【结果】结果表明,对于考虑和不考虑开关次数控制的PMSM MPTC系统,两种权重系数设计算法均可行。NSGA-II得到的使适应度函数值最小的权重系数与贝叶斯优化算法得到的最优权重系数基本相当,控制性能也基本相当,贝叶斯优化算法的控制性能相对略优。【结论】NSGA-II可提供一组适合不同应用场景的Pareto最优解,但其算法复杂度高、计算时间长且占用内存大,适用于动态变化的运行场景。贝叶斯优化算法易于实现、占用资源少,在多控制目标的复杂场景中具有更好的寻优效果和更高的寻优效率。 展开更多
关键词 永磁同步电机 模型预测转矩控制 权重系数 开关次数控制 非支配排序遗传算法II 贝叶斯优化
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A multi-line laser scanning system design and evaluation framework based on physical simulation 认领 引用
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作者 Yunpeng LI Yifan CHEN +3 位作者 Limei SONG Hongyi WANG Hongmin WANG Baozhen GE 《Optoelectronics Letters》 EI 2026年第5期268-274,共7页
We propose a multi-line laser simulation system utilizing computer graphics and physical simulation to generate virtual multi-line laser datasets.Our framework provides key physical properties of the scene,including c... We propose a multi-line laser simulation system utilizing computer graphics and physical simulation to generate virtual multi-line laser datasets.Our framework provides key physical properties of the scene,including camera parameters,depth values,surface normals,and the actual two-dimensional(2D)and three-dimensional(3D)coordinates of the laser stripe centers for each rendered image.Beyond,we construct a virtual line laser scanning image dataset with a complex background by simulating interactions between lasers and object surfaces with the Monte Carlo method.With the proposed framework and dataset,a multi-line laser extraction algorithm based on a robust sorting algorithm is proposed and tested,which utilizes distance-based error analysis,connected component labeling,and iterative optimization refinement techniques.Both simulation and actual experiments show that our method outperforms the other state-of-the-art multi-line laser stripe center extraction methods.The proposed framework can be applied to different types of laser scanning systems in the future. 展开更多
关键词 physical simulation computer graphics Robust sorting algorithm Monte Carlo method Multi line laser scanning simulating interactions las virtual line laser scanning image dataset
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Two-stage two-dimensional force allocation strategy for tunnel boring machines based on a region-reconfigurable thrust system 认领 引用
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作者 Zhe ZHENG Kaihao ZHU +7 位作者 Jiaqi HOU Haibo XIE Lijie JIANG Fulong LIN Lianhui JIA Laikuang LIN Huayong YANG Dong HAN 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS CSCD 2026年第6期583-597,I0035-I0042,共15页
Determining the group forces of the thrust system is essential for trajectory control of tunnel boring machines(TBMs).Existing methods for selecting an optimal solution mainly consider the force variance among groups,... Determining the group forces of the thrust system is essential for trajectory control of tunnel boring machines(TBMs).Existing methods for selecting an optimal solution mainly consider the force variance among groups,while ignoring other constraints,such as uneven segment loading and excessive hydraulic shock.In this study,we develop a more comprehensive and robust framework for force allocation.First,a novel region-reconfigurable hydraulic system is designed,which enforces consistency among the forces acting on each segment.Then on this basis,for the ramping-up tunneling stage,quadratic programming(QP)is used to optimize force uniformity across the spatial dimension.Compared to the on-site allocation result,the improvement in force uniformity reaches up to 32.89%.Moreover,to address the hydraulic shock caused by excessive adjustment to the force,hydraulic compliance is introduced and optimized together with force uniformity using the non-dominated sorting genetic algorithm II(NSGA-II),which outperforms weighted QP by 1.25×106 kN2 in uniformity and 2.86 kN2 in compliance.Analyzing performance in the steady tunneling stage,the service life of the components improves significantly.To avoid a non-existent solution for the thrust force vector,a genetic algorithm-based error tolerance method is developed.Therefore,all deviation rectification commands can be answered with a minor compromise of up to 3%in the fitting accuracy of the thrust force vector.In summary,this framework enhances the adaptability and robustness of the force allocation strategy,providing a reliable foundation for TBM trajectory control. 展开更多
关键词 Tunnel boring machine(TBM) Thrust system Thrust force vector Force allocation Quadratic programming(QP) Non-dominated sorting genetic algorithm II(NSGA-II)
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MAV-UAV combat organization's force formation plan generation based on NSGA-Ⅲ 认领 引用
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作者 ZHONG Yun WAN Lujun ZHANG Jieyong 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2026年第1期307-317,共11页
Manned aerial vehicle-unmanned aerial vehicle(MAV-UAV)combat organization is a MAV-UAV combat collective formed from the perspective of organization design theory and methodology,and the generation of force formation ... Manned aerial vehicle-unmanned aerial vehicle(MAV-UAV)combat organization is a MAV-UAV combat collective formed from the perspective of organization design theory and methodology,and the generation of force formation plan is a key step in the organizational planning.Based on the description of the problem and the definition of organizational elements,the matching model of platform-target attack wave is constructed to minimize the redundancy of command and decision-making capability,resource capability and the number of platforms used.Based on the non-dominated sorting genetic algorithmⅢ(NSGA-Ⅲ)framework,which includes encoding/decoding method and constraint handling method,the generation model of organizational force formation plan is solved,and the effectiveness and superiority of the algorithm are verified by simulation experiments. 展开更多
关键词 manned-unmanned aerial vehicle combat organization force formation plan command and decision-making capability resource capability non-dominated sorting genetic algorithmⅢ(NSGA-Ⅲ)
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柔性路径变节与跨单元协同的调度节能优化 认领 引用
20
作者 沈景凤 田源 +2 位作者 李嘉曜 仲梁维 苗涛 《上海理工大学学报》 CAS 北大核心 2026年第2期239-252,共14页
针对多柔性路径下单元制造系统生产效率低、生产能耗高的问题,从优化跨单元运输次数的角度出发,建立了以完工时间、总生产能耗和跨单元次数为优化目标的多目标模型,并提出一种变邻域非支配排序遗传算法进行求解。基于混合全局和随机生... 针对多柔性路径下单元制造系统生产效率低、生产能耗高的问题,从优化跨单元运输次数的角度出发,建立了以完工时间、总生产能耗和跨单元次数为优化目标的多目标模型,并提出一种变邻域非支配排序遗传算法进行求解。基于混合全局和随机生成解集法,选取跨单元次数较少的个体为初始解,设计基于跨单元运输的解码方式,并融合3种变邻域算子,降低运输及空闲时间对加工过程的影响,运用改进交叉和变异非支配排序方法得到高效的进化过程。最后,通过算例仿真验证改进算法的合理性,并在实例部分分析得出:均衡跨单元次数有利于协调优化完工时间与总能耗这两个目标,进一步证实了所建模型的优越性。 展开更多
关键词 生产能耗 跨单元调度 跨单元运输次数 非支配排序遗传算法
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