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Parallel Distributed CFAR Detection Optimization Based on Genetic Algorithm with Interval Encoding 认领 引用 被引量：1
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作者 于泽 周荫清 《Chinese Journal of Aeronautics》 SCIE EI CAS 2010年第3期351-358,共8页
Aiming at parallel distributed constant false alarm rate （CFAR） detection employing K/N fusion rule,an optimization algorithm based on the genetic algorithm with interval encoding is proposed. N-1 local probabilitie... Aiming at parallel distributed constant false alarm rate （CFAR） detection employing K/N fusion rule,an optimization algorithm based on the genetic algorithm with interval encoding is proposed. N-1 local probabilities of false alarm are selected as optimization variables. And the encoding intervals for local false alarm probabilities are sequentially designed by the person-by-person optimization technique according to the constraints. By turning constrained optimization to unconstrained optimization,the problem of increasing iteration times due to the punishment technique frequently adopted in the genetic algorithm is thus overcome. Then this optimization scheme is applied to spacebased synthetic aperture radar （SAR） multi-angle collaborative detection,in which the nominal factor for each local detector is determined. The scheme is verified with simulations of cases including two,three and four independent SAR systems. Besides,detection performances with varying K and N are compared and analyzed. 展开更多
关键词 parallel processing systems synthetic aperture radar detectors genetic algorithms optimization encoding
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A genetic algorithm for community detection in complex networks 认领 引用 被引量：9
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作者 李赟 刘钢 老松杨 《Journal of Central South University》 SCIE EI CAS 2013年第5期1269-1276,共8页
A new genetic algorithm for community detection in complex networks was proposed. It adopts matrix encoding that enables traditional crossover between individuals. Initial populations are generated using nodes similar... A new genetic algorithm for community detection in complex networks was proposed. It adopts matrix encoding that enables traditional crossover between individuals. Initial populations are generated using nodes similarity, which enhances the diversity of initial individuals while retaining an acceptable level of accuracy, and improves the efficiency of optimal solution search. Individual crossover is based on the quality of individuals' genes; all nodes unassigned to any community are grouped into a new community, while ambiguously placed nodes are assigned to the community to which most of their neighbors belong. Individual mutation, which splits a gene into two new genes or randomly fuses it into other genes, is non-uniform. The simplicity and effectiveness of the algorithm are revealed in experimental tests using artificial random networks and real networks. The accuracy of the algorithm is superior to that of some classic algorithms, and is comparable to that of some recent high-precision algorithms. 展开更多
关键词 complex networks community detection genetic algorithm matrix encoding nodes similarity
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An Improved Genetic Algorithm for Solving the Mixed⁃Flow Job⁃Shop Scheduling Problem with Combined Processing Constraints 认领 引用 被引量：4
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作者 ZHU Haihua ZHANG Yi +2 位作者 SUN Hongwei LIAO Liangchuang TANG Dunbing 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2021年第3期415-426,共12页
The flexible job-shop scheduling problem(FJSP)with combined processing constraints is a common scheduling problem in mixed-flow production lines.However,traditional methods for classic FJSP cannot be directly applied.... The flexible job-shop scheduling problem(FJSP)with combined processing constraints is a common scheduling problem in mixed-flow production lines.However,traditional methods for classic FJSP cannot be directly applied.Targeting this problem,the process state model of a mixed-flow production line is analyzed.On this basis,a mathematical model of a mixed-flow job-shop scheduling problem with combined processing constraints is established based on the traditional FJSP.Then,an improved genetic algorithm with multi-segment encoding,crossover,and mutation is proposed for the mixed-flow production line problem.Finally,the proposed algorithm is applied to the production workshop of missile structural components at an aerospace institute to verify its feasibility and effectiveness. 展开更多
关键词 mixed-flow production flexible job-shop scheduling problem(FJSP) genetic algorithm encoding
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Neural network fault diagnosis method optimization with rough set and genetic algorithms 认领 引用
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作者 孙红岩 《Journal of Chongqing University》 2006年第2期94-97,共4页
Aiming at the disadvantages of BP model in artificial neural networks applied to intelligent fault diagnosis, neural network fault diagnosis optimization method with rough sets and genetic algorithms are presented. Th... Aiming at the disadvantages of BP model in artificial neural networks applied to intelligent fault diagnosis, neural network fault diagnosis optimization method with rough sets and genetic algorithms are presented. The neural network nodes of the input layer can be calculated and simplified through rough sets theory; The neural network nodes of the middle layer are designed through genetic algorithms training; the neural network bottom-up weights and bias are obtained finally through the combination of genetic algorithms and BP algorithms. The analysis in this paper illustrates that the optimization method can improve the performance of the neural network fault diagnosis method greatly. 展开更多
关键词 rough sets genetic algorithm BP algorithms artificial neural network encoding rule
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GLOBAL OPTIMIZATION OF PUMP CONFIGURATION PROBLEM USING EXTENDED CROWDING GENETIC ALGORITHM 认领 引用 被引量：3
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作者 ZhangGuijun WuTihua YeRong 《Chinese Journal of Mechanical Engineering》 EI CAS 2004年第2期247-252,共6页
An extended crowding genetic algorithm (ECGA) is introduced for solvingoptimal pump configuration problem, which was presented by T. Westerlund in 1994. This problem hasbeen found to be non-convex, and the objective f... An extended crowding genetic algorithm (ECGA) is introduced for solvingoptimal pump configuration problem, which was presented by T. Westerlund in 1994. This problem hasbeen found to be non-convex, and the objective function contained several local optima and globaloptimality could not be ensured by all the traditional MINLP optimization method. The concepts ofspecies conserving and composite encoding are introduced to crowding genetic algorithm (CGA) formaintain the diversity of population more effectively and coping with the continuous and/or discretevariables in MINLP problem. The solution of three-levels pump configuration got from DICOPT++software (OA algorithm) is also given. By comparing with the solutions obtained from DICOPT++, ECPmethod, and MIN-MIN method, the ECGA algorithm proved to be very effective in finding the globaloptimal solution of multi-levels pump configuration via using the problem-specific information. 展开更多
关键词 Pump configuration problem Extended crowding genetic algorithm Speciesconserving Composite encoding Global optimization
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Improved Real-Coded Genetic Algorithm Solution for Unit Commitment Problem Considering Energy Saving and Emission Reduction Demands 认领 引用
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作者 潘谦 何星 +2 位作者 蔡云泽 王治华 苏凡 《Journal of Shanghai Jiaotong university(Science)》 EI 2015年第2期218-223,共6页
Unit commitment(UC), as a typical optimization problem in electric power system, faces new challenges as energy saving and emission reduction get more and more important in the way to a more environmentally friendly s... Unit commitment(UC), as a typical optimization problem in electric power system, faces new challenges as energy saving and emission reduction get more and more important in the way to a more environmentally friendly society. To meet these challenges, we propose a UC model considering energy saving and emission reduction. By using real-number coding method, swap-window and hill-climbing operators, we present an improved real-coded genetic algorithm(IRGA) for UC. Compared with other algorithms approach to the proposed UC problem, the IRGA solution shows an improvement in effectiveness and computational time. 展开更多
关键词 genetic algorithm(GA) unit commitment(UC) improved real-number encoding
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Application of a Genetic Algorithm Based on the Immunity for Flow Shop under Uncertainty 认领 引用 被引量：1
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作者 WANG Luchao DENG Yongping 《武汉理工大学学报》 EI CAS 北大核心 2006年第S2期673-676,共4页
The uncertain duration of each job in each machine in flow shop problem was regarded as an independent random variable and was described by mathematical expectation.And then,an immune based partheno-genetic algorithm ... The uncertain duration of each job in each machine in flow shop problem was regarded as an independent random variable and was described by mathematical expectation.And then,an immune based partheno-genetic algorithm was proposed by making use of concepts and principles introduced from immune system and genetic system in nature.In this method,processing se-quence of products could be expressed by the character encoding and each antibody represents a feasible schedule.Affinity was used to measure the matching degree between antibody and antigen.Then several antibodies producing operators,such as swopping,mov-ing,inverting,etc,were worked out.This algorithm was combined with evolution function of the genetic algorithm and density mechanism in organisms immune system.Promotion and inhibition of antibodies were realized by expected propagation ratio of an-tibodies,and in this way,premature convergence was improved.The simulation proved that this algorithm is effective. 展开更多
关键词 genetic algorithm based on the immunity flow shop character encoding antibody
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基于NSGA-Ⅱ算法与离散模块梁单元水弹性方法的连接件优化设计分析 认领 引用
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作者 陈永强 张显涛 《中国舰船研究》 CSCD 北大核心 2026年第3期158-167,共10页
[目的]在离散模块梁单元(DMB)框架下,针对浮箱型多模块海上漂浮式光伏(OFPV)平台连接件刚度优化问题,提出一种新的方法。[方法]首先,介绍DMB水弹性分析方法,给出连接件刚度矩阵的形式并简述水弹性响应的数值建模方法;其次,给出线性加权... [目的]在离散模块梁单元(DMB)框架下,针对浮箱型多模块海上漂浮式光伏(OFPV)平台连接件刚度优化问题,提出一种新的方法。[方法]首先,介绍DMB水弹性分析方法,给出连接件刚度矩阵的形式并简述水弹性响应的数值建模方法;其次,给出线性加权遗传算法和非支配排序遗传算法Ⅱ(NSGA-Ⅱ)的求解步骤,重点介绍刚度编码的实数码、指数码和科学记数码这3种基因编码方式以及其对应的交叉和变异算子,并进行对比分析;最后,引入等效零刚度和等效无穷刚度缩聚解空间。[结果]结果显示,使用NSGA-Ⅱ算法可求解得出最大结构剪力最小和最大结构弯矩最小的Pareto前沿,同时,该Pareto前沿可视作由线性加权法得到的不同权重设置所对应最优解的集合,且科学记数码的搜索性能优。[结论]所述优化理论模型可针对浮箱型多模块平台用于对连接件刚度进行多目标优化。 展开更多
关键词 连接件 刚度 离散模块梁单元 非支配排序遗传算法Ⅱ 多目标优化 科学记数码
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基于遗传算法的齿轮传动可靠性优化设计 认领 引用
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作者 王纯 《机械工程师》 2026年第3期153-156,共4页
为了实现齿轮传动系统的优化设计,以二级斜齿圆柱齿轮传动系统作为研究对象,建立二级斜齿圆柱齿轮传动系统的可靠性优化数学模型,以齿轮的关键参数(齿数、模数、螺旋角)为设计变量,选取二级斜齿圆柱齿轮传动系统的体积和重合度为目标函... 为了实现齿轮传动系统的优化设计,以二级斜齿圆柱齿轮传动系统作为研究对象,建立二级斜齿圆柱齿轮传动系统的可靠性优化数学模型,以齿轮的关键参数(齿数、模数、螺旋角)为设计变量,选取二级斜齿圆柱齿轮传动系统的体积和重合度为目标函数,以可靠性等约束作为约束条件,并利用浮点数编码的遗传算法对二级斜齿圆柱齿轮传动系统进行可靠性优化设计,得到各参数最优解,结果显示体积减小27.3%,重合度提高12.3%。实现是降低成本、提高齿轮传动稳定性的目的。 展开更多
关键词 遗传算法 优化设计 可靠性 齿轮传动 多目标 浮点数编码
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基于改进遗传算法的电子设备多级协调控制方法 认领 引用
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作者 温田辉 林聪友 +2 位作者 李朝平 金自力 姚泽玮 《电工技术》 2026年第11期8-11,共4页
针对电子设备多级协调控制实践中存在的电压波动异常和谐波畸变率较高的问题,提出基于改进遗传算法的电子设备多级协调控制方法。构建以配电网电子设备为一级、分布式光伏电网电子设备为二级的多级协调控制模型,目标函数综合考虑系统网... 针对电子设备多级协调控制实践中存在的电压波动异常和谐波畸变率较高的问题,提出基于改进遗传算法的电子设备多级协调控制方法。构建以配电网电子设备为一级、分布式光伏电网电子设备为二级的多级协调控制模型,目标函数综合考虑系统网损、电子设备电压稳定性及运行成本,并计及电子设备电压、交互功率、光伏出力等多重约束条件,形成一类高维非线性优化问题。针对该模型求解难题,设计一种改进遗传算法,采用自然数编码表征控制策略,结合启发式规则生成高质量初始种群,引入自适应变异概率与互换变异算子增强全局搜索能力,并利用罚函数法处理复杂约束,通过迭代求解,实现基于改进遗传算法的电子设备多级协调控制。以某典型分布式光伏配电网为对象,通过仿真证明所提方法能有效抑制电压波动,将谐波畸变率控制在1%以下,验证了其在实现电子设备多级协调精确控制方面的有效性与优越性。 展开更多
关键词 改进遗传算法 电子设备 协调控制 自然数编码 启发式规则
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CPU/GPU异构资源下机器双编码—解码调度算法设计 认领 引用
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作者 黎元宝 冯汉枣 刘运奇 《微型电脑应用》 2026年第3期361-364,共4页
为了解决CPU/GPU异构资源易产生负载失衡问题,设计针对CPU/GPU异构资源的机器双编码—解码调度算法。设计异构资源数据处理算法的框架。设计数据处理顺序表和编码矩阵,利用遗传算法进行任务调度和优化,以决定编码—解码任务的执行顺序... 为了解决CPU/GPU异构资源易产生负载失衡问题,设计针对CPU/GPU异构资源的机器双编码—解码调度算法。设计异构资源数据处理算法的框架。设计数据处理顺序表和编码矩阵,利用遗传算法进行任务调度和优化,以决定编码—解码任务的执行顺序和分配给不同处理器的方式。根据调度结果,将编码任务分配给CPU进行处理,将解码任务分配给GPU进行处理。在编码任务和解码任务完成后,将两者的结果进行合并,并输出最终的处理结果。实验表明,双编码—解码调度算法的加速比在0.9以上,在3种系统配置下的时间比例始终低于40%,内存开销小于15 KB,具有良好的调度效果。 展开更多
关键词 CPU/GPU异构资源 双编码—解码调度算法 遗传算法 数据调度
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基于遗传算法与专家经验融合的钢轨断面尺寸自动调整算法实现与优化研究 认领 引用
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作者 朱军 陶功明 +3 位作者 吴郭贤 向重宗 赵平 刘璐峣 《四川冶金》 CAS 2026年第1期25-28,51,共4页
在铁路运输向高速、重载发展的背景下,钢轨断面尺寸精度对运输安全至关重要。传统轧机辊缝人工调整存在效率低、精度不足等问题,本研究提出遗传算法与专家经验融合的自动调整策略,通过构建基础方案矩阵结构化专家经验,采用矩阵编码优化... 在铁路运输向高速、重载发展的背景下,钢轨断面尺寸精度对运输安全至关重要。传统轧机辊缝人工调整存在效率低、精度不足等问题,本研究提出遗传算法与专家经验融合的自动调整策略,通过构建基础方案矩阵结构化专家经验,采用矩阵编码优化求解过程,结合加权稀疏整数优化算法实现最优方案选择。实验表明,该方法在调整精度和时间上显著优于传统方法及单一遗传算法,为钢铁行业智能化发展提供了技术支撑。 展开更多
关键词 遗传算法 专家经验方案 矩阵编码 钢轨断面尺寸 自动调整
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Two-stage evolutionary algorithm for dynamic multicast routing in mesh network 认领 引用
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作者 Li ZHU Zhi-shu LI +1 位作者 Liang-yin CHEN Yan-hong CHENG 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS 2008年第6期791-798,共8页
In order to share multimedia transmissions in mesh networks and optimize the utilization of network resources, this paper presents a Two-stage Evolutionary Algorithm (TEA), i.e., unicast routing evolution and multicas... In order to share multimedia transmissions in mesh networks and optimize the utilization of network resources, this paper presents a Two-stage Evolutionary Algorithm (TEA), i.e., unicast routing evolution and multicast path composition, for dynamic multicast routing. The TEA uses a novel link-duplicate-degree encoding, which can encode a multicast path in the link-duplicate-degree and decode the path as a link vector easily. A dynamic algorithm for adding nodes to or removing nodes from a multicast group and a repairing algorithm are also covered in this paper. As the TEA is based on global evaluation, the quality of the multicast path remains stabilized without degradation when multicast members change over time. Therefore, it is not necessary to rearrange the multicast path during the life cycle of the multicast sessions. Simulation results show that the TEA is efficient and convergent. 展开更多
关键词 Dynamic multicast Routing Encoding Quality of Service （QoS） Evolution Genetic algorithm （GA）
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基于改进遗传算法的多样本柔性车间调度问题研究 认领 引用
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作者 赵子恒 杨敬辉 《智能计算机与应用》 2026年第5期204-210,F0003,共7页
在工业4.0背景下,制造业正在经历向智能化与数字化的深刻转型,以提升效率并应对经济与环境双重挑战。本文针对这一趋势,专注于柔性车间调度问题(FJSP),以减少最大完工时间为目标,设计一种改进的遗传算法,采用双向量编码,由于FJSP是一个... 在工业4.0背景下,制造业正在经历向智能化与数字化的深刻转型,以提升效率并应对经济与环境双重挑战。本文针对这一趋势,专注于柔性车间调度问题(FJSP),以减少最大完工时间为目标,设计一种改进的遗传算法,采用双向量编码,由于FJSP是一个离散组合优化问题,本文的编码采用连续组合优化方式(DLGA)并通过层级竞争策略初始化种群,以增强种群多样性并促进算法跳出局部最优。算法设计中,种群被分为优胜者、跟随者和失败者3个层级,通过筛选、学习和竞争算子来优化解的质量,进一步提升了解决问题的能力。实验部分采用了两种类型的数据样本,一种是Brandimarte设计的10个多样化案例,进行多次实验。另一种为了保证算法的可用性,从实际保温杯工厂中进一步提取样本数据,证明算法的有效性。实验结果表明DLGA算法虽然在公共数据集上可以得到良好的效果,但从实际企业需求上来看,DLGA可以更好地解决企业所面临的实际问题。 展开更多
关键词 工业4.0 柔性车间调度问题(FJSP) 改进遗传算法 双向量编码 层级竞争策略
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Permutation Encoding for Pilot Coordination in Multi-user Massive MIMO 认领 引用
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作者 Hafiz Ahmad Khalid 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2018年第S1期59-62,共4页
Pilot plays an essential role in a duplex communication system.Several methods have been proposed for pilot assignment over specific scenarios.With the help of permutation encoding,we implemented a genetic algorithm f... Pilot plays an essential role in a duplex communication system.Several methods have been proposed for pilot assignment over specific scenarios.With the help of permutation encoding,we implemented a genetic algorithm for optimizing pilot assignment in a multi-user massive multiple input multiple output(MIMO)system.Results show improvement on existing results especially in the case of strong user estimation rates. 展开更多
关键词 genetic algorithms performance analysis permutation encoding
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Effects of Different Representations for Solving Integrated Production and Transportation Scheduling Problem 认领 引用 被引量：1
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作者 Youjie Yao Qingzheng Wang +1 位作者 Cuiyu Wang Xinyu Li 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2025年第3期209-228,共20页
With the growing adoption of automated guided vehicles(AGVs)in various industries,the integrated production and transportation scheduling problem(IPTSP)has emerged as a critical research focus.The IPTSP is classified ... With the growing adoption of automated guided vehicles(AGVs)in various industries,the integrated production and transportation scheduling problem(IPTSP)has emerged as a critical research focus.The IPTSP is classified as a strongly NP-hard problem due to the simultaneous scheduling of two resources:machines and transportation equipment.Meta-heuristic algorithms are one of the most popular and effective approaches to solving this problem.However,their effectiveness heavily depends on the choice of solution representation,which influences both the algorithm’s search space and convergence speed.This paper reviews the existing encoding and decoding methods and proposes a novel active decoding approach.Based on different combinations of encoding and decoding methods,six solution representations are identified,among which the newly proposed representation offers a trade-off between the search space and the algorithm’s efficiency.Specifically,four scenarios of IPTSP under different assumptions are first analyzed.Next,the variations in the six solution representations across unused scenarios and different layouts,as well as their respective encoding spaces and qualities,are summarized.Subsequently,the search efficiency of the six solution representations is evaluated using a genetic algorithm to analyze their performance under different scenarios,layouts,time ratios,and number of AGVs.Finally,the advantages,disadvantages and applicable scenes for each solution representation are summarized based on the experimental results and analysis.These findings provide valuable insights for designing more efficient algorithms to address the IPTSP. 展开更多
关键词 Integrated scheduling Processing and transportation Encoding and decoding Genetic algorithm
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基于遗传算法的被动式木窗材下料优化 认领 引用 被引量：3
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作者 任长清 武子棋 +2 位作者 闫杰 丁星尘 杨春梅 《森林工程》 北大核心 2025年第3期595-602,共8页
在定制化被动式木窗加工过程中,减少边框材下料过程中的原料浪费是降低成本的关键。为此,将该问题建模为一维下料问题,针对传统遗传算法中个体编码方式在迭代过程中容易导致切割模式被破坏和探索效率低下的问题,提出一种新的个体编码方... 在定制化被动式木窗加工过程中,减少边框材下料过程中的原料浪费是降低成本的关键。为此,将该问题建模为一维下料问题,针对传统遗传算法中个体编码方式在迭代过程中容易导致切割模式被破坏和探索效率低下的问题,提出一种新的个体编码方式,以保护进化过程中切割模式的完整性。同时,设计启发式策略和修正策略,用于个体修正和种群进化。仿真试验表明,在不同算例下,除末根外的原料平均利用率均可达到99%,且末根余料长度相较其他算法也有所提高。在2组企业的实际生产数据中,与企业现有软件相比,该算法不仅达到了理论下界,还在除末根外的平均利用率上分别达到99.49%和99.66%,优于企业软件的计算结果。该算法有助于降低成本,能为工程实践提供可靠的解决方案。 展开更多
关键词 一维下料问题 遗传算法 启发式算法 种群编码 可用剩余物
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基于多染色体编码遗传算法的多星成像与数传耦合规划方法 认领 引用 被引量：1
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作者 刘佳 秦嘉豪 +2 位作者 李瀛搏 姚远 徐明 《宇航学报》 EI CAS CSCD 北大核心 2025年第3期616-630,共15页
针对对地观测卫星集群的大范围成像与数据下传耦合规划,提出了一种融合结构体编码与多层编码的多染色体遗传算法,实现了在复杂约束条件下对多个目标的同时优化。算法建立了成像与数传任务的约束满足模型,优化了卫星的拼幅成像与数据传... 针对对地观测卫星集群的大范围成像与数据下传耦合规划,提出了一种融合结构体编码与多层编码的多染色体遗传算法,实现了在复杂约束条件下对多个目标的同时优化。算法建立了成像与数传任务的约束满足模型,优化了卫星的拼幅成像与数据传输方案,考虑了卫星姿态机动能力与多个区域的全覆盖需求。此外,采用多层编码方式,有效解决了成像与数传任务解空间映射关系。基于遗传算法的全局搜索机制显著提高了任务规划的效率。试验验证表明,在3颗太阳同步轨道卫星星座中,该算法实现了对超过5个大范围区域的全覆盖,卫星的能源和数据存储未超出约束上限;同时,单次规划的运行时间小于15 min,验证了其实用性和高效性。该方法有效解决了复杂任务的耦合规划问题,具有较强的工程应用价值。 展开更多
关键词 多星测运控 多星任务规划 多染色体编码遗传算法 成像与数传任务耦合规划
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基于低冗余度染色体编码的族群无人机SAR二维成像任务分配方法 认领 引用
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作者 任航 孙稚超 +1 位作者 杨建宇 武俊杰 《雷达学报（中英文）》 EI CSCD 北大核心 2025年第5期1153-1169,共17页
该文针对族群无人机SAR系统的任务分配问题,提出了一种基于低冗余度染色体编码的族群无人机SAR任务分配方法。该方法针对SAR成像任务的特有问题分析了成像性能与成像几何构型之间的内在联系,并据此建立了考虑成像性能的路径函数,将族群... 该文针对族群无人机SAR系统的任务分配问题,提出了一种基于低冗余度染色体编码的族群无人机SAR任务分配方法。该方法针对SAR成像任务的特有问题分析了成像性能与成像几何构型之间的内在联系,并据此建立了考虑成像性能的路径函数,将族群无人机SAR任务分配问题建模为广义均衡多旅行商问题;然后,采用冗余度较低的两部分染色体编码方式来表征任务分配方案,提高遗传算法的搜索效率和准确性。针对实际应用中可能发生的意外情况,该文还提出了一种融合了合同网算法和注意力机制的动态任务分配策略,该策略能够根据实际情况灵活调整任务分配方案,确保系统的鲁棒性。仿真实验验证了该文所提方法的有效性。 展开更多
关键词 族群无人机 合成孔径雷达 任务分配 遗传算法 染色体编码
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基于一种双层编码的协同配送路径研究 认领 引用
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作者 吕海利 王梓印 张艳伟 《武汉理工大学学报（信息与管理工程版）》 CAS 2025年第6期716-724,共9页
随着无人机技术的不断发展和电子商务市场规模的扩大,无人机与车辆协同配送成为了解决配送成本过高、提升配送效率的重要方式。针对无人机与车辆协同配送问题设计了一种双层编码,基于该双层编码构建了由遗传算法和模拟退火算法组成的混... 随着无人机技术的不断发展和电子商务市场规模的扩大,无人机与车辆协同配送成为了解决配送成本过高、提升配送效率的重要方式。针对无人机与车辆协同配送问题设计了一种双层编码,基于该双层编码构建了由遗传算法和模拟退火算法组成的混合算法。同时,提供一种确保无人机与车辆同时抵达汇合点的计算方式,减少配送时间并防止无人机提前抵达汇合点后出现被盗或被损坏等潜在风险。以目前求解无人机与车辆协同配送问题表现良好的两种编码方式作为对比,实验结果表明所提新型编码方式的最优解和平均解都表现更好。 展开更多
关键词 路径优化 无人机 车辆 协同配送 双层编码 遗传算法 模拟退火算法
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