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Global optimal path planning for mobile robot based onimproved Dijkstra algorithm and ant system algorithm 认领 引用 被引量：23
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作者 谭冠政 贺欢 Aaron Sloman 《Journal of Central South University of Technology》 2006年第1期80-86,共7页
A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK ... A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is adopting the improved Dijkstra algorithm to find out a sub-optimal collision-free path, and the third step is using the ant system algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path for the mobile robot. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the hybrid genetic algorithm in the global optimal path planning. 展开更多
关键词 mobile robot global optimal path planning improved Dijkstra algorithm ant system algorithm MAKLINK graph free MAKLINK line
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Intelligent PID controller based on ant system algorithm and fuzzy inference and its application to bionic artificial leg 认领 引用 被引量：3
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作者 谭冠政 曾庆冬 李文斌 《Journal of Central South University of Technology》 2004年第3期316-322,共7页
A designing method of intelligent proportional-integral-derivative(PID) controllers was proposed based on the ant system algorithm and fuzzy inference. This kind of controller is called Fuzzy-ant system PID controller... A designing method of intelligent proportional-integral-derivative(PID) controllers was proposed based on the ant system algorithm and fuzzy inference. This kind of controller is called Fuzzy-ant system PID controller. It consists of an off-line part and an on-line part. In the off-line part, for a given control system with a PID controller,by taking the overshoot, setting time and steady-state error of the system unit step response as the performance indexes and by using the ant system algorithm, a group of optimal PID parameters K*p , Ti* and T*d can be obtained, which are used as the initial values for the on-line tuning of PID parameters. In the on-line part, based on Kp* , Ti*and Td* and according to the current system error e and its time derivative, a specific program is written, which is used to optimize and adjust the PID parameters on-line through a fuzzy inference mechanism to ensure that the system response has optimal transient and steady-state performance. This kind of intelligent PID controller can be used to control the motor of the intelligent bionic artificial leg designed by the authors. The result of computer simulation experiment shows that the controller has less overshoot and shorter setting time. 展开更多
关键词 ant system algorithm fuzzy inference PID controller Fuzzy-ant system PID controller intelligent bionic artificial leg
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Satellite Constellation Design with Adaptively Continuous Ant System Algorithm 认领 引用 被引量：7
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作者 He Quan Han Chao 《Chinese Journal of Aeronautics》 SCIE EI CAS 2007年第4期297-303,共7页
The ant system algorithm （ASA） has proved to be a novel meta-heuristic algorithm to solve many multivariable problems. In this paper, the earth coverage of satellite constellation is analyzed and a n ＋ 1^ -fold cov... The ant system algorithm （ASA） has proved to be a novel meta-heuristic algorithm to solve many multivariable problems. In this paper, the earth coverage of satellite constellation is analyzed and a n ＋ 1^ -fold coverage rate is put forward to evaluate the coverage performance of a satellite constellation. An optimization model of constellation parameters is established on the basis of the coverage performance. As a newly developed method, ASA can be applied to optimize the constellation parameters. In order to improve the ASA, a rule for adaptive number of ants is proposed, by which the search range is obviously enlarged and the convergence speed increased. Simulation results have shown that the ASA is more quick and efficient than other methodV211.71s. 展开更多
关键词 ant system algorithm satellite constellation optimization design coverage performance adaptive adjusting
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Design of PID controller with incomplete derivation based on ant system algorithm 认领 引用 被引量：10
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作者 Guanzheng TAN Qingdong ZENG Wenbin LI 《控制理论与应用（英文版）》 2004年第3期246-252,共7页
A new and intelligent design method for PID controller with incomplete derivation is proposed based on the ant system algorithm ( ASA) . For a given control system with this kind of PID controller, a group of optimal ... A new and intelligent design method for PID controller with incomplete derivation is proposed based on the ant system algorithm ( ASA) . For a given control system with this kind of PID controller, a group of optimal PID controller parameters K p * , T i * , and T d * can be obtained by taking the overshoot, settling time, and steady-state error of the system's unit step response as the performance indexes and by use of our improved ant system algorithm. K p * , T i * , and T d * can be used in real-time control. This kind of controller is called the ASA-PID controller with incomplete derivation. To verify the performance of the ASA-PID controller, three different typical transfer functions were tested, and three existing typical tuning methods of PID controller parameters, including the Ziegler-Nichols method (ZN),the genetic algorithm (GA),and the simulated annealing (SA), were adopted for comparison. The simulation results showed that the ASA-PID controller can be used to control different objects and has better performance compared with the ZN-PID and GA-PID controllers, and comparable performance compared with the SA-PID controller. 展开更多
关键词 PID controller Incomplete derivation Parameter tuning Ant system algorithm Genetic algorithm Simulated annealing
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Novel Voltage Scaling Algorithm Through Ant Colony Optimization for Embedded Distributed Systems 认领 引用
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作者 章立生 丁丹 《Journal of Beijing Institute of Technology》 EI CAS 2007年第4期430-436,共7页
Dynamic voltage scaling (DVS), supported by many DVS-enabled processors, is an efficient technique for energy-efficient embedded systems. Many researchers work on DVS and have presented various DVS algorithms, some wi... Dynamic voltage scaling (DVS), supported by many DVS-enabled processors, is an efficient technique for energy-efficient embedded systems. Many researchers work on DVS and have presented various DVS algorithms, some with quite good results. However, the previous algorithms either have a large time complexity or obtain results sensitive to the count of the voltage modes. Fine-grained voltage modes lead to optimal results, but coarse-grained voltage modes cause less optimal one. A new algorithm is presented, which is based on ant colony optimization, called ant colony optimization voltage and task scheduling (ACO-VTS) with a low time complexity implemented by parallelizing and its linear time approximation algorithm. Both of them generate quite good results, saving up to 30% more energy than that of the previous ones under coarse-grained modes, and their results don’t depend on the number of modes available. 展开更多
关键词 dynamic voltage algorithm distributed system ant colony optimization multi-processor
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Improved Multi-objective Ant Colony Optimization Algorithm and Its Application in Complex Reasoning 认领 引用 被引量：4
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作者 WANG Xinqing ZHAO Yang +2 位作者 WANG Dong ZHU Huijie ZHANG Qing 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2013年第5期1031-1040,共10页
The problem of fault reasoning has aroused great concern in scientific and engineering fields.However,fault investigation and reasoning of complex system is not a simple reasoning decision-making problem.It has become... The problem of fault reasoning has aroused great concern in scientific and engineering fields.However,fault investigation and reasoning of complex system is not a simple reasoning decision-making problem.It has become a typical multi-constraint and multi-objective reticulate optimization decision-making problem under many influencing factors and constraints.So far,little research has been carried out in this field.This paper transforms the fault reasoning problem of complex system into a paths-searching problem starting from known symptoms to fault causes.Three optimization objectives are considered simultaneously: maximum probability of average fault,maximum average importance,and minimum average complexity of test.Under the constraints of both known symptoms and the causal relationship among different components,a multi-objective optimization mathematical model is set up,taking minimizing cost of fault reasoning as the target function.Since the problem is non-deterministic polynomial-hard(NP-hard),a modified multi-objective ant colony algorithm is proposed,in which a reachability matrix is set up to constrain the feasible search nodes of the ants and a new pseudo-random-proportional rule and a pheromone adjustment mechinism are constructed to balance conflicts between the optimization objectives.At last,a Pareto optimal set is acquired.Evaluation functions based on validity and tendency of reasoning paths are defined to optimize noninferior set,through which the final fault causes can be identified according to decision-making demands,thus realize fault reasoning of the multi-constraint and multi-objective complex system.Reasoning results demonstrate that the improved multi-objective ant colony optimization(IMACO) can realize reasoning and locating fault positions precisely by solving the multi-objective fault diagnosis model,which provides a new method to solve the problem of multi-constraint and multi-objective fault diagnosis and reasoning of complex system. 展开更多
关键词 fault reasoning ant colony algorithm Pareto set multi-objective optimization complex system
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Using Data Mining to Find Patterns in Ant Colony Algorithm Solutions to the Travelling Salesman Problem 认领 引用
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作者 阎世梁 王银玲 《现代电子技术》 2007年第5期117-119,共3页
Travelling Salesman Problem(TSP) is a classical optimization problem and it is one of a class of NP-Problem.The purposes of this work is to apply data mining methodologies to explore the patterns in data generated by ... Travelling Salesman Problem(TSP) is a classical optimization problem and it is one of a class of NP-Problem.The purposes of this work is to apply data mining methodologies to explore the patterns in data generated by an Ant Colony Algorithm(ACA) performing a searching operation and to develop a rule set searcher which approximates the ACA′s searcher.An attribute-oriented induction methodology was used to explore the relationship between an operations′ sequence and its attributes and a set of rules has been developed.At the end of this paper,the experimental results have shown that the proposed approach has good performance with respect to the quality of solution and the speed of computation. 展开更多
关键词 数据挖掘 数据管理系统 数据库 数据分析
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基于改进BMO算法的巡检机器人多目标路径规划 认领 引用
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作者 陈秋杰 陈渠 +1 位作者 刘建锋 陈鹏远 《计算机仿真》 2026年第3期294-298,360,共5页
机器人巡检替代人工巡检是未来智能巡检技术发展的方向,当下巡检机器人存在多目标巡检路径规划效率低下的问题,为提升规划搜索收敛性,解决传统路径规划算法存在局部收敛的问题,将自适应藤壶交配算法与蚁群系统规划算法有机融合,构建了AD... 机器人巡检替代人工巡检是未来智能巡检技术发展的方向,当下巡检机器人存在多目标巡检路径规划效率低下的问题,为提升规划搜索收敛性,解决传统路径规划算法存在局部收敛的问题,将自适应藤壶交配算法与蚁群系统规划算法有机融合,构建了AD-BMO-ACS多目标巡检路径规划模型。模型首先采用AD-BMO算法,通过自适应阴茎系数控制模型,在系统选择授精与藤壶种群繁衍的基础上,优化ACS关键参数e1与e2,提升全局最优解求取效率;然后基于优化关键参数,采用蚁周算法对信息素进行迭代以降低系统计算效率;接着通过构建自适应启发模型,通过信息素的更新迭代,以解决系统早熟与局部收敛的问题;最后在阈值高度差设定的基础上,通过构建栅格模型,利用CHT算法确定最优路径的支点位置信息,完成多目标最优路径任务。多目标巡检路径规划仿真结果表明,在25×50巡检规划区域栅格模型上,与A*、Dijkstra和D*Lite三类传统路径规划模型相比,在栅格障碍率为43.1%时,文中模型的规划效率平均提升了6.61%,同时规划路长平均降低了0.61%;从整体上看,在全障碍率下,与传统路径规划模型对比,文中AD-BMO-ACS模型的多目标路径规划效率整体提升了6.73%,同时规划路长降低了1.62%。故本文模型的多目标巡检路径规划效率最优,同时规划路径最优。故综上所述,提出的AD-BMO-ACS巡检机器人多目标路径规划算法在智能巡检领域中具有重要的仿真研究价值。 展开更多
关键词 藤壶交配算法 蚁群系统算法 多目标路径规划 智能巡检
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单基地固定区段动车组乘务交路计划优化编制方法 认领 引用
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作者 陈维亚 叶凤女 +1 位作者 李朵 袁子越 《交通运输系统工程与信息》 EI CSCD 北大核心 2026年第1期148-160,共13页
编制动车组乘务交路计划是高速铁路运输组织的关键技术环节,编制质量直接影响运营乘务成本和乘务员工作效率。针对单基地固定区段动车组乘务交路计划编制问题,提出“少班快转、便乘优先和过夜均衡”优化编制策略,构建兼顾降低运营乘务成... 编制动车组乘务交路计划是高速铁路运输组织的关键技术环节,编制质量直接影响运营乘务成本和乘务员工作效率。针对单基地固定区段动车组乘务交路计划编制问题,提出“少班快转、便乘优先和过夜均衡”优化编制策略,构建兼顾降低运营乘务成本,提高乘务员工作效率及尽可能满足乘务员工作偏好的多目标两阶段优化模型和算法。第1阶段,实施“少班快转”优化策略,构建以最大化乘务区段接续数量和最小化乘务区段总接续时间为双层优化目标的数学模型,设计融合基于帕累托前沿的信息素增量分配策略和混合精英策略的改进蚁群算法,求解获得乘务员数量最少的初始乘务区段接续组合;第2阶段,实施“便乘优先和过夜均衡”优化策略,以第1阶段的优化结果为基础,建立以最小化便乘和异地过夜补贴总费用为优化目标的数学模型,设计启发式算法求解,获得综合最优的乘务交路计划。以兰州局管辖的徐兰高铁动车组开行方案数据为实例,测试模型和算法,求解结果验证了所提出方法能快速求出动车组列车成对开行和非成对开行情形下的乘务交路计划。所提出的优化策略和编制方法可为优化动车组乘务调度提供兼顾经济效益与人员满意度的决策支持,对同类资源优化调度问题也具有参考价值。 展开更多
关键词 铁路运输 乘务交路计划 多目标两阶段优化 固定区段轮乘制 改进蚁群算法
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高精度增材制造控制算法的研究进展 认领 引用
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作者 杨云辉 《电子科技》 2026年第7期76-80,共5页
为了提高增材制造在三维离散堆砌过程中的位置精度,越来越多的高精度增材制造控制算法被国内外工业界应用和研究。增材制造的路径规划需通过多种高精度控制算法来解决台阶效应、空走路径以及运动位置偏差等问题,同时提高制造效率和成品... 为了提高增材制造在三维离散堆砌过程中的位置精度,越来越多的高精度增材制造控制算法被国内外工业界应用和研究。增材制造的路径规划需通过多种高精度控制算法来解决台阶效应、空走路径以及运动位置偏差等问题,同时提高制造效率和成品质量。文中梳理和回顾了造成增材制造精度误差的主要问题,讨论了现行的主要填充算法并分析了填充算法的优缺点和适用条件。文中还总结了应对空走路径的常见遗传算法、蚁群算法原理以及增材制造中自适应控制系统的研究进展,提出了增材制造未大规模应用和未来需重点解决的问题。 展开更多
关键词 增材制造 路径规划 切片算法 蚁群算法 自适应控制 伺服系统 机器人 位置精度
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蚁群系统算法求解比例多处理器开放车间调度问题 认领 引用
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作者 党予卿 陈丁鹏 +4 位作者 李春宝 吴建豪 关越巍 完颜笑如 刘双 《计算机工程与应用》 EI CSCD 北大核心 2026年第16期123-135,共13页
为高效求解比例多处理器开放车间调度问题,提出了一种蚁群系统算法。该算法采用基于阶段的编码方式,结合高效的解码策略,蚂蚁以确定性选择与随机性选择相结合的任务转移策略进行路径搜索,并在搜索与迭代过程中动态更新信息素与启发素浓... 为高效求解比例多处理器开放车间调度问题,提出了一种蚁群系统算法。该算法采用基于阶段的编码方式,结合高效的解码策略,蚂蚁以确定性选择与随机性选择相结合的任务转移策略进行路径搜索,并在搜索与迭代过程中动态更新信息素与启发素浓度,从而避免算法陷入局部最优。该算法引入随机解以扩大搜索范围,提高求解效率。理论分析表明该算法能够在多项式时间内求得较优解。构造了包含100道问题的测试数据集,用于开展参数调优实验与正式数值实验。通过对比其他算法,蚁群系统算法以更少的迭代次数与更短的运行时间求得更高质量的解,从而验证了算法的有效性。研究结果能够为人体数据采集调度优化提供理论依据与方法学支撑。 展开更多
关键词 比例多处理器开放车间调度 蚁群系统算法 数据采集调度 基于阶段的编码
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Ant Lion Optimization Approach for Load Frequency Control of Multi-Area Interconnected Power Systems 认领 引用
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作者 R. Satheeshkumar R. Shivakumar 《Circuits and Systems》 2016年第9期2357-2383,共27页
This work proposes a novel nature-inspired algorithm called Ant Lion Optimizer (ALO). The ALO algorithm mimics the search mechanism of antlions in nature. A time domain based objective function is established to tune ... This work proposes a novel nature-inspired algorithm called Ant Lion Optimizer (ALO). The ALO algorithm mimics the search mechanism of antlions in nature. A time domain based objective function is established to tune the parameters of the PI controller based LFC, which is solved by the proposed ALO algorithm to reach the most convenient solutions. A three-area interconnected power system is investigated as a test system under various loading conditions to confirm the effectiveness of the suggested algorithm. Simulation results are given to show the enhanced performance of the developed ALO algorithm based controllers in comparison with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Bat Algorithm (BAT) and conventional PI controller. These results represent that the proposed BAT algorithm tuned PI controller offers better performance over other soft computing algorithms in conditions of settling times and several performance indices. 展开更多
关键词 Load Frequency Control (LFC) Multi-Area Power System Proportional-Integral (PI) Controller Ant Lion Optimization (ALO) Bat Algorithm (BAT) Genetic Algorithm (GA) Particle Swarm Optimization (PSO)
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一种基于蚁群算法的电力推进系统故障诊断方法 认领 引用
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作者 沈枫 张凯 +1 位作者 柯常国 贾志强 《船电技术》 2026年第1期44-47,共4页
一种基于蚁群算法的电力推进系统故障诊断方法,属于船舶电力推进系统监控系统设计技术领域,是对蚁群算法、故障树分析方法以及船舶电力推进系统故障等进行深入研究的基础上,将蚁群算法和故障树分析方法相结合,首次提出了基于蚁群算法的... 一种基于蚁群算法的电力推进系统故障诊断方法,属于船舶电力推进系统监控系统设计技术领域,是对蚁群算法、故障树分析方法以及船舶电力推进系统故障等进行深入研究的基础上,将蚁群算法和故障树分析方法相结合,首次提出了基于蚁群算法的电力推进系统故障诊断算法。本算法的优点在对船舶电力推进系统故障树进行诊断推理过程中,提供信息素,并能根据诊断结果修正信息素,完成诊断系统的学习,提高了电力推进系统故障诊断效率和准确性。 展开更多
关键词 故障诊断 电力推进系统 蚁群算法
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基于Fisher判别与差分蚁群算法的交通智能配时研究 认领 引用
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作者 杨环瑜 苏丹 赵海清 《佛山科学技术学院学报（自然科学版）》 CAS 2026年第3期58-64,共7页
针对城市交叉口多时段、多方向车流特征复杂、传统信号灯配时方法适应性不足的问题,提出一种融合车流特征量化与智能优化的交通信号配时方法。首先,引入Fisher判别模型对多源路口监控数据进行高维特征融合与多等级判别,实现不同时段、... 针对城市交叉口多时段、多方向车流特征复杂、传统信号灯配时方法适应性不足的问题,提出一种融合车流特征量化与智能优化的交通信号配时方法。首先,引入Fisher判别模型对多源路口监控数据进行高维特征融合与多等级判别,实现不同时段、不同方向车流量的定量估计,为信号灯配时提供精细化数据支撑。在此基础上,结合韦伯斯特理论构建包含信号周期、绿灯时长及排队约束的多约束信号配时优化模型,并采用差分蚁群算法进行求解,以提升连续配时变量空间中的搜索效率与收敛稳定性。算例结果表明,所提方法在车流量估计精度和信号配时效果方面均优于初始配时方案,能够有效降低车辆控制延误和排队长度,提升交叉口通行效率。 展开更多
关键词 智能交通系统 Fisher判别模型 差分蚁群算法
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基于蚁群算法的电动汽车充电调度系统设计与实现 认领 引用
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作者 雷康亮 黄焘 +1 位作者 李浩帆 程旭 《微型电脑应用》 2026年第5期327-330,335,共4页
在大规模调度情况下,传统的电动汽车充电调度方案效果较差,调度耗时较长。为此,设计一种基于蚁群算法的电动汽车充电调度系统。在硬件设计中,详细部署系统车载以及通信的硬件结构;在软件设计中,采用图形化建模的方式规划电动汽车充电,... 在大规模调度情况下,传统的电动汽车充电调度方案效果较差,调度耗时较长。为此,设计一种基于蚁群算法的电动汽车充电调度系统。在硬件设计中,详细部署系统车载以及通信的硬件结构;在软件设计中,采用图形化建模的方式规划电动汽车充电,确定车辆行驶路径、充电站数量、功率平衡等约束条件,利用蚁群算法求解模型,合理安排车辆在不同时间段的充电方案。实验结果表明,与传统系统相比,所设计的系统在不同的调度规模下可以根据电动汽车的充电需求合理地安排车辆,缩短了调度时间,证明了所设计的系统具有一定的实际应用价值。 展开更多
关键词 蚁群算法 电动汽车 充电调度 系统设计
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融合拓扑解耦与启发式蚁群算法的大型齿轮传动系统装配序列规划研究 认领 引用
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作者 刘阳 高畅 +1 位作者 牛一凡 余海东 《传动技术（中英文）》 2026年第2期69-83,共15页
针对大型齿轮传动系统零部件数量庞大、物理关联与工艺约束高度耦合导致的装配序列规划求解效率低下问题,提出一种融合拓扑解耦与启发式蚁群算法的装配序列规划方法。首先通过基于模型的设计技术(MBD)构建装配信息全域映射模型,提取零... 针对大型齿轮传动系统零部件数量庞大、物理关联与工艺约束高度耦合导致的装配序列规划求解效率低下问题,提出一种融合拓扑解耦与启发式蚁群算法的装配序列规划方法。首先通过基于模型的设计技术(MBD)构建装配信息全域映射模型,提取零件间的几何干涉、连接强度及工艺关联,建立装配约束加权网络模型;进而引入图论中的Louvain社区发现算法,以模块度最大化为目标函数对复杂装配网络进行自动聚类与解耦,将全域规划空间划分为局部可控的子模块,实现寻优维度的有效降低;基于此设计一种分层改进蚁群算法,在模块内部利用工艺知识启发因子引导寻优搜索,并实现对候选节点的实时过滤,确保序列的物理可行性。以典型大型行星齿轮箱装配为案例验证方法的有效性,结果表明,所提方法可将寻优空间压缩21个数量级,求解耗时降低38.7%,显著提升大规模零件系统装配序列规划的搜索效率与收敛精度。 展开更多
关键词 齿轮传动系统 装配序列规划 Louvain算法 蚁群算法 加权装配网络
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Storage Assignment Optimization in a Multi-tier Shuttle Warehousing System 认领 引用 被引量：10
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作者 WANG Yanyan MOU Shandong WU Yaohua 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2016年第2期421-429,共9页
The current mathematical models for the storage assignment problem are generally established based on the traveling salesman problem（TSP）,which has been widely applied in the conventional automated storage and retri... The current mathematical models for the storage assignment problem are generally established based on the traveling salesman problem（TSP）,which has been widely applied in the conventional automated storage and retrieval system（AS/RS）.However,the previous mathematical models in conventional AS/RS do not match multi-tier shuttle warehousing systems（MSWS） because the characteristics of parallel retrieval in multiple tiers and progressive vertical movement destroy the foundation of TSP.In this study,a two-stage open queuing network model in which shuttles and a lift are regarded as servers at different stages is proposed to analyze system performance in the terms of shuttle waiting period（SWP） and lift idle period（LIP） during transaction cycle time.A mean arrival time difference matrix for pairwise stock keeping units（SKUs） is presented to determine the mean waiting time and queue length to optimize the storage assignment problem on the basis of SKU correlation.The decomposition method is applied to analyze the interactions among outbound task time,SWP,and LIP.The ant colony clustering algorithm is designed to determine storage partitions using clustering items.In addition,goods are assigned for storage according to the rearranging permutation and the combination of storage partitions in a 2D plane.This combination is derived based on the analysis results of the queuing network model and on three basic principles.The storage assignment method and its entire optimization algorithm method as applied in a MSWS are verified through a practical engineering project conducted in the tobacco industry.The applying results show that the total SWP and LIP can be reduced effectively to improve the utilization rates of all devices and to increase the throughput of the distribution center. 展开更多
关键词 Multi-tier shuttle warehousing system storage assignment optimization open queuing network ant colony clustering algorithm
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基于改进蚁群算法的智能垂直速递柜运维管理系统设计 认领 引用
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作者 姜磊 胡益维 +2 位作者 万优 王宇博 韩世林 《黑龙江科学》 2026年第8期162-164,共3页
当今,物流行业正经历着深刻的变革,传统运维管理模式已难以满足现代智能垂直速递柜的安全、可靠、高效运行需求。为提高物流配送效率和服务质量,设计了基于改进蚁群算法的智能垂直速递柜运维管理系统,对系统硬件和软件进行优化设计,以... 当今,物流行业正经历着深刻的变革,传统运维管理模式已难以满足现代智能垂直速递柜的安全、可靠、高效运行需求。为提高物流配送效率和服务质量,设计了基于改进蚁群算法的智能垂直速递柜运维管理系统,对系统硬件和软件进行优化设计,以实现对智能垂直速递柜运维的高效管理。测试结果表明,系统响应效率较高且负荷较低,能够实现快递包裹的高效存储与便捷取件。 展开更多
关键词 智能垂直速递柜 蚁群算法 运维管理 系统设计
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考虑电解槽寿命的离网风光互补制氢系统双层嵌套配置优化策略研究 认领 引用
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作者 孙浩然 林光伟 +4 位作者 汤纪飞 欧阳彦超 王志敏 祝乔 杨锦 《综合智慧能源》 CAS 2026年第5期56-63,共8页
为精准匹配离网风光互补制氢系统当地资源并降低全生命周期成本,提出了一种容量配置优化方法。通过构建光伏、风机及蓄电池的能效模型,特别是电解槽寿命模型,动态量化制氢功率对设备寿命的影响,突破传统固定寿命假设的局限。以平准化制... 为精准匹配离网风光互补制氢系统当地资源并降低全生命周期成本,提出了一种容量配置优化方法。通过构建光伏、风机及蓄电池的能效模型,特别是电解槽寿命模型,动态量化制氢功率对设备寿命的影响,突破传统固定寿命假设的局限。以平准化制氢成本(LCOH)最小化为目标,设计了一种双层嵌套优化框架:内层采用基于规则的能量管理策略实现功率分配,外层则运用蚁群优化算法进行系统容量参数寻优。选取西藏八宿和青海格尔木的实际风光资源数据进行验证,结果表明,所提策略较传统方法可显著降低LCOH,有效提升系统经济性,为离网制氢系统的工程应用提供理论依据。 展开更多
关键词 电解槽 离网风光互补制氢系统 配置优化 双层嵌套 能量管理 蚁群优化算法
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基于改进蚁群-贪婪算法的四向穿梭车仓储系统货位分配优化 认领 引用 被引量：6
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作者 李丽 刘保国 +2 位作者 武照云 何学武 赵彬彬 《计算机集成制造系统》 EI CSCD 北大核心 2025年第4期1446-1460,共15页
针对四向穿梭车仓储系统中多设备并行作业特点和高效作业的需求,建立了综合考虑出入库效率、货架稳定性、作业均衡度和货物关联性4个因素的货位分配优化模型,并提出一种改进蚁群-贪婪算法(IACGA)的两阶段混合算法对模型进行优化求解。... 针对四向穿梭车仓储系统中多设备并行作业特点和高效作业的需求,建立了综合考虑出入库效率、货架稳定性、作业均衡度和货物关联性4个因素的货位分配优化模型,并提出一种改进蚁群-贪婪算法(IACGA)的两阶段混合算法对模型进行优化求解。该算法综合了蚁群算法的全局寻优能力与贪婪算法的局部优化调整能力,改进了蚁群算法的启发式函数、状态转移策略以及信息素更新规则。通过仿真实验优化了算法的主要参数,验证了算法的有效性。与标准遗传算法、传统蚁群算法和混合蛙跳算法相比,提出的改进蚁群-贪婪算法求解结果更好,货位分配更加合理,且当货物数量越多时,算法优势越明显。 展开更多
关键词 四向穿梭车仓储系统 货位分配 蚁群算法 贪婪算法
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