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An Adaptive Cooperated Shuffled Frog-Leaping Algorithm for Parallel Batch Processing Machines Scheduling in Fabric Dyeing Processes 认领 引用
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作者 Lianqiang Wu Deming Lei Yutong Cai 《Computers, Materials & Continua》 SCIE EI 2025年第5期1771-1789,共19页
Fabric dyeing is a critical production process in the clothing industry and heavily relies on batch processing machines(BPM).In this study,the parallel BPM scheduling problem with machine eligibility in fabric dyeing ... Fabric dyeing is a critical production process in the clothing industry and heavily relies on batch processing machines(BPM).In this study,the parallel BPM scheduling problem with machine eligibility in fabric dyeing is considered,and an adaptive cooperated shuffled frog-leaping algorithm(ACSFLA)is proposed to minimize makespan and total tardiness simultaneously.ACSFLA determines the search times for each memeplex based on its quality,with more searches in high-quality memeplexes.An adaptive cooperated and diversified search mechanism is applied,dynamically adjusting search strategies for each memeplex based on their dominance relationships and quality.During the cooperated search,ACSFLA uses a segmented and dynamic targeted search approach,while in non-cooperated scenarios,the search focuses on local search around superior solutions to improve efficiency.Furthermore,ACSFLA employs adaptive population division and partial population shuffling strategies.Through these strategies,memeplexes with low evolutionary potential are selected for reconstruction in the next generation,while thosewithhighevolutionarypotential are retained to continue their evolution.Toevaluate the performance of ACSFLA,comparative experiments were conducted using ACSFLA,SFLA,ASFLA,MOABC,and NSGA-CC in 90 instances.The computational results reveal that ACSFLA outperforms the other algorithms in 78 of the 90 test cases,highlighting its advantages in solving the parallel BPM scheduling problem with machine eligibility. 展开更多
关键词 Batch processing machine parallel machine scheduling shuffled frog-leaping algorithm fabric dyeing process machine eligibility
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Nonlinear Rayleigh wave inversion based on the shuffled frog-leaping algorithm 认领 引用 被引量：11
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作者 Sun Cheng-Yu Wang Yan-Yan +1 位作者 Wu Dun-Shi Qin Xiao-Jun 《Applied Geophysics》 SCIE CSCD 2017年第4期551-558,622,共8页
At present, near-surface shear wave velocities are mainly calculated through Rayleigh wave dispersion-curve inversions in engineering surface investigations, but the required calculations pose a highly nonlinear globa... At present, near-surface shear wave velocities are mainly calculated through Rayleigh wave dispersion-curve inversions in engineering surface investigations, but the required calculations pose a highly nonlinear global optimization problem. In order to alleviate the risk of falling into a local optimal solution, this paper introduces a new global optimization method, the shuffle frog-leaping algorithm （SFLA）, into the Rayleigh wave dispersion-curve inversion process. SFLA is a swarm-intelligence-based algorithm that simulates a group of frogs searching for food. It uses a few parameters, achieves rapid convergence, and is capability of effective global searching. In order to test the reliability and calculation performance of SFLA, noise-free and noisy synthetic datasets were inverted. We conducted a comparative analysis with other established algorithms using the noise-free dataset, and then tested the ability of SFLA to cope with data noise. Finally, we inverted a real-world example to examine the applicability of SFLA. Results from both synthetic and field data demonstrated the effectiveness of SFLA in the interpretation of Rayleigh wave dispersion curves. We found that SFLA is superior to the established methods in terms of both reliability and computational efficiency, so it offers great potential to improve our ability to solve geophysical inversion problems. 展开更多
关键词 Shuffle frog-leaping algorithm Rayleigh wave dispersion curves non-linear inversion shear wave velocity
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A Shufled Frog-Leaping Algorithm with Competition for Parallel Batch Processing Machines Scheduling in Fabric Dyeing Process 认领 引用 被引量：1
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作者 Mingbo Li Deming Lei 《Computer Modeling in Engineering & Sciences》 SCIE EI 2025年第5期1789-1808,共20页
As a complicated optimization problem,parallel batch processing machines scheduling problem(PBPMSP)exists in many real-life manufacturing industries such as textiles and semiconductors.Machine eligibility means that a... As a complicated optimization problem,parallel batch processing machines scheduling problem(PBPMSP)exists in many real-life manufacturing industries such as textiles and semiconductors.Machine eligibility means that at least one machine is not eligible for at least one job.PBPMSP and scheduling problems with machine eligibility are frequently considered;however,PBPMSP with machine eligibility is seldom explored.This study investigates PBPMSP with machine eligibility in fabric dyeing and presents a novel shuffled frog-leaping algorithm with competition(CSFLA)to minimize makespan.In CSFLA,the initial population is produced in a heuristic and random way,and the competitive search of memeplexes comprises two phases.Competition between any two memeplexes is done in the first phase,then iteration times are adjusted based on competition,and search strategies are adjusted adaptively based on the evolution quality of memeplexes in the second phase.An adaptive population shuffling is given.Computational experiments are conducted on 100 instances.The computational results showed that the new strategies of CSFLA are effective and that CSFLA has promising advantages in solving the considered PBPMSP. 展开更多
关键词 Batch processing machines shuffled frog-leaping algorithm competition parallel machines scheduling
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An Adaptive Shuffled Frog-Leaping Algorithm for Hybrid-Flow Shop Scheduling with No Precedence Between Some Stages 认领 引用
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作者 Zhenghui Yin Deming Lei Bo Yang 《Complex System Modeling and Simulation》 EI 2024年第3期292-302,共11页
Hybrid flow shop scheduling problem(HFSP)has been extensively considered,however,some reallife conditions are seldom investigated.In this study,HFsP with no precedence between some stages is solved and an adaptive shu... Hybrid flow shop scheduling problem(HFSP)has been extensively considered,however,some reallife conditions are seldom investigated.In this study,HFsP with no precedence between some stages is solved and an adaptive shuffled frog-leaping algorithm(ASFLA)is developed to optimize makespan.A new solution representation and a decoding procedure are presented,an adaptive memeplex search and dynamical population shuffling are implemented together.Many computational experiments are implemented.Computational results prove that the new strategies of ASFLA are effective and ASFLA is very competitive in solving HFSP with no precedence between some stages. 展开更多
关键词 hybrid-flow shop scheduling shuffled frog-leaping algorithm precedence
Test Case Prioritization in Unit and Integration Testing:A Shuffled-Frog-Leaping Approach 认领 引用
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作者 Atulya Gupta Rajendra Prasad Mahapatra 《Computers, Materials & Continua》 SCIE EI 2023年第3期5369-5387,共19页
Both unit and integration testing are incredibly crucial for almost any software application because each of them operates a distinct process to examine the product.Due to resource constraints,when software is subject... Both unit and integration testing are incredibly crucial for almost any software application because each of them operates a distinct process to examine the product.Due to resource constraints,when software is subjected to modifications,the drastic increase in the count of test cases forces the testers to opt for a test optimization strategy.One such strategy is test case prioritization(TCP).Existing works have propounded various methodologies that re-order the system-level test cases intending to boost either the fault detection capabilities or the coverage efficacy at the earliest.Nonetheless,singularity in objective functions and the lack of dissimilitude among the re-ordered test sequences have degraded the cogency of their approaches.Considering such gaps and scenarios when the meteoric and continuous updations in the software make the intensive unit and integration testing process more fragile,this study has introduced a memetics-inspired methodology for TCP.The proposed structure is first embedded with diverse parameters,and then traditional steps of the shuffled-frog-leaping approach(SFLA)are followed to prioritize the test cases at unit and integration levels.On 5 standard test functions,a comparative analysis is conducted between the established algorithms and the proposed approach,where the latter enhances the coverage rate and fault detection of re-ordered test sets.Investigation results related to the mean average percentage of fault detection(APFD)confirmed that the proposed approach exceeds the memetic,basic multi-walk,PSO,and optimized multi-walk by 21.7%,13.99%,12.24%,and 11.51%,respectively. 展开更多
关键词 Test case prioritization unit testing shuffled frog leaping approach memetic based optimization algorithm integration testing
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Genetic-Frog-Leaping Algorithm for Text Document Clustering 认领 引用 被引量：1
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作者 Lubna Alhenak Manar Hosny 《Computers, Materials & Continua》 SCIE EI 2019年第9期1045-1074,共30页
In recent years,the volume of information in digital form has increased tremendously owing to the increased popularity of the World Wide Web.As a result,the use of techniques for extracting useful information from lar... In recent years,the volume of information in digital form has increased tremendously owing to the increased popularity of the World Wide Web.As a result,the use of techniques for extracting useful information from large collections of data,and particularly documents,has become more necessary and challenging.Text clustering is such a technique;it consists in dividing a set of text documents into clusters(groups),so that documents within the same cluster are closely related,whereas documents in different clusters are as different as possible.Clustering depends on measuring the content(i.e.,words)of a document in terms of relevance.Nevertheless,as documents usually contain a large number of words,some of them may be irrelevant to the topic under consideration or redundant.This can confuse and complicate the clustering process and make it less accurate.Accordingly,feature selection methods have been employed to reduce data dimensionality by selecting the most relevant features.In this study,we developed a text document clustering optimization model using a novel genetic frog-leaping algorithm that efficiently clusters text documents based on selected features.The proposed approach is based on two metaheuristic algorithms:a genetic algorithm(GA)and a shuffled frog-leaping algorithm(SFLA).The GA performs feature selection,and the SFLA performs clustering.To evaluate its effectiveness,the proposed approach was tested on a well-known text document dataset:the“20Newsgroup”dataset from the University of California Irvine Machine Learning Repository.Overall,after multiple experiments were compared and analyzed,it was demonstrated that using the proposed algorithm on the 20Newsgroup dataset greatly facilitated text document clustering,compared with classical K-means clustering.Nevertheless,this improvement requires longer computational time. 展开更多
关键词 Text documents clustering meta-heuristic algorithms shuffled frog-leaping algorithm genetic algorithm feature selection
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A ε-indicator-based shuffled frog leaping algorithm for many-objective optimization problems 认领 引用 被引量：1
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作者 WANG Na SU Yuchao +2 位作者 CHEN Xiaohong LI Xia LIU Dui 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2020年第1期142-155,共14页
Many-objective optimization problems take challenges to multi-objective evolutionary algorithms.A number of nondominated solutions in population cause a difficult selection towards the Pareto front.To tackle this issu... Many-objective optimization problems take challenges to multi-objective evolutionary algorithms.A number of nondominated solutions in population cause a difficult selection towards the Pareto front.To tackle this issue,a series of indicatorbased multi-objective evolutionary algorithms(MOEAs)have been proposed to guide the evolution progress and shown promising performance.This paper proposes an indicator-based manyobjective evolutionary algorithm calledε-indicator-based shuffled frog leaping algorithm(ε-MaOSFLA),which adopts the shuffled frog leaping algorithm as an evolutionary strategy and a simple and effectiveε-indicator as a fitness assignment scheme to press the population towards the Pareto front.Compared with four stateof-the-art MOEAs on several standard test problems with up to 50 objectives,the experimental results show thatε-MaOSFLA outperforms the competitors. 展开更多
关键词 evolutionary algorithm many-objective optimization shuffled frog leaping algorithm(SFLA) ε-indicator
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Membrane-inspired quantum shuffled frog leaping algorithm for spectrum allocation 认领 引用 被引量：3
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作者 Hongyuan Gao Jinlong Cao 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2012年第5期679-688,共10页
To solve discrete optimization difficulty of the spectrum allocation problem,a membrane-inspired quantum shuffled frog leaping（MQSFL） algorithm is proposed.The proposed MQSFL algorithm applies the theory of membrane... To solve discrete optimization difficulty of the spectrum allocation problem,a membrane-inspired quantum shuffled frog leaping（MQSFL） algorithm is proposed.The proposed MQSFL algorithm applies the theory of membrane computing and quantum computing to the shuffled frog leaping algorithm,which is an effective discrete optimization algorithm.Then the proposed MQSFL algorithm is used to solve the spectrum allocation problem of cognitive radio systems.By hybridizing the quantum frog colony optimization and membrane computing,the quantum state and observation state of the quantum frogs can be well evolved within the membrane structure.The novel spectrum allocation algorithm can search the global optimal solution within a reasonable computation time.Simulation results for three utility functions of a cognitive radio system are provided to show that the MQSFL spectrum allocation method is superior to some previous spectrum allocation algorithms based on intelligence computing. 展开更多
关键词 quantum shuffled frog leaping algorithm membrane computing spectrum allocation cognitive radio
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Shuffled frog leaping algorithm with non-dominated sorting for dynamic weapon-target assignment 认领 引用 被引量：4
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作者 ZHAO Yang LIU Jicheng +1 位作者 JIANG Ju ZHEN Ziyang 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2023年第4期1007-1019,共13页
The dynamic weapon target assignment(DWTA)problem is of great significance in modern air combat.However,DWTA is a highly complex constrained multi-objective combinatorial optimization problem.An improved elitist non-d... The dynamic weapon target assignment(DWTA)problem is of great significance in modern air combat.However,DWTA is a highly complex constrained multi-objective combinatorial optimization problem.An improved elitist non-dominated sorting genetic algorithm-II(NSGA-II)called the non-dominated shuffled frog leaping algorithm(NSFLA)is proposed to maximize damage to enemy targets and minimize the self-threat in air combat constraints.In NSFLA,the shuffled frog leaping algorithm(SFLA)is introduced to NSGA-II to replace the inside evolutionary scheme of the genetic algorithm(GA),displaying low optimization speed and heterogeneous space search defects.Two improvements have also been raised to promote the internal optimization performance of SFLA.Firstly,the local evolution scheme,a novel crossover mechanism,ensures that each individual participates in updating instead of only the worst ones,which can expand the diversity of the population.Secondly,a discrete adaptive mutation algorithm based on the function change rate is applied to balance the global and local search.Finally,the scheme is verified in various air combat scenarios.The results show that the proposed NSFLA has apparent advantages in solution quality and efficiency,especially in many aircraft and the dynamic air combat environment. 展开更多
关键词 dynamic weapon-target assignment(DWTA)problem shuffled frog leaping algorithm(SFLA) air combat research
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Improved Shuffled Frog Leaping Algorithm Optimizing Integral Separated PID Control for Unmanned Hypersonic Vehicle 认领 引用 被引量：2
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作者 梁冰冰 江驹 +1 位作者 甄子洋 马坤 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2015年第1期110-114,共5页
To solve the flight control problem for unmanned hypersonic vehicles,a novel intelligent optimized control method is proposed.A flight control system based on integral separated proportional-integral-derivative(PID)co... To solve the flight control problem for unmanned hypersonic vehicles,a novel intelligent optimized control method is proposed.A flight control system based on integral separated proportional-integral-derivative(PID)control is designed for hypersonic vehicle,and an improved shuffled frog leaping algorithm is presented to optimize the control parameters.A nonlinear model of hypersonic vehicle is established to examine the dynamic characteristics achieved by the flight control system.Simulation results demonstrate that the proposed optimized controller can effectively achieve better flight control performance than the traditional controller. 展开更多
关键词 hypersonic vehicles flight control shuffled frog leaping algorithm unmanned aerial vehicles(UAVs)
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Quantitative algorithm for airborne gamma spectrum of large sample based on improved shuffled frog leaping-particle swarm optimization convolutional neural network 认领 引用 被引量：2
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作者 Fei Li Xiao-Fei Huang +5 位作者 Yue-Lu Chen Bing-Hai Li Tang Wang Feng Cheng Guo-Qiang Zeng Mu-Hao Zhang 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2023年第7期242-252,共11页
In airborne gamma ray spectrum processing,different analysis methods,technical requirements,analysis models,and calculation methods need to be established.To meet the engineering practice requirements of airborne gamm... In airborne gamma ray spectrum processing,different analysis methods,technical requirements,analysis models,and calculation methods need to be established.To meet the engineering practice requirements of airborne gamma-ray measurements and improve computational efficiency,an improved shuffled frog leaping algorithm-particle swarm optimization convolutional neural network(SFLA-PSO CNN)for large-sample quantitative analysis of airborne gamma-ray spectra is proposed herein.This method was used to train the weight of the neural network,optimize the structure of the network,delete redundant connections,and enable the neural network to acquire the capability of quantitative spectrum processing.In full-spectrum data processing,this method can perform the functions of energy spectrum peak searching and peak area calculations.After network training,the mean SNR and RMSE of the spectral lines were 31.27 and 2.75,respectively,satisfying the demand for noise reduction.To test the processing ability of the algorithm in large samples of airborne gamma spectra,this study considered the measured data from the Saihangaobi survey area as an example to conduct data spectral analysis.The results show that calculation of the single-peak area takes only 0.13~0.15 ms,and the average relative errors of the peak area in the U,Th,and K spectra are 3.11,9.50,and 6.18%,indicating the high processing efficiency and accuracy of this algorithm.The performance of the model can be further improved by optimizing related parameters,but it can already meet the requirements of practical engineering measurement.This study provides a new idea for the full-spectrum processing of airborne gamma rays. 展开更多
关键词 Large sample Airborne gamma spectrum(AGS) Shuffled frog leaping algorithm(SFLA) Particle swarm optimization(PSO) Convolutional neural network(CNN)
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Control Strategy for a Quadrotor Based on a Memetic Shuffled Frog Leaping Algorithm 认领 引用 被引量：1
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作者 Nour Ben Ammar Hegazy Rezk Soufiene Bouallègue 《Computers, Materials & Continua》 SCIE EI 2021年第6期4081-4100,共20页
This work presents a memetic Shuffled Frog Leaping Algorithm(SFLA)based tuning approach of an Integral Sliding Mode Controller(ISMC)for a quadrotor type of Unmanned Aerial Vehicles(UAV).Based on the Newton–Euler form... This work presents a memetic Shuffled Frog Leaping Algorithm(SFLA)based tuning approach of an Integral Sliding Mode Controller(ISMC)for a quadrotor type of Unmanned Aerial Vehicles(UAV).Based on the Newton–Euler formalism,a nonlinear dynamic model of the studied quadrotor is firstly established for control design purposes.Since the main parameters of the ISMC design are the gains of the sliding surfaces and signum functions of the switching control law,which are usually selected by repetitive and time-consuming trials-errors based procedures,a constrained optimization problem is formulated for the systematically tuning of these unknown variables.Under time-domain operating constraints,such an optimization-based tuning problem is effectively solved using the proposed SFLA metaheuristic with an empirical comparison to other evolutionary computation-and swarm intelligence-based algorithms such as the Crow Search Algorithm(CSA),Fractional Particle Swarm Optimization Memetic Algorithm(FPSOMA),Ant Bee Colony(ABC)and Harmony Search Algorithm(HSA).Numerical experiments are carried out for various sets of algorithms’parameters to achieve optimal gains of the sliding mode controllers for the altitude and attitude dynamics stabilization.Comparative studies revealed that the SFLA is a competitive and easily implemented algorithm with high performance in terms of robustness and non-premature convergence.Demonstrative results verified that the proposed metaheuristicsbased approach is a promising alternative for the systematic tuning of the effective design parameters in the integral sliding mode control framework. 展开更多
关键词 Quadrotor modeling integral sliding mode control gains tuning advanced metaheuristics memetic algorithms shuffled frog leaping algorithm
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Modified Shuffled Frog Leaping Algorithm for Solving Economic Load Dispatch Problem 认领 引用 被引量：2
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作者 Priyanka Roy A. Chakrabarti 《Energy and Power Engineering》 2011年第4期551-556,共6页
In the recent restructured power system scenario and complex market strategy, operation at absolute minimum cost is no longer the only criterion for dispatching electric power. The economic load dispatch (ELD) problem... In the recent restructured power system scenario and complex market strategy, operation at absolute minimum cost is no longer the only criterion for dispatching electric power. The economic load dispatch (ELD) problem which accounts for minimization of both generation cost and power loss is itself a multiple conflicting objective function problem. In this paper, a modified shuffled frog-leaping algorithm (MSFLA), which is an improved version of memetic algorithm, is proposed for solving the ELD problem. It is a relatively new evolutionary method where local search is applied during the evolutionary cycle. The idea of memetic algorithm comes from memes, which unlike genes can adapt themselves. The performance of MSFLA has been shown more efficient than traditional evolutionary algorithms for such type of ELD problem. The application and validity of the proposed algorithm are demonstrated for IEEE 30 bus test system as well as a practical power network of 203 bus 264 lines 23 machines system. 展开更多
关键词 Economic Load Dispatch Modified Shuffled Frog Leaping Algorithm Genetic Algorithm
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一种交叠的Shuffled-BP LDPC译码算法 认领 引用 被引量：4
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作者 范亚楠 王丽冲 +1 位作者 姚秀娟 孟新 《电子与信息学报》 EI CAS CSCD 北大核心 2016年第11期2908-2915,共8页
Shuffled-BP(SBP)译码算法是一种基于变量节点的串行消息传递译码算法,其收敛速度快于原有的置信度传播译码算法,然而由于实际工程实现中的半并行化处理,其收敛速度和误码性能均有所降低。为了进一步提高SBP算法的性能,该文提出一种交叠... Shuffled-BP(SBP)译码算法是一种基于变量节点的串行消息传递译码算法,其收敛速度快于原有的置信度传播译码算法,然而由于实际工程实现中的半并行化处理,其收敛速度和误码性能均有所降低。为了进一步提高SBP算法的性能,该文提出一种交叠的Shuffled-BP(Overlapped Shuffled-BP,OSBP)译码算法。该算法采用若干个相同的子译码器以不同的更新顺序同时进行更新,对于每个变量节点,在每次迭代更新后选取最可靠的信息参与下一次迭代,以此提高迭代的收敛速度。理论分析和仿真实验均表明,在不增加额外存储空间的条件下,OSBP算法相比于SBP算法有着更优的误码性能以及更快的收敛速度。此外,提出的OSBP算法对于规则和不规则LDPC码均有效。 展开更多
关键词 LDPC码 收敛速度 译码算法 Shuffled-BP 交叠的Shuffled-BP
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基于精确统计的Spark均衡重分区方法 认领 引用
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作者 张军 余凤琦 《计算机工程与设计》 北大核心 2026年第4期974-982,共9页
Spark Shuffle过程中因不同分区间的数据分布倾斜易导致Spark集群分布式计算性能下降,对此,提出了基于精确统计的Spark均衡重分区方法 BPPS。该方法采用基于单次遍历的精确统计算法,对Map任务输出的中间数据进行高效统计,从而捕捉Spark... Spark Shuffle过程中因不同分区间的数据分布倾斜易导致Spark集群分布式计算性能下降,对此,提出了基于精确统计的Spark均衡重分区方法 BPPS。该方法采用基于单次遍历的精确统计算法,对Map任务输出的中间数据进行高效统计,从而捕捉Spark中间数据的分布情况,以判断是否会出现数据倾斜。如果出现数据倾斜,则根据统计得到的中间数据分布情况进行均衡重分区,使不同分区的数据分布趋于均衡。实验结果表明,相比于Hash分区算法和Range分区算法,BPPS方法平均执行时间分别降低32.37%和63.22%,有效实现了性能优化。 展开更多
关键词 Apache Spark框架 分布式计算 Shuffle机制 数据倾斜 重分区算法 负载均衡 性能优化
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基于电解槽效率和成本模型的可再生能源制氢园区设备容量优化 认领 引用
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作者 刘宇 毛煜东 +1 位作者 杨开敏 刘吉营 《热力发电》 CAS CSCD 北大核心 2026年第1期102-112,共11页
为了解决风、光等可再生能源发电制氢中电力输出的间歇性与不稳定性问题,实现绿电制氢设备的最优配置非常重要。研究引入离散组合优化算法与多目标蛙跳优化算法,针对纯光伏、纯风电和光伏-风电混合系统可再生能源发电的园区规划展开优化... 为了解决风、光等可再生能源发电制氢中电力输出的间歇性与不稳定性问题,实现绿电制氢设备的最优配置非常重要。研究引入离散组合优化算法与多目标蛙跳优化算法,针对纯光伏、纯风电和光伏-风电混合系统可再生能源发电的园区规划展开优化,构建电解槽系统效率与运行功率、成本与容量的模型。结果显示:在光伏容量2.60 MW和风电容量3.80 MW的混合系统中,氢平准化成本最低为17.83元/kg,电解槽满负荷小时数约3 400 h;经多目标蛙跳优化算法优化后,最优配置为光伏容量1.50 MW、风电容量0.55 MW,其最大制氢量2 949.62 kg。光伏-风电混合系统既能降低氢平准化成本,又能增加满负荷运行时间,可为未来可再生能源制氢的科学规划提供理论参考。 展开更多
关键词 可再生能源 绿色制氢 电解槽 离散组合优化 多目标蛙跳优化算法
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基于移动贝叶斯和左右手法则的GPSR协议 认领 引用
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作者 周德宇 戴海燕 《计算机系统应用》 2026年第4期200-213,共14页
针对车联网(Internet of Vehicles,IoV)中大多数基于位置的路由协议存在传输时延高的问题,提出一种基于移动贝叶斯和仿生智能算法的路由协议.首先,该协议在原贪心周界无状态路由(greedy perimeter stateless routing,GPSR)协议的基础上... 针对车联网(Internet of Vehicles,IoV)中大多数基于位置的路由协议存在传输时延高的问题,提出一种基于移动贝叶斯和仿生智能算法的路由协议.首先,该协议在原贪心周界无状态路由(greedy perimeter stateless routing,GPSR)协议的基础上引入动态贝叶斯网络(dynamic Bayesian network,DBN),用于预测车辆下一时刻位置,然后确定下一时刻距离源节点最远且最可靠的节点.基于所确定的节点确定可信通信范围,在可信通信范围内添加移动性的概念来选择下一跳.其次,如果不符合贪心转发条件而转入周界转发,该协议采用混合蛙跳算法(shuffled frog leaping algorithm,SFLA)、蚁群优化算法(ant colony optimization algorithm,ACO)和左右手法则来确定下一跳路由路径.实验结果表明,该协议在高速公路场景中的数据包丢失率(packet loss rate,PLR)和吞吐量均优于经典GPSR、无线自组网按需平面距离向量路由(ad-hoc on-demand distance vector routing,AODV)协议、基于粒子群优化的GPSR(particle swarm optimization based GPSR,PSO-GPSR)协议和最大累计通信持续时间最小角度GPSR(maxduration-minangle GPSR,MM-GPSR)协议. 展开更多
关键词 贪心周界无状态路由 贝叶斯 混合蛙跳算法 蚁群优化算法 左右手法则
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Construction of Quasi-Cyclic Low-Density Parity-Check Codes for Simplifying Shuffle Networks in Layered Decoder 认领 引用 被引量：1
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作者 张建军 董明科 +2 位作者 王达 金野 项海格 《China Communications》 SCIE CSCD 2013年第12期102-113,共12页
Offset Shuffle Networks(OSNs) interleave a-posterior probability messages in the Block Row-Layered Decoder(BRLD) of QuasiCyclic Low-Density Parity-Check(QC-LDPC)codes.However,OSNs usually consume a significant amount ... Offset Shuffle Networks(OSNs) interleave a-posterior probability messages in the Block Row-Layered Decoder(BRLD) of QuasiCyclic Low-Density Parity-Check(QC-LDPC)codes.However,OSNs usually consume a significant amount of computational resources and limit the clock frequency,particularly when the size of the Circulant Permutation Matrix(CPM)is large.To simplify the architecture of the OSN,we propose a Simplified Offset Shuffle Network Block Progressive Edge-Growth(SOSNBPEG) algorithm to construct a class of QCLDPC codes.The SOSN-BPEG algorithm constrains the shift values of CPMs and the difference of the shift values in the same column by progressively appending check nodes.Simulation results indicate that the error performance of the SOSN-BPEG codes is the same as that of the codes in WiMAX and DVB-S2.The SOSNBPEG codes can reduce the complexity of the OSNs by up to 54.3%,and can improve the maximum frequency by up to 21.7%for various code lengths and rates. 展开更多
关键词 QC-LDPC codes construction alg-orithm PEG algorithm row-layered decoder shuffle network
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A comparative study of GA,PSO and SCE algorithms for estimating kinetics of biomass pyrolysis 认领 引用
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作者 Hongfang Wang Junhui Gong 《Emergency Management Science and Technology》 2023年第1期136-145,共10页
Optimization performances of three most frequently utilized optimization algorithms,GA(Genetic Algorithm),PSO(Particle Swarm Optimization),and SCE(Shuffled Complex Evolution),are compared to examine their accuracy,com... Optimization performances of three most frequently utilized optimization algorithms,GA(Genetic Algorithm),PSO(Particle Swarm Optimization),and SCE(Shuffled Complex Evolution),are compared to examine their accuracy,computation efficiency,and convergence efficiency.Micro scale TGA(thermogravimetric analysis)experiments of wood were conducted at three heating rates to collect the necessary data for analysis.Gauss multi-peak fitting method was first applied to identify the contribution of each component of wood to the mass loss rate(MLR)curves.Then the Kissinger method and three isoconversional methods,including KAS,Tang,and DAEM methods,were employed to extract kinetics of wood pyrolysis.The average values of the four sets of solutions were adopted to determine the search range in the following optimizations.A thermally thin numerical model was developed to inversely model the collected experimental data combining the three algorithms.The results showed that wood pyrolysis can be described by a four-component parallel reaction scheme.The four sets of kinetic parameters derived using different analytical methods are very close to each other.When extracting kinetics from experimental data using numerical model and optimization algorithms,the accuracies of the three algorithms are ranked as SCE>PSO>GA.While the computation efficiencies and convergency efficiencies are ranked as GA≈PSO>SCE and PSO>SCE>GA,indicating each algorithm has its inherent advantages and limits.In most optimization applications,PSO is more favorable considering its better overall performance. 展开更多
关键词 identify contribution each component genetic algorithm optimization algorithmsga genetic algorithm pso particle swarm optimization optimization algorithms shuffled complex evolution thermogravimetric analysis sce shuffled complex evolution particle swarm optimization
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混合离散蛙跳算法求解柔性装配系统调度问题 认领 引用 被引量：1
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作者 李晓玲 冯彦翔 +1 位作者 张广辉 段浩浩 《控制理论与应用》 EI CAS CSCD 北大核心 2025年第4期816-826,共11页
本文主要研究不含中间缓冲区的柔性装配系统(FAS)的优化调度问题,其中当工件竞争使用有限的生产资源时,不合理的资源分配会导致系统死锁(deadlock).针对易死锁(deadlock-prone)FAS的优化调度问题,本文采用Petri网建模,提出了一种混合离... 本文主要研究不含中间缓冲区的柔性装配系统(FAS)的优化调度问题,其中当工件竞争使用有限的生产资源时,不合理的资源分配会导致系统死锁(deadlock).针对易死锁(deadlock-prone)FAS的优化调度问题,本文采用Petri网建模,提出了一种混合离散蛙跳算法(HDSFLA)以最小化最大完工时间(makespan).首先,提出了一种新的编码解码方法,其中一个个体编码为一个包含全部工件加工信息的变迁序列,可解码为一个工件–工序序列;其次,为了保证种群中个体的可行性,提出了一个个体修正算法和基于最早引发时间的改进个体修正算法,从而将不可行个体修复为可行个体;然后,结合编码特征设计了用于生成新个体的交叉操作;最后,为了平衡算法的全局搜索和局部开发能力,设计了一个基于交换和插入算子的局部搜索策略.通过不同规模算例上的仿真实验和算法对比分析,验证了HDSFLA的有效性. 展开更多
关键词 柔性装配系统 死锁 Petri网 调度 混合离散蛙跳算法
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