检索结果-内蒙古大学图书馆

Performance of shuffled frog-leaping algorithm in Finance-Based Scheduling

JOURNAL OF COMPUTING IN CIVIL ENGINEERING 2012年第3期26卷 396-408页

作者： Alghazi, Anas Selim, Shokri Z. Elazouni, Ashraf King Fahd Univ Petr & Minerals Construct Engn & Management Dept Dhahran 31261 Saudi Arabia King Fahd Univ Petr & Minerals Dept Syst Engn Dhahran 31261 Saudi Arabia

Currently, meta-heuristics including the genetic algorithms (GA) and simulated annealing (SA) have been used extensively to solve non-deterministic polynomial-time hard (NP-hard) problems. Continued efforts of researchers to upgrade the performance of the meta-heuristics in use resulted in the evolution of new ones. shuffled frog-leaping algorithm (SFLA) is one of the recently introduced heuristics. The few applications of the SFLA in the literature in different areas demonstrated the capacity of the SFLA to provide high-quality solutions. The main objective of this paper is to further bring the SFLA to the attention of researchers as a potential technique to solve the NP-hard combinatorial problem of finance-based scheduling. The performance of the SFLA is evaluated through benchmarking its results against those of the GA and SA. The traditional problem of generating infeasible solutions in scheduling problems is adequately tackled in the implementations of the GA, SA, and SFLA. Fairly large projects of 120 and 210 activities are used to compare the performance of the three meta-heuristics. Finally, the obtained results indicate that the SFLA improved the quality of solutions with a substantial reduction in the computational time. DOI: 10.1061/(ASCE)CP.1943-5487.0000157. (C) 2012 American Society of Civil Engineers.

关键词： Meta-heuristics Evolutionary algorithms Genetic algorithms Simulated annealing shuffled frog-leaping algorithm Cash flow Financial management Project financing

来源：评论

学校读者我要写书评

暂无评论

An Adaptive shuffled frog-leaping algorithm for Hybrid-Flow Shop Scheduling with No Precedence Between Some Stages

引用

Complex System Modeling and Simulation 2024年第3期4卷 292-302页

作者： Zhenghui Yin Deming Lei Bo Yang School of Automation Wuhan University of TechnologyWuhan 430070China

Hybrid flow shop scheduling problem(HFSP)has been extensively considered,however,some reallife conditions are seldom *** 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 *** computational experiments are *** results prove that the new strategies of ASFLA are effective and ASFLA is very competitive in solving HFSP with no precedence between some stages.

关键词： hybrid-flow shop scheduling shuffled frog-leaping algorithm precedence

来源：评论

学校读者我要写书评

暂无评论

Optimal inverse magnetorheological damper modeling using shuffled frog-leaping algorithm-based adaptive neuro-fuzzy inference system approach

引用

ADVANCES IN MECHANICAL ENGINEERING 2016年第8期8卷 1687814016662770-1687814016662770页

作者： Lin, Xiufang Chen, Shumei Fuzhou Univ Coll Mech Engn Fuzhou 350116 Peoples R China Fujian Agr & Forestry Univ Dept Informat & Mechatron Engn Jianshan Coll Fuzhou Peoples R China

Magnetorheological dampers have become prominent semi-active control devices for vibration mitigation of structures which are subjected to severe loads. However, the damping force cannot be controlled directly due to the inherent nonlinear characteristics of the magnetorheological dampers. Therefore, for fully exploiting the capabilities of the magnetorheological dampers, one of the challenging aspects is to develop an accurate inverse model which can appropriately predict the input voltage to control the damping force. In this article, a hybrid modeling strategy combining shuffled frogleaping algorithm and adaptive-network-based fuzzy inference system is proposed to model the inverse dynamic characteristics of the magnetorheological dampers for improving the modeling accuracy. The shuffled frog-leaping algorithm is employed to optimize the premise parameters of the adaptive-network-based fuzzy inference system while the consequent parameters are tuned by a least square estimation method, here known as shuffled frog-leaping algorithm-based adaptive-network-based fuzzy inference system approach. To evaluate the effectiveness of the proposed approach, the inverse modeling results based on the shuffled frog-leaping algorithm-based adaptive-network-based fuzzy inference system approach are compared with those based on the adaptive-network-based fuzzy inference system and genetic algorithm-based adaptive-network-based fuzzy inference system approaches. Analysis of variance test is carried out to statistically compare the performance of the proposed methods and the results demonstrate that the shuffled frogleaping algorithm-based adaptive-network-based fuzzy inference system strategy outperforms the other two methods in terms of modeling (training) accuracy and checking accuracy.

关键词： Magnetorheological damper inverse model adaptive-network-based fuzzy inference system shuffled frog-leaping algorithm genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

An Integration of Neural Network and shuffled frog-leaping algorithm for CNC Machining Monitoring

引用

FOUNDATIONS OF COMPUTING AND DECISION SCIENCES 2021年第1期46卷 27-42页

作者： Goli, Alireza Tirkolaee, Erfan Babaee Weber, Gerhard-Wilhelm Univ Isfahan Dept Ind Engn Esfahan Iran Istinye Univ Dept Ind Engn Istanbul Turkey Poznan Univ Tech Fac Engn Management Poznan Poland Middle East Tech Univ Inst Appl Math Ankara Turkey

This paper addresses Acoustic Emission (AE) from Computer Numerical Control (CNC) machining operations. Experimental measurements are performed on the CNC lathe sensors to provide the power consumption data. To this end, a hybrid methodology based on the integration of an Artificial Neural Network (ANN) and a shuffled frog-leaping algorithm (SFLA) is applied to the data resulting from these measurements for data fusion from the sensors which is called SFLA-ANN. The initial weights of ANN are selected using SFLA. The goal is to assess the potency of the signal periodic component among these sensors. The efficiency of the proposed SFLA-ANN method is analyzed compared to hybrid methodologies of Simulated Annealing (SA) algorithm and ANN (SA-ANN) and Genetic algorithm (GA) and ANN (GA-ANN).

关键词： Artificial Neural Network shuffled frog-leaping algorithm Simulated Annealing Genetic algorithm CNC machining Multi-sensor data fusion

来源：评论

学校读者我要写书评

暂无评论

A shuffled frog-leaping algorithm with three memeplexes for hybrid flowshop scheduling problem with two batch processing machines stages

A shuffled frog-leaping algorithm with three memeplexes for ...

引用

第43届中国控制会议

作者： Deming Lei Shihan Wen School of Automation Wuhan University of Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Hybrid flowshop scheduling problem(HFSP) with batch processing machines(BPM) has attracted some attention by using various meta-heuristics. In this study, HFSP with two BPM stages is solved and a shuffled frog-leaping algorithm with three memeplexes(TMSFLA) is presented to minimize makespan and totardiness. In TMSFLA, the number of memeplexes is not used as parameter and fixed to be 3. A new way is given to divide population into three memeplexes. Lexicographical method is adopted in memeplex 2 for makespan and memeplex 3 for total tardiness. The differentiated search strategies are used in three memeplexes and reinforcement search is added. Extensive experiments are conducted. The effectiveness of new strategies and the search advantages are tested for TMSFLA in solving HFSP with two BPM stages.

关键词： Hybrid flowshop scheduling problem shuffled frog-leaping algorithm batch processing machines

来源：评论

学校读者我要写书评

暂无评论

The construction of a support vector machine using the shuffled frog-leaping algorithm

The construction of a support vector machine using the shuff...

引用

2014 International Conference on Computer Science and Systems Engineering（CSSE2014）

作者： M.H.Horng C.F.Chao H.Z.Chai Department of Computer Science and Information Engineering “National PingTung University”

ISBN: (纸本)9781784660543

The parameter setting of a support vector machine is a very important factor to its accuracy and efficiency. In this paper, we employ the shuffled frog-leaping algorithm(SFLA) to simultaneously train all parameters of the support vector machine including the penalty parameter, smoothness parameter and Lagrangian multiplier. The proposed method is called the SFLA-based support vector machine(SFLA-SVM). In experiments, binary and multi-class classifications are explored. In experiments, 10 of the benchmark data sets of UCI Machine Learning Repository are used. The classification performance of SFLA-SVM is compared to the original LIBSVM method associated with the grid search method and the PSO-SVM. The experimental results advocate that the use of SFLA-SVM for classifying the pattern classifications has better classification accuracy.

关键词： support vector machine shuffled frog-leaping algorithm UCI machine learning repository particle swarm optimization

来源：评论

学校读者我要写书评

暂无评论

UAV Path Planning Based on shuffled frog-leaping algorithm and Dubins Path

UAV Path Planning Based on Shuffled Frog-Leaping Algorithm a...

引用

第三十九届中国控制会议

作者： Xinfang Li Yangwang Fang Wenxing Fu Northwestern Polytechnical University

In this paper, a novel path planning algorithm for the fixed-wing UAV based on shuffled frog-leaping algorithm（SFLA） and Dubins path is proposed. First, the Dubins path planning is transformed into a discrete combinatorial optimization problem. Then the SFLA is used to search the optimal Dubins path, so that the generated flight path directly satisfies the minimum turning radius constraint of UAV. In order to perfectly combine the SFLA and the Dubins path, a novel coding method and the worst frog update strategy are presented. Finally, the simulation results prove that the algorithm is effective for path planning of single UAV and multiple UAVs.

关键词： path planning Dubins path shuffled frog-leaping algorithm obstacle avoidance

来源：评论

学校读者我要写书评

暂无评论

Identification of noise in multi noise plant using enhanced version of shuffled frog leaping algorithm

引用

INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2018年第1期9卷 43-51页

作者： Sharma, Tarun Kumar Pant, Millie Amity Univ Rajasthan Jaipur Rajasthan India IIT Roorkee Dept Appl Sci & Engn Roorkee Uttar Pradesh India

In any factory or industry the high level noise can be very harmful to the employees. As investigated by Occupational Safety and Health Act of 1970, the high level noise not only causes physiological ailments in employees but also causes harmful environment in the neighborhood. Therefore it becomes essential to control the noise levels in any manufacturing plant or industry. This can be achieved by optimal allocation of noise equipment which is quite not easy to recognize the exact location. In this study a shuffled frog-leaping algorithm (SFLA) with modification is applied to identify optimal locations for equipment in order to reduce noise level in multi noise plant. Comparatively, SFLA is a recent addition to the family of nontraditional population based search methods that mimics the social and natural behavior of species (frogs). SFLA merges the advantages of particle swarm optimization and genetic algorithm (GA). Though SFLA has been successfully applied to solve many benchmark and real time problems but it limits in convergence speed. In order to improve its performance, the frog with best position in each memeplexes is allowed to slightly modify its position using random walk. This process improves the local search around the best position. The proposal is named as improved local search in SFLA. The simulated results defend the efficacy of the proposal when compared with the differential evolution, GA and SFL algorithms.

关键词： shuffled frog-leaping algorithm SFLA Global optimization Noise identification

来源：评论

学校读者我要写书评

暂无评论

Elitism based shuffled frog leaping algorithm 5

Elitism based Shuffled Frog Leaping Algorithm

引用

International Conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： Sharma, Pragya Sharma, Nirmala Sharma, Harish Rajasthan Tech Univ Kota India

ISBN: (纸本)9781509020287

shuffled frog-leaping algorithm (SFLA) is a memetic meta-heuristic approach for solving complex optimization problems. Like other evolutionary algorithms, it may also suffer from the problem of slow convergence. To elevate the convergence and to improve the intensification and diversification capabilities of SFLA, elitism is embedded by calculating the mean of local best and second local best solutions while updating the position of worst solution in local best updating phase. Similarly, mean of global best and second global best solutions is used to improve the position of worst solution while updating the position of worst solution in global best updating phase. The proposed algorithm is named as Elitism based shuffled frog-leaping algorithm (ESFLA). The modified algorithm ESFLA is analysed over 15 distinct benchmark test problems and compared with conventional SFLA, its recent variant, namely Binomial Crossover Embedded shuffled frog-leaping algorithm (BC-SFLA) and two other nature inspired algorithms, namely Gravitational Search algorithm (GSA) and Biogeography-Based Optimization algorithm (BBO). The results manifest that ESFLA is an antagonist variant of SFLA.

关键词： Meta-heuristic Optimization Techniques shuffled frog-leaping algorithm Swarm Intelligence Elitism

来源：评论

学校读者我要写书评

暂无评论

Binomial Crossover Embedded shuffled frog leaping algorithm

Binomial Crossover Embedded Shuffled Frog Leaping Algorithm

引用

IEEE International Conference on Computing, Communication and Automation (ICCCA)

作者： Sharma, Pragya Sharma, Nirmala Sharma, Harish Rajasthan Tech Univ Kota India

ISBN: (纸本)9781509016662

shuffled frog-leaping algorithm (SFLA) is a memetic meta-heuristic used for solving various combinatorial optimization problems. SFLA divides population into several memeplexes and then apply evolutionary process to update every memeplex. Like other evolutionary algorithm, it may also suffer from the problem of slow convergence. To improve the convergence and exploitation capability of SFLA, Binomial crossover is embedded. The proposed algorithm is named as, Binomial Crossover Embedded shuffled frog leaping algorithm (BC-SFLA). In the proposed BC-SFLA, the perturbation rate of the solutions are controlled by the binomial crossover. The proposed algorithm is tested over 15 benchmark test functions and compared with basic SFLA and two other nature inspired algorithms namely gravitational search algorithm (GSA) and differential evolution algorithm (DE). The results state that BCSFLA is a competitive variant of SFLA.

关键词： Meta-heuristic Optimization Techniques shuffled frog-leaping algorithm Swarm Intelligence Binomial Crossover

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：