检索结果-南通市图书馆

Chinese Journal of Mechanical Engineering 2022年第6期35卷 165-177页

作者： Hongfei Guo Linsheng Zhang Yaping Ren Leilei Meng Zhongwei Zhou Jianqing Li GBA and B&R International Joint Research Center for Smart Logistics School of Intelligent Systems Science and EngineeringInstitute of Physical InternetJinan University(Zhuhai Campus)Zhuhai 519070China School of Computer Science Liaocheng UniversityLiaocheng 252059China Faculty of Information Technology Macao University of Science and TechnologyMacao 999078China

The recycling and remanufacturing of end-of-life products are significant for environmental protection and resource conservation.Disassembly is an essential process of remanufacturing end-of-life products.Effective disassembly plans help improve disassembly efficiency and reduce disassembly costs.This paper studies a disassembly planning problem with operation attributes,in which an integrated decision of the disassembly sequence,disassembly directions,and disassembly tools are made.Besides,a mathematical model is formulated with the objective of minimizing the penalty cost caused by the changing of operation attributes.Then,a neighborhood modularization-based Artificial bee colony algorithm is developed,which contains a modular optimized design.Finally,two case studies with different scales and complexities are used to verify the performance of the proposed approach,and experimental results show that the proposed algorithm outperforms the two existing methods within an acceptable computational time.

关键词： End-of-life products Disassembly planning Artificial bee colony Neighborhood modularization

Selective Harmonics Elimination Technique for Artificial bee colony Implementation

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2023年第6期45卷 2721-2740页

作者： T.DeepikaVinothini R.Karthigaivel J.BarsanaBanu Department of Electrical and Electronics Engineering Velammal College of Engineering and TechnologyMaduraiIndia Department of Electrical and Electronics Engineering PSNA College of Engineering and TechnologyDindigulIndia Department of Electrical and Electronics Engineering SBM College of Engineering and TechnologyDindigulIndia

In this research,an Artificial bee colony(ABC)algorithm based Selective Harmonics Elimination(SHE)technique is used as a pulse generator in a reduced switch fifteen level inverter that receives input from a PV system.Pulse width modulation based on Selective Harmonics Elimination is mostly used to suppress lower-order harmonics.A high gain DC-DC-SEPIC converter keeps the photovoltaic(PV)panel’s output voltage constant.The Grey Wolf Optimization(GWO)filter removes far more Photovoltaic panel energy from the sunlight frame.To eliminate voltage harmonics,this unique inverter architecture employs a multi-carrier duty cycle,a high-frequency modulation approach.The proposed ABC harmonics elimination approach is compared to SHE strategies based on Particle Swarm Optimization(PSO)and Flower Pollination Algorithm(FPA).The suggested system’s performance is simulated and measured using the MATLAB simulation tool.The proposed ABC approach has a THD level of 4.86%,which is better than the PSO and FPA methods.

关键词： Artificial bee colony photovoltaic flower pollination algorithm multi-carrier

An Effective Discrete Artificial bee colony Based SPARQL Query Path Optimization by Reordering Triples

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Computer Science & Technology 2021年第2期36卷 445-462页

作者： Zeynep Banu Ozger Nurgul Yuzbasioglu Uslu Department of Computer Engineering Sutcu Imam UniversityKahramanmaras 46040Turkey Department of Computer Engineering Yildiz Technical UniversityIstanbul 34220Turkey

Semantic Web has emerged to make web content machine-readable,and with the rapid increase in the number of web pages,its importance has increased.Resource description framework(RDF)is a special data graph format where Semantic Web data are stored and it can be queried by SPARQL query language.The challenge is to find the optimal query order that results in the shortest period of time.In this paper,the discrete Artificial bee colony(dABCSPARQL)algorithm is proposed,based on a novel heuristic approach,namely reordering SPARQL queries.The processing time of queries with different shapes and sizes is minimized using the dABCSPARQL algorithm.The performance of the proposed method is evaluated on chain,star,cyclic,and chain-star queries of different sizes from the Lehigh University Benchmark(LUBM)dataset.The results obtained by the proposed method are compared with those of ARQ(a SPARQL processor for Jena)query engine,the Ant System,the Elitist Ant System,and MAX-MIN Ant System algorithms.The experiments demonstrate that the proposed method significantly reduces the processing time,and in most queries,the reduction rate is higher compared with other optimization methods.

关键词： Artificial bee colony resource description framework(RDF) query optimization reordering triple pattern SPARQL

Automatic Data Clustering Based Mean Best Artificial bee colony Algorithm

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2021年第8期68卷 1575-1593页

作者： Ayat Alrosan Waleed Alomoush Mohammed Alswaitti Khalid Alissa Shahnorbanun Sahran Sharif Naser Makhadmeh Kamal Alieyan Deanship of Information and Communication Technology Imam Abdulrahman bin Faisal UniversityDammamSaudi Arabia Computer Department Imam Abdulrahman bin Faisal UniversityDammamSaudi Arabia School of Electrical and Computer Engineering Department of Information and Communication TechnologyXiamen University MalaysiaSepang43900Malaysia Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman bin Faisal UniversityDammamSaudi Arabia Center for artificial Intelligence Technology(CAIT) Faculty of Information Science and TechnologyUniversiti Kebangsaan Malaysia43600 BangiMalaysia School of Computer Sciences Universiti Sains Malaysia11800PenangMalaysia Faculty of Computer Sciences and Informatics Amman Arab UniversityAmmanJordan

Fuzzy C-means(FCM)is a clustering method that falls under unsupervised machine learning.The main issues plaguing this clustering algorithm are the number of the unknown clusters within a particular dataset and initialization sensitivity of cluster centres.Artificial bee colony(ABC)is a type of swarm algorithm that strives to improve the members’solution quality as an iterative process with the utilization of particular kinds of randomness.However,ABC has some weaknesses,such as balancing exploration and exploitation.To improve the exploration process within the ABC algorithm,the mean Artificial bee colony(MeanABC)by its modified search equation that depends on solutions of mean previous and global best is used.Furthermore,to solve the main issues of FCM,Automatic clustering algorithm was proposed based on the mean Artificial bee colony called(AC-MeanABC).It uses the MeanABC capability of balancing between exploration and exploitation and its capacity to explore the positive and negative directions in search space to find the best value of clusters number and centroids value.A few benchmark datasets and a set of natural images were used to evaluate the effectiveness of AC-MeanABC.The experimental findings are encouraging and indicate considerable improvements compared to other state-of-the-art approaches in the same domain.

关键词： Artificial bee colony automatic clustering natural images validity index number of clusters

A Novel Hybrid Data Clustering Algorithm Based on Artificial bee colony Algorithm and K-Means

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Chinese Journal of Electronics 2015年第4期24卷 694-701页

作者： TRAN Dang Cong WU Zhijian WANG Zelin DENG Changshou State Key Laboratory of Software Engineering School of Computer Wuhan University Vietnam Academy of Science and Technology School of Information Science and Technology Jiujiang University

To improve the performance of K-means clustering algorithm, this paper presents a new hybrid approach of Enhanced Artificial bee colony algorithm and Kmeans(EABCK). In EABCK, the original Artificial bee colony algorithm(called ABC) is enhanced by a new mutation operation and guided by the global best solution(called EABC). Then, the best solution is updated by Kmeans in each iteration for data clustering. In the experiments, a set of benchmark functions was used to evaluate the performance of EABC with other comparative ABC variants. To evaluate the performance of EABCK on data clustering, eleven benchmark datasets were utilized. The experimental results show that EABC and EABCK outperform other comparative ABC variants and data clustering algorithms, respectively.

关键词： Data clustering K-means Artificial bee colony Mutation operation

Hybridizing Artificial bee colony with Bat Algorithm for Web Service Composition

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2023年第8期46卷 2429-2445页

作者： Tariq Ahamed Ahanger Fadl Dahan Usman Tariq Department of Management Information Systems College of Business AdministrationPrince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Management Information Systems College of Business Administration-Hawtat Bani TamimPrince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Computer Sciences Faculty of Computing and Information Technology Al-TurbahTaiz UniversityTaiz9674Yemen

In the Internet of Things(IoT),the users have complex needs,and the Web Service Composition(WSC)was introduced to address these needs.The WSC’s main objective is to search for the optimal combination of web services in response to the user needs and the level of Quality of Services(QoS)constraints.The challenge of this problem is the huge number of web services that achieve similar functionality with different levels of QoS constraints.In this paper,we introduce an extension of our previous works on the Artificial bee colony(ABC)and Bat Algorithm(BA).A new hybrid algorithm was proposed between the ABC and BA to achieve a better tradeoff between local exploitation and global search.The bat agent is used to improve the solution of exhausted bees after a threshold(limits),and also an Elitist Strategy(ES)is added to BA to increase the convergence rate.The performance and convergence behavior of the proposed hybrid algorithm was tested using extensive comparative experiments with current state-ofthe-art nature-inspired algorithms on 12 benchmark datasets using three evaluation criteria(average fitness values,best fitness values,and execution time)that were measured for 30 different runs.These datasets are created from real-world datasets and artificially to form different scale sizes of WSC datasets.The results show that the proposed algorithm enhances the search performance and convergence rate on finding the near-optimal web services combination compared to competitors.TheWilcoxon signed-rank significant test is usedwhere the proposed algorithm results significantly differ fromother algorithms on 100%of datasets.

关键词： Internet of things Artificial bee colony bat algorithm elitist strategy web service composition

Improved binary Artificial bee colony algorithm

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Frontiers of Information Technology & Electronic Engineering 2021年第8期22卷 1080-1091页

作者： Rafet DURGUT Computer Engineering Department Engineering FacultyKarabuk UniversityKarabuk 78050Turkey

The Artificial bee colony(ABC)algorithm is an evolutionary optimization algorithm based on swarm intelligence and inspired by the honey bees’food search behavior.Since the ABC algorithm has been developed to achieve optimal solutions by searching in the continuous search space,modification is required to apply it to binary optimization problems.In this study,we modify the ABC algorithm to solve binary optimization problems and name it the improved binary ABC(IbinABC).The proposed method consists of an update mechanism based on fitness values and the selection of different decision variables.Therefore,we aim to prevent the ABC algorithm from getting stuck in a local minimum by increasing its exploration ability.We compare the IbinABC algorithm with three variants of the ABC and other meta-heuristic algorithms in the literature.For comparison,we use the well-known OR-Library dataset containing 15 problem instances prepared for the uncapacitated facility location problem.Computational results show that the proposed algorithm is superior to the others in terms of convergence speed and robustness.The source code of the algorithm is available at https://***/rafetdurgut/ibinABC.

关键词： Artificial bee colony Binary optimization Uncapacitated facility location problem(UFLP)

An improved discrete Artificial bee colony algorithm for the distributed permutation flowshop scheduling problem with preventive maintenance

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

An improved discrete artificial bee colony algorithm for the...

An Improved Artificial bee colony Algorithm with History Best Points

第三十九届中国控制会议

作者： Jiayang Mao XiaoLu Hu Quan-ke Pa Zhonghua Miao Chuangxin He M Fatih Tasgetiren School of Mechanical and Electrical Engineering and Automation Shanghai University China Rural Technology Development Center International logistics management department Yasar University

The distributed permutation flowshop scheduling problem with preventive maintenance operator（PM/DPFSP） is closely related to modern industry.This paper presents an improved discrete Artificial bee colony（IDABC） algorithm for solving this problem.The criterion to be optimized is the makespan.An improved NEH heuristic method is proposed to initialize the population effectively.We adapted a local search method with insertion and swap operator to produce neighboring solutions in employ bee phase and onlooker bee phase.A global search method with destruction and reconstruction phase is introduced to avoid local optima in scout bee phase.The parameters for the proposed IDABC are calibrated by means of a design of experiments and analysis of variance.We conduct extensive experiments to test the performance of IDABC.Computational results indicate that IDABC has promising advantages on PM/DPFSP.

关键词： Distributed scheduling Flowshop Preventive maintenance Artificial bee colony

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

An Improved Artificial Bee Colony Algorithm with History Bes...

A Discrete Artificial bee colony for Distributed Permutation Flowshop Scheduling Problem with Total Flow Time Minimization

第30届中国控制与决策会议

作者： Xingyu Xia Xi Wang Haidong Hu Dongmei Wu Hao Gao The Institute of Advanced Technology Nanjing University of Posts and Telecommunications College of Automation Nanjing University of Posts and Telecommunications Beijing Institute of Control Engineering

Depending on the power global search ability, Artificial bee colony algorithm attracts more attentions in recent years. But its slow convergence rate constraints its development. To better balance its exploration and exploitation abilities, we define a new point named as mean history best points（MHB） to lead the direction of bee population. The numerical experiments on the basic benchmark functions validate the efficiency of our algorithm.

关键词： Artificial bee colony convergence rate evolutionary computation global search ability

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

A Discrete Artificial Bee Colony for Distributed Permutation...