Relevant bibliographies by topics / Cooperative artificial bee colony

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  2. Dissertations / Theses
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Academic literature on the topic 'Cooperative artificial bee colony'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Cooperative artificial bee colony"

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Zou, Wenping, Yunlong Zhu, Hanning Chen, and Xin Sui. "A Clustering Approach Using Cooperative Artificial Bee Colony Algorithm." Discrete Dynamics in Nature and Society 2010 (2010): 1–16. http://dx.doi.org/10.1155/2010/459796.

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Artificial Bee Colony (ABC) is one of the most recently introduced algorithms based on the intelligent foraging behavior of a honey bee swarm. This paper presents an extended ABC algorithm, namely, the Cooperative Article Bee Colony (CABC), which significantly improves the original ABC in solving complex optimization problems. Clustering is a popular data analysis and data mining technique; therefore, the CABC could be used for solving clustering problems. In this work, first the CABC algorithm is used for optimizing six widely used benchmark functions and the comparative results produced by A
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Li, Jun-yi, Yi-ding Zhao, Jian-hua Li, and Xiao-jun Liu. "Artificial Bee Colony Optimizer with Bee-to-Bee Communication and Multipopulation Coevolution for Multilevel Threshold Image Segmentation." Mathematical Problems in Engineering 2015 (2015): 1–23. http://dx.doi.org/10.1155/2015/272947.

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This paper proposes a modified artificial bee colony optimizer (MABC) by combining bee-to-bee communication pattern and multipopulation cooperative mechanism. In the bee-to-bee communication model, with the enhanced information exchange strategy, individuals can share more information from the elites through the Von Neumann topology. With the multipopulation cooperative mechanism, the hierarchical colony with different topologies can be structured, which can maintain diversity of the whole community. The experimental results on comparing the MABC to several successful EA and SI algorithms on a
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Liang, Jun-Hao, and Ching-Hung Lee. "A Modification Artificial Bee Colony Algorithm for Optimization Problems." Mathematical Problems in Engineering 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/581391.

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This paper presents a modified artificial bee colony algorithm (MABC) for solving function optimization problems and control of mobile robot system. Several strategies are adopted to enhance the performance and reduce the computational effort of traditional artificial bee colony algorithm, such as elite, solution sharing, instant update, cooperative strategy, and population manager. The elite individuals are selected as onlooker bees for preserving good evolution, and, then, onlooker bees, employed bees, and scout bees are operated. The solution sharing strategy provides a proper direction for
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Lin, Chun-Hui, Shyh-Hau Wang, and Cheng-Jian Lin. "Interval Type-2 Neural Fuzzy Controller-Based Navigation of Cooperative Load-Carrying Mobile Robots in Unknown Environments." Sensors 18, no. 12 (2018): 4181. http://dx.doi.org/10.3390/s18124181.

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In this paper, a navigation method is proposed for cooperative load-carrying mobile robots. The behavior mode manager is used efficaciously in the navigation control method to switch between two behavior modes, wall-following mode (WFM) and goal-oriented mode (GOM), according to various environmental conditions. Additionally, an interval type-2 neural fuzzy controller based on dynamic group artificial bee colony (DGABC) is proposed in this paper. Reinforcement learning was used to develop the WFM adaptively. First, a single robot is trained to learn the WFM. Then, this control method is implem
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Ye, Fang, Fei Che, and Lipeng Gao. "Multiobjective Cognitive Cooperative Jamming Decision-Making Method Based on Tabu Search-Artificial Bee Colony Algorithm." International Journal of Aerospace Engineering 2018 (December 9, 2018): 1–10. http://dx.doi.org/10.1155/2018/7490895.

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For the future information confrontation, a single jamming mode is not effective due to the complex electromagnetic environment. Selecting the appropriate jamming decision to coordinately allocate the jamming resources is the development direction of the electronic countermeasures. Most of the existing studies about jamming decision only pay attention to the jamming benefits, while ignoring the jamming cost. In addition, the conventional artificial bee colony algorithm takes too many iterations, and the improved ant colony (IAC) algorithm is easy to fall into the local optimal solution. Agains
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Harfouchi, Fatima, and Hacene Habbi. "A cooperative learning artificial bee colony algorithm with multiple search mechanisms." International Journal of Hybrid Intelligent Systems 13, no. 2 (2016): 113–24. http://dx.doi.org/10.3233/his-160229.

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Liang, Xiaodan, Lin Na, Liangyu Li, and Hanning Chen. "A Cooperative Coevolutionary Artificial Bee Colony Algorithm for Multi-Objective Optimization." Journal of Computational and Theoretical Nanoscience 13, no. 9 (2016): 6258–66. http://dx.doi.org/10.1166/jctn.2016.5555.

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Ma, Lianbo, Kunyuan Hu, Yunlong Zhu, and Hanning Chen. "Cooperative artificial bee colony algorithm for multi-objective RFID network planning." Journal of Network and Computer Applications 42 (June 2014): 143–62. http://dx.doi.org/10.1016/j.jnca.2014.02.012.

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Zhou, Xiaoming, Anlong Su, Aimin Liu, Wanli Cui, and Wei Liu. "Cooperative approach to artificial bee colony algorithm for optimal power flow." Cluster Computing 22, S4 (2018): 8059–67. http://dx.doi.org/10.1007/s10586-017-1594-9.

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Hei, Yongqiang, Wentao Li, Weihong Fu, and Xiaohui Li. "Efficient Parallel Artificial Bee Colony Algorithm for Cooperative Spectrum Sensing Optimization." Circuits, Systems, and Signal Processing 34, no. 11 (2015): 3611–29. http://dx.doi.org/10.1007/s00034-015-0028-2.

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Dissertations / Theses on the topic "Cooperative artificial bee colony"

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Lee, Jessica. "Vägplanering i dataspel med hjälp av Artificial Bee Colony Algorithm." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-11044.

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Artificial Bee Colony Algorithm är en algoritm som tidigare tillämpats på många numeriska optimeringsproblem. Algoritmen är dock inte vanligt förekommande vad gäller vägplanering i dataspel. Detta arbete undersöker ifall algoritmen presterar bättre än A* på fyra olika testmiljöer eftersom A* är en av de mest använda algoritmerna för vägplanering i dataspel och således en bra referens. De aspekter som jämförs vid mätningarna är algoritmernas tidsåtgång samt längden på de resulterande vägarna. En riktad slumpgenerering av vägar har implementerats till algoritmen som gör att den inte fungerar på
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Hashim, Mohd Ruzaini. "Improved spiral dynamics and artificial bee colony algorithms with application to engineering problems." Thesis, University of Sheffield, 2018. http://etheses.whiterose.ac.uk/20175/.

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Marrè, Badalló Roser. "Implementation and Testing of Two Bee-Based Algorithms in Finite Element Model Updating." Thesis, KTH, Bro- och stålbyggnad, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-140846.

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Finite Element Model Updating has recently arisen as an issue of vast importance on the design, construction and maintenance of structures in civil engineering. Many algorithms have been proposed, developed and enhanced in order to accomplish the demands of the updating process, mainly to achieve computationally efficient programs and greater results.The present Master Thesis proposes two new algorithms to be used in Finite Element Model Updating: the Bees Algorithms (BA) and the Artificial Bee Colony algorithm (ABC). Both were first proposed in 2005, are based on the foraging behaviour of bee
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Idachaba, Unekwu Solomon. "A bio-inspired cache management policy for cloud computing environments using the artificial bee colony algorithm." Thesis, University of Kent, 2015. https://kar.kent.ac.uk/57856/.

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Caching has become an important technology in the development of cloud computing-based high-performance web services. Caches reduce the request-response latency experienced by users and reduce workload on backend databases. Caches need a high cache-hit rate to be fit for purpose, and this is dependent on the cache management policy used. Existing cache management policies do not prevent cache pollution and cache monopoly. This lack of prevention impacts negatively on cache hit rates. This work presents a Bio-inspired Community-based Caching (BCC) approach to address these two problems, by draw
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Santos, Daniela Scherer dos. "Bee clustering : um algoritmo para agrupamento de dados inspirado em inteligência de enxames." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2009. http://hdl.handle.net/10183/18249.

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Agrupamento de dados é o processo que consiste em dividir um conjunto de dados em grupos de forma que dados semelhantes entre si permaneçam no mesmo grupo enquanto que dados dissimilares sejam alocados em grupos diferentes. Técnicas tradicionais de agrupamento de dados têm sido usualmente desenvolvidas de maneira centralizada dependendo assim de estruturas que devem ser acessadas e modificadas a cada passo do processo de agrupamento. Além disso, os resultados gerados por tais métodos são dependentes de informações que devem ser fornecidas a priori como por exemplo número de grupos, tamanho do
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Tatjana, Jakšić Krüger. "Development, implementation and theoretical analysis of the bee colony optimization meta-heuristic method." Phd thesis, Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, 2017. https://www.cris.uns.ac.rs/record.jsf?recordId=104550&source=NDLTD&language=en.

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The Ph.D. thesis addresses a comprehensive study of the bee colonyoptimization meta-heuristic method (BCO). Theoretical analysis of themethod is conducted with the tools of probability theory. Necessary andsufficient conditions are presented that establish convergence of the BCOmethod towards an optimal solution. Three parallelization strategies and fivecorresponding implementations are proposed for BCO for distributed-memorysystems. The influence of method’s parameters on the performance of theBCO algorithm for two combinatorial optimization problems is analyzedthrough the experimental
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Melo, Everton Luiz de. "Meta-heurísticas Iterated Local Search, GRASP e Artificial Bee Colony aplicadas ao Job Shop Flexível para minimização do atraso total." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/3/3136/tde-15122014-002717/.

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O ambiente de produção abordado neste trabalho é o Job Shop Flexível (JSF), uma generalização do Job Shop (JS). O problema de programação de tarefas, ou jobs, no ambiente JS é classificado por Garey; Johnson e Sethi (1976) como NP-Difícil e o JSF é, no mínimo, tão difícil quanto o JS. O JSF é composto por um conjunto de jobs, cada qual constituído por operações. Cada operação deve ser processada individualmente, sem interrupção, em uma única máquina de um subconjunto de máquinas habilitadas. O principal critério de desempenho considerado é a minimização dos atrasos dos jobs. São apresentados m
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Basaran, Dilek. "Design, Production And Development Of Mini/micro Robots To Form A Cooperative Colony." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1058874/index.pdf.

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Design, production and development of individual mini/micro robots and then formation of their cooperative colony are the main topics of this thesis. The produced mini/micro robots are as small and light as possible. In addition, they are multifunctional (programmable), flexible and intelligent while maintaining a very low production cost. Mini/micro robots, called MinT-DB series are able to communicate with each other to work cooperatively. Moreover, these robots can be the basis for the future studies considering the application of artificial intelligence and modeling of live colonies in the
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Kavaliauskas, Donatas. "Dirbtinės bičių kolonijos algoritmai ir jų taikymai maršrutų optimizavimo uždaviniams spręsti." Bachelor's thesis, Lithuanian Academic Libraries Network (LABT), 2013. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2013~D_20130729_153102-94516.

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Šiame darbe yra trumpai apžvelgiami dalelių spiečių sistemų algoritmai, maršrutų optimizavimo uždaviniai ir jų formuluotės, bei praktinės interpretacijos. Plačiau apžvelgiami dirbtinių bičių kolonijų algoritmai ir jų pritaikymas keliaujančio pirklio uždaviniams spręsti. Taip pat šiame darbe galima rasti dirbtinių bičių kolonijų algoritmo pritaikymą keliaujančio pirklio uždaviniams spręsti, bei sukurtos programos skaičiavimo rezultatų analizę.<br>This paper consists of short description of swarm systems algorithms, route optimisation problems overview and longer description of artificial bee co
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SOUZA, Viviane Lucy Santos de. "Uma metodologia para síntese de circuitos digitais em FPGAs baseada em otimização multiobjetivo." Universidade Federal de Pernambuco, 2015. https://repositorio.ufpe.br/handle/123456789/17339.

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Submitted by Irene Nascimento (irene.kessia@ufpe.br) on 2016-07-12T18:32:53Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Tese_Final_bib.pdf: 4325542 bytes, checksum: 5cafa644d256b743ce0f06490e4d5920 (MD5)<br>Made available in DSpace on 2016-07-12T18:32:53Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Tese_Final_bib.pdf: 4325542 bytes, checksum: 5cafa644d256b743ce0f06490e4d5920 (MD5) Previous issue date: 2015-08-20<br>Atualmente, a evolução na arquitetura dos FPGAs (Field programa
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Books on the topic "Cooperative artificial bee colony"

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Wade, Dani. Variants of Artificial Bee Colony Algorithm and Its Applications in Medical Image Processing: Artificial Bee Colony,Optimization,Medical Imaging,artificial Intelligence in Medical Imaging. Independently Published, 2021.

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Book chapters on the topic "Cooperative artificial bee colony"

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Bullinaria, John A., and Khulood AlYahya. "Artificial Bee Colony Training of Neural Networks." In Nature Inspired Cooperative Strategies for Optimization (NICSO 2013). Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-01692-4_15.

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Aderhold, Andrej, Konrad Diwold, Alexander Scheidler, and Martin Middendorf. "Artificial Bee Colony Optimization: A New Selection Scheme and Its Performance." In Nature Inspired Cooperative Strategies for Optimization (NICSO 2010). Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12538-6_24.

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Guo, Chen, Heng Tang, Chang Boon Patrick Lee, and Ben Niu. "Data Clustering Using the Cooperative Search Based Artificial Bee Colony Algorithm." In Intelligent Computing Methodologies. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-26766-7_60.

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Rajasekhar, Anguluri, and Swagatam Das. "Cooperative Micro Artificial Bee Colony Algorithm for Large Scale Global Optimization Problems." In Swarm, Evolutionary, and Memetic Computing. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-03753-0_42.

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Liu, JunXia, ZhenHong Jia, XiZhong Qin, Chun Chang, GuoJun Xu, and XiaoYan Xia. "The Applications in Channel Assignment Based on Cooperative Hybrid Artificial Bee Colony Algorithm." In Advances in Intelligent and Soft Computing. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27951-5_60.

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Liu, Bin, Wei-min Li, and Shuai Pan. "A Novel Adaptive Cooperative Artificial Bee Colony Algorithm for Solving Numerical Function Optimization." In Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2663-8_3.

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Bansal, Jagdish Chand, Harish Sharma, and K. V. Arya. "Model Order Reduction of Single Input Single Output Systems Using Artificial Bee Colony Optimization Algorithm." In Nature Inspired Cooperative Strategies for Optimization (NICSO 2011). Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24094-2_6.

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Lin, Jianfeng, Ruiquan Lin, Jun Wang, and Min Zhang. "Optimal Cooperation Scheme Based on Improved Artificial Bee Colony for Energy Harvesting Cognitive Network." In Lecture Notes in Electrical Engineering. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-6324-6_39.

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Badar, Altaf Q. H. "Artificial Bee Colony." In Evolutionary Optimization Algorithms. CRC Press, 2021. http://dx.doi.org/10.1201/9781003206477-6.

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Kaveh, Ali, and Taha Bakhshpoori. "Artificial Bee Colony Algorithm." In Metaheuristics: Outlines, MATLAB Codes and Examples. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04067-3_3.

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Conference papers on the topic "Cooperative artificial bee colony"

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Wenping Zou, Yunlong Zhu, Hanning Chen, and Zhu Zhu. "Cooperative approaches to Artificial Bee Colony algorithm." In 2010 International Conference on Computer Application and System Modeling (ICCASM 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccasm.2010.5623088.

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El-Abd, Mohammed. "A cooperative approach to The Artificial Bee Colony algorithm." In 2010 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2010. http://dx.doi.org/10.1109/cec.2010.5586007.

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Liu, Ming, Tong Zhao, Bo Wang, Wenqiang Li, and Lei Luan. "Cooperative Interference Decision Based on Directed Mutation Search Artificial Bee Colony Algorithm." In 2021 IEEE 4th International Conference on Electronic Information and Communication Technology (ICEICT). IEEE, 2021. http://dx.doi.org/10.1109/iceict53123.2021.9531258.

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Ashrafinia, S., U. Pareek, M. Naeem, and D. C. Lee. "Binary Artificial Bee Colony for cooperative relay communication in cognitive radio systems." In ICC 2012 - 2012 IEEE International Conference on Communications. IEEE, 2012. http://dx.doi.org/10.1109/icc.2012.6364087.

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Lu, Gao, Qianqi Dai, and Jiechen Xia. "Cooperative Jamming Resource Allocation Based on Artificial Bee Colony Multi-objective Decomposition." In 2022 International Applied Computational Electromagnetics Society Symposium (ACES-China). IEEE, 2022. http://dx.doi.org/10.1109/aces-china56081.2022.10065231.

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Li, Min, Yongqiang Hei, and Zhuo Qiu. "Optimization of Non-convex Cooperative Spectrum Sensing with Modified Artificial Bee Colony Algorithm." In 2014 IEEE International Conference on Computer and Information Technology (CIT). IEEE, 2014. http://dx.doi.org/10.1109/cit.2014.116.

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Cao, Lu, and Qiwei Chen. "Cooperative path planning for multi-USV based on improved artificial bee colony algorithm." In Other Applications. SPIE, 2018. http://dx.doi.org/10.1117/12.2285623.

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Harfouchi, Fatima, and Hacene Habbi. "A cooperative learning strategy with multiple search mechanisms for improved artificial bee colony optimization." In 2015 15th International Conference on Intelligent Systems Design and Applications (ISDA). IEEE, 2015. http://dx.doi.org/10.1109/isda.2015.7489269.

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Xia, Jiechen, Jing Ma, Yibing Li, and Mingzhao Song. "Cooperative Jamming Resource Allocation Based on Integer-Encoded Directed Mutation Artificial Bee Colony Algorithm." In 2021 IEEE 4th International Conference on Electronic Information and Communication Technology (ICEICT). IEEE, 2021. http://dx.doi.org/10.1109/iceict53123.2021.9531174.

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Zhao, Li, Lianhe Yang, Shaoqiang Zhang, and Jinglian Liang. "A Cooperative Artificial Bee Colony Algorithm and its application to Fashion Color Forecast in Clothing." In the 2018 2nd International Conference. ACM Press, 2018. http://dx.doi.org/10.1145/3242840.3242854.

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Reports on the topic "Cooperative artificial bee colony"

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Kanagavel, Rameshkumar, and Indragandhi Vairavasundaram. FPGA Implementation and Investigation of Hybrid Artificial Bee Colony Algorithm-based Single Phase Shunt Active Filter. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, 2020. http://dx.doi.org/10.7546/crabs.2020.05.13.

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