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2022 | OriginalPaper | Buchkapitel

18. Hybrid Optimization Algorithm Based on QUATRE and ABC Algorithms

verfasst von : Xin Zhang, Linlin Tang, Shu-Chuan Chu, Shaowei Weng, Jeng-Shyang Pan

Erschienen in: Advances in Smart Vehicular Technology, Transportation, Communication and Applications

Verlag: Springer Singapore

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Abstract

Artificial bee colony optimization algorithm (ABC) is an optimization algorithm based on swarm intelligence which is obtained by observing the behavior of bees looking for nectar and sharing food information with bees in the hive. QUasi-Affine TRansformation Evolutionary (QUATRE) is an algorithm that uses quasi-affine transformation as an evolution method because ABC has the shortcoming of weak ability to develop new nectar sources, and QUATRE has weak search ability but strong development ability, so this paper combines these two algorithms to a certain extent and proposes an improved artificial bee colony optimization algorithm (QUA-ABC). QUA-ABC is inspired by the location update formula in QUATRE and proposes a new location update formula suitable for ABC. In this study, experiments were conducted using the internationally used CEC2013 data set. The optimization accuracy and convergence speed of QUA-ABC were compared with the original ABC. The results show that the QUA-ABC algorithm has stronger capabilities and better performance.

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Vorheriges Kapitel QUasi-Affine TRansformation Evolution Algorithm for Optimal Power Flow of Integrated Electrical Network Combining Thermal Power with Wind Power

Nächstes Kapitel Joint Adaptive Reception Algorithm with Ant Colony Optimization for Asynchronous Cooperation Transmission Systems

Bonabeau, E.: Swarm intelligence : from natural to artificial systems. Santa Fe Inst. Stud. Sci. Complexity (1999)

Guo, W.: Research and development of algorithm based on swarm intelligence. J. Henan Mech. Electr. Eng. Col. (2007)

Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, Perth, pp. 1942–1948 (1995)

Menzel, R., Fuchs, J., Kirbach, A., et al.: Navigation and communication in honey bees. In: Honeybee Neurobiology and Behavior. Springer Netherlands (2012)

Karaboga, D., Basturk. B.: A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. J. Global Optim. 39(3), 459–471 (2007)

Meng, Z., Pan, J.-S., Xu, H.: QUasi-Affine TRansformation evolutionary (QUATRE) algorithm: a cooperative swarm based algorithm for global optimization. Knowl. Based Syst. 109, 104–121 (2016)

Meng, Z., Pan, J.-S.: QUasi-Affine TRansformation evolution with external ARchive (QUATRE-EAR): an enhanced structure for differential evolution. Knowl.-Based Syst. 155, 35–53 (2018)CrossRef

Liu, N., Pan, J.-S., Xue, J.Y.: An orthogonal QUasi-Affine TRansformation evolution (O-QUATRE) algorithm for global optimization. IIH-MSP. Springer, vol 157, pp 57–66 (2019)

Meng, Z., Pan, J.-S.: QUasi-affine TRansformation Evolutionary (QUATRE) algorithm: a parameter-reduced differential evolution algorithm for optimization problems. CEC 2016, 4082–4089 (2016)

10.

Pan, J.-S., Meng, Z., Huarong, Xu., Li, X.: QUasi-affine TRansformation evolution (QUATRE) algorithm: a new simple and accurate structure for global optimization. IEA/AIE 2016, 657–667 (2016)

11.

Bao, L., Zeng, J.C.: Comparison and analysis of the selection mechanism in the artificial bee colony algorithm. In: ninth international conference on hybrid intelligent systems. IEEE Computer Society (2009)

12.

Talebi, M., Abadi, M.: BeeMiner: a novel artificial bee colony algorithm for classification rule discovery. In: Intell. Syst. IEEE (2014)

13.

Fister, I., Fister, I., Brest, J., et al.: Memetic artificial bee colony algorithm for large-scale global optimization (2012)

14.

Banharnsakun, A., Achalakul, T., Sirinaovakul, B.: ABC-GSX: a hybrid method for solving the traveling salesman problem. In: Second World Congress on Nature & Biologically Inspired Computing, NaBIC 2010, Kitakyushu, Japan, 15–17 Dec 2010. IEEE (2010)

15.

Jiang, B.-Q., Pan, J.-S.: A parallel quasi-affine transformation evolution algorithm for global optimization. J. Network Intell. 2(4), 30–46 (2019)

16.

Du, Z.-G., Pan, J.-S., Chu, S.-C., Luo, H.-J., Hu, P.: Quasi-affine transformation evolutionary algorithm with communication schemes for application of RSSI in wireless sensor networks. IEEE Access 8, 8583–8594. https://doi.org/10.1109/ACCESS.2020.2964783

17.

Liu, N., Pan, J.-S., Wang, J., Nguyes, T.-T.: An adaptation multi-group quasi-affine transformation evolutionary algorithm for global optimization and its application in node localization in wireless sensor networks. Sensors 19(19), 4112 (2019). https://doi.org/10.3390/s19194112CrossRef

18.

Zhang, F., Tsu-Yang, Wu., Wang, Y., Xiong, R., Ding, G., Mei, P., Liu, L.: Application of quantum genetic optimization of LVQ neural network in smart city traffic network prediction. IEEE Access 8, 104555–104564 (2020)CrossRef

19.

Chu, S.-C., Chen, Y., Meng, F., Yang, C., Pan, J.-S., Meng, Z.: Internal search of the evolution matrix in QUasi-Affine TRansformation Evolution (QUATRE) algorithm. J. Intell. Fuzzy Syst. 38(5), 5673–5684 (2020)CrossRef

20.

Chen, J.-N., Zhou, Y.-P., Huang, Z.-J., Wu, T.-Y., Zou, F.-M., Tso, R.: An efficient aggregate signature scheme for healthcare wireless sensor networks. J. Network Intell. 6(1):1-15 (2021)

21.

Liu, N., Pan, J.-S., Sun, C., Chu, S.-C.: An efficient surrogate-assisted QUasi-affine TRansformation evolutionary algorithm for expensive optimization problems. Knowl. Based Syst. (2020) (Accepted)

22.

Chu, S.-C., Huang, H.-C., Roddick, J.F., Pan, J.-S.: Overview of algorithms for swarm intelligence. ICCCI 1(2011), 28–41 (2011)

23.

Sun, C., Jin, Y., Cheng, R., Ding, J., Zeng, J.: Surrogate-assisted cooperative swarm optimization of high-dimensional expensive problems. IEEE Trans. Evol. Comput. 21(4), 644–660 (2017)CrossRef

24.

Zhao, L., Gai, M., Jia, Y.: Classification of multiple power quality disturbances based on PSO-SVM of hybrid kernel function. J. Inform. Hiding Multimedia Signal Process. 10(1), 138–146 (2019)

25.

Nguyen, T.-T., Chu, S.-C., Dao, T.-K., Nguyen, T.-D., Ngo, T.-G.: An optimal deployment wireless sensor network based on compact differential evolution. J. Network Intell. 2(3), 263–274 (2017)

26.

Wang, H., Zhijian, Wu., Rahnamayan, S., Sun, H., Liu, Y., Pan, J.-S.: Multi-strategy ensemble artificial bee colony algorithm. Inf. Sci. 279, 587–603 (2014)MathSciNetCrossRef

27.

Pan, J.-S., Wang, H., Zhao, H., Tang, L.-L.: Interaction artificial bee colony based load balance method in cloud computing, in \textit{ICGEC 2014}, pp 49–57

28.

Tang, L., Zhang, Xi., Li, Z., Zhang, Y.: A New hybrid task scheduling algorithm designed based on ACO and GA. J. Inform. Hiding Multimedia Signal Process. 9(6), 1585–1594 (2018)

29.

Chu, S.-C., Roddick, J.F., Su, C.-J., Pan, J.-S.: Constrained ant colony optimization for data clustering, in 8th Pacific Rim International Conference on Artificial Intelligence, LNAI 3157 (2004), pp. 534–543

Titel: Hybrid Optimization Algorithm Based on QUATRE and ABC Algorithms
verfasst von: Xin Zhang
Linlin Tang
Shu-Chuan Chu
Shaowei Weng
Jeng-Shyang Pan
Verlag: Springer Singapore
Buch: Advances in Smart Vehicular Technology, Transportation, Communication and Applications
Print ISBN: 978-981-16-4038-4

Electronic ISBN: 978-981-16-4039-1

Copyright-Jahr: 2022
DOI: https://doi.org/10.1007/978-981-16-4039-1_18

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