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Research Article

Equilibrium optimizer of interswarm interactive learning strategy

, ORCID Icon, &
Article: 1949636 | Received 09 Feb 2021, Accepted 26 Jun 2021, Published online: 07 Jul 2021

References

  • Casbeer, D. W., D. B. Kingston, R. W. Beard, and T. W. McLain. 2006. “Co- Operative Forest fire Surveillance Using a Team of Small Unmanned Air Vehicles.” International Journal of Systems Science 37 (6): 27–51. doi:10.1080/00207720500438480.
  • Chang, J. F., S. Chuan Chu, J. F. Roddick, and J. Shyang Pan. 2005. “A Parallel Particle Swarm Optimization Algorithm with Communication Strategies.” Journal of Information Science And Engineering 21 (4): 809–818.
  • Chen, Y., X. G. Zhao, and J. D. Han. 2010. “Review of 3D Path Planning Methods for Mobile Robot.” Robot 32 (4): 568–576. doi:10.3724/SP.J.1218.2010.00568.
  • Chen, Y.-B., G.-C. Luo, Y.-S. Mei, Y. Jian-qiao, and S. Xiao-long. 2016. “UAV Path Planning Using Artificial Potential field Method Updated by Optimal Control Theory.” International Journal of Systems Science 47 (6): 1407–1420. doi:10.1080/00207721.2014.929191.
  • Das, S., and P. N. Suganthan. 2010. “Differential Evolution: A Survey of the State-of-the-art.” IEEE Transactions on Evolutionary Computation 15 (1): 4–31. doi:10.1109/TEVC.2010.2059031.
  • Dorigo, M., and G. D. Caro. 2002. “Ant Colony Optimization: A New Meta-heuristic.” In Congress on Evolutionary Computation,  Washington, DC, USA.
  • Dovis, F., L. L. Presti, E. Magli, P. Mulassano, and G. Olmo. 2001. “Stratospheric Platforms: A Novel Technological Support for Earth Observation and Remote Sensing Applications.” In Sensors, Systems, and Next-Generation Satellites V. Vol. 4540, 402–411. United States: International Society for Optics and Photonics.
  • Elfes, A., S. S. Bueno, J. G. R. Josu´e, D. P. Ely C, M. Bergerman, R. H. C. Jos´e, S. M. Maeta, L. G. B. Mirisola, B. G. Faria, and R. A. Jos´e. 2002. “Modelling, Control and Perception for an Autonomous Robotic Airship.” Sensor Based In- Telligent Robots 2238: 216–244.
  • Faramarzi, A., M. Heidarinejad, B. Stephens, and S. Mirjalili. 2020. “Equilibrium Optimizer: A Novel Optimization Algorithm.” Knowledge-Based Systems 191: 105190. doi:10.1016/j.knosys.2019.105190.
  • Foo, J. L., J. Knutzon, V. Kalivarapu, J. Oliver, and E. Winer. 2009. “Path planning of unmanned aerial vehicles using B-splines and particle swarm optimization.” Journal of aerospace computing, Information, and communication 6 (4): 271–290.
  • Formato, R. A. 2009. “Central Force Optimization: A New Deterministic Gradient-like Optimiza- Tion Metaheuristic.” OPSEARCH 46 (1): 25–51. doi:10.1007/s12597-009-0003-4.
  • Gigras, Y., K. Gupta, and K. Choudhury. 2015. “A Comparison between Bat Algorithm and Cuckoo Search for Path Planning.” International Journal of Innovative Research in Computer and Communication Engineering 3 (5): 4459–4466.
  • Goldberg, D. E. 1989. “Genetic Algorithms in Search.” Optimization, and Machine Learning:372.
  • Gupta, S., K. Deep, and S. Mirjalili. 2020. “An Efficient Equilibrium Op- Timizer with Mutation Strategy for Numerical Optimization.” Applied Soft Computing 96: 106542. doi:10.1016/j.asoc.2020.106542.
  • Holt, J., S. Biaz, L. Yilmaz, and C. Affane Aji. 2014. “A Symbiotic Simulation Architecture for Evaluating UAVs Collision Avoidance Techniques.” Journal of Simulation 8 (1): 64–75. doi:10.1057/jos.2013.5.
  • Hunt, E. R., W. Dean Hively, S. J. Fujikawa, D. S. Linden, C. St Daugh- Try, and W. M. Greg. 2010. “Acquisition of NIR-green-blue Digital Photographs from Unmanned Aircraft for Crop Monitoring.” Remote Sensing 2 (1): 290–305. doi:10.3390/rs2010290.
  • Joyce, T., and J. Michael Herrmann. 2018. “A Review of No Free Lunch Theorems, and Their Implications for Metaheuristic Optimisation.” Nature-inspired Algorithms and Applied Optimization 744: 27–51.
  • Karaboga, D., and B. Basturk. 2008. “On the Performance of Artificial Bee Colony (ABC) Algorithm.” Applied Soft Computing 8 (1): 687–697. doi:10.1016/j.asoc.2007.05.007.
  • Kennedy, J., and R. Eberhart. 1995. “Particle Swarm Optimization.” In Proceedings of ICNN’95-international conference on neural networks, Vol. 4, 1942–1948. Perth, WA, Australia: IEEE.
  • Lan, R., Y. Zhu, L. Huimin, Z. Tang, Z. Liu, and X. Luo. 2020. “Large- Scale Optimisation via Cooperatively Coevolving Competition Swarm Optimiser.” Enterprise Information Systems 14 (9–10): 1439–1456. doi:10.1080/17517575.2019.1681518.
  • Luan, X. L., F. X. Gong, Z. Q. Wei, B. Yin, and Y. T. Sun. 2016. “Using Ant Colony Optimization and Cuckoo Search in AUV 3D Path Planning.” In Software Engineering and Information Technology: Proceedings of the 2015 International Conference on Software Engineering and Information Technology (SEIT2015), 208–212. Guilin, Guangxi, China: World Scientific.
  • Meng, Z., J. S. Pan, and K. K. Tseng. 2019. “PaDE: An Enhanced Differential Evolution Algorithm with Novel Control Parameter Adaptation Schemes for Numerical Opti- Mization.” Knowledge-Based Systems 168: 80–99. doi:10.1016/j.knosys.2019.01.006.
  • Meng, Z., and J.-S. Pan. 2016. “Monkey King Evolution: A New Memetic evolutionary Algorithm and Its Application in Vehicle Fuel Consumption Optimization.” Knowledge-Based Systems 97: 144–157. doi:10.1016/j.knosys.2016.01.009.
  • Meng, Z., J.-S. Pan, and X. Huarong. 2016. “QUasi-Affine TRansformation Evo- Lutionary (QUATRE) Algorithm: A Cooperative Swarm Based Algorithm for Global Optimiza- Tion.” Knowledge-Based Systems 109: 104–121. doi:10.1016/j.knosys.2016.06.029.
  • Meng, Z., J.-S. Pan, and L. Kong. 2018. “Parameters with adaptive learning mechanism (PALM) for the enhancement of differential evolution.” Knowledge-Based Systems 141: 92–112.
  • Mirjalili, S., S. M. Mirjalili, and A. Lewis. 2014. “Grey Wolf Opti- Mizer.” Advances in Engineering Software 69: 46–61. doi:10.1016/j.advengsoft.2013.12.007.
  • Mohanty, P. K., and D. R. Parhi. 2016. “Optimal Path Planning for a Mobile Robot Using Cuckoo Search Algorithm.” Journal of Experimental & Theoretical Artificial Intelligence 28 (1–2): 35–52. doi:10.1080/0952813X.2014.971442.
  • Mucherino, A., O. Seref, O. Seref, O. Erhun Kundakcioglu, and P. Pardalos. 2007. “Monkey Search: A Novel Metaheuristic Search for Global Optimization.” American Institute of Physics 953: 162–173.
  • Mussi, L., F. Daolio, and S. Cagnoni. 2012. “Evaluation of Parallel Particle Swarm Optimization Algorithms within the CUDA Architecture.” Information Sciences 181 (20): 4642–4657. doi:10.1016/j.ins.2010.08.045.
  • Pan, J. S., P. Hu, and S. C. Chu. 2019. “Novel Parallel Heterogeneous Meta-Heuristic and Its Communication Strategies for the Prediction of Wind Power.” Processes 7 (11): 845. doi:10.3390/pr7110845.
  • Pan, J.-S., J.-L. Liu, and S.-C. Hsiung. 2019. “Chaotic Cuckoo Search Algo- Rithm for Solving Unmanned Combat Aerial Vehicle Path Planning Problems.” In Proceedings of the 2019 11th International Conference on Machine Learning and Computing, 224–230, Zhuhai, China.
  • Pan, J.-S., Z. Meng, S.-C. Chu, and X. Hua-Rong. 2017. “Monkey King Evolution: An Enhanced Ebb-tide-fish Algorithm for Global Optimization and Its Application in Vehicle Navigation under Wireless Sensor Network Environment.” Telecommunication Systems 65 (3): 351–364. doi:10.1007/s11235-016-0237-4.
  • Pan, R. 2004. “Ant Colony System with Communication Strategies.” Information Sciences. vol 167.
  • Parouha, R. P., and K. N. Das. 2016. “A memory based differential evolution algorithm for unconstrained optimization.” Applied Soft Computing 38: 501–517.
  • Pooranian, Z., M. Shojafar, J. H. Abawajy, and A. Abraham. 2015. “An Efficient Meta-heuristic Algorithm for Grid Computing.” Journal of Combinatorial Optimization 30 (3): 413–434. doi:10.1007/s10878-013-9644-6.
  • Qin, A. K., V. L. Huang, and P. N. Suganthan. 2009. “Differential Evolution Algorithm with Strategy Adaptation for Global Numerical Optimization.” IEEE Transactions on Evolu- Tionary Computation 13 (2): 398–417. doi:10.1109/TEVC.2008.927706.
  • Rashedi, E., H. Nezamabadi-Pour, and S. Saryazdi. 2009. “GSA: a gravitational search algorithm.” Information sciences 179 (13): 2232–2248.
  • Sharma, R. K., and D. Ghose. 2009. “Collision Avoidance between UAV Clusters Using Swarm Intelligence Techniques.” International Journal of Systems Science 40 (5): 521–538. doi:10.1080/00207720902750003.
  • Shi, Y., and R. Eberhart. 1998. “A modified particle swarm optimizer.” In 1998IEEE international conference on evolutionary computation proceedings. IEEE world congress on computational intelligence (Cat. No. 98TH8360), 69–73. IEEE.
  • Shi, Y., and R. C. Eberhart. 1999. “Empirical study of particle swarm optimization.” In Proceedings of the 1999congress on evolutionary computation-CEC99 (Cat. No. 99TH8406), Vol. 3, 1945–1950. IEEE.
  • Storn, R., and K. Price. 1997. “Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces.” Journal of Global Optimization 11 (4): 341–359. doi:10.1023/A:1008202821328.
  • Sutton, R., and A. Barto. 1998. “Reinforcement Learning: An Introduction (Adaptive Compu- Tation and Machine Learning).” IEEE transactions on neural networks. U.S. and Canada.
  • Tsai, P. W., J. S. Pan, S. M. Chen, B. Y. Liao, and S. P. Hao. 2008. “Parallel Cat Swarm Optimization.” In Machine Learning and Cybernetics, 2008 International Conference on. Kunming, China
  • Tuba, E., I. Strumberger, D. Zivkovic, N. Bacanin, and M. Tuba. 2018. “Mobile Robot Path Planning by Improved Brain Storm Optimization Algorithm.” In 2018 IEEE Congress on Evolutionary Computation (CEC), 1–8. Rio de Janeiro, Brazil: IEEE.
  • Wang, G.-G., H. E. Chu, and S. Mirjalili. 2016. “Three-dimensional Path Planning for UCAV Using an Improved Bat Algorithm.” Aerospace Science and Technology 49: 231–238. doi:10.1016/j.ast.2015.11.040.
  • Weber, M., F. Neri, and V. Tirronen. 2011. “Shuffle or Update Parallel Differ- Ential Evolution for Large-scale Optimization.” Soft Computing 15 (11): 2089–2107. doi:10.1007/s00500-010-0640-9.
  • Wolpert, D. H., and W. G. Macready. 1997. “No Free Lunch Theorems for Optimization.” IEEE Transactions on Evolutionary Computation 1 (1): 67–82. doi:10.1109/4235.585893.
  • Wunnava, A., M. K. Naik, R. Panda, B. Jena, and A. Abra- ham. 2020. “A Novel Interdependence Based Multilevel Thresholding Technique Using Adaptive Equilibrium Optimizer.” Engineering Applications of Artificial Intelligence 94: 103836. doi:10.1016/j.engappai.2020.103836.
  • Yang, Z., K. Li, Q. Niu, and Y. Xue. 2017. “A novel parallel-series hybrid metaheuristic method for solving a hybrid unit commitment problem.” Knowledge-Based Systems 134: 13–30.
  • Yang, X.-S. 2010. “Firefly algorithm, stochastic test functions and design optimisation.” International journal of bio-inspired computation 2 (2): 78–84.
  • Yao, X., Y. Liu, and G. Lin. 1999. “Evolutionary programming made faster.” IEEE Transactions on Evolutionary computation 3 (2): 82–102.
  • Yue, J., T. Lei, L. Changchun, and J. Zhu. 2012. “The Application of Un- Manned Aerial Vehicle Remote Sensing in Quickly Monitoring Crop Pests.” Intelligent Automa- Tion & Soft Computing 18 (8): 1043–1052.
  • Zhang, S., Y. Zhou, L. Zhiming, and W. Pan. 2016. “Grey Wolf Optimizer for Un- Manned Combat Aerial Vehicle Path Planning.” Advances in Engineering Software 99: 121–136. doi:10.1016/j.advengsoft.2016.05.015.
  • Zhao, M. 2020. “A Novel Compact Cat Swarm Optimization Based on Differential Method.” Enterprise Information Systems 14 (2): 196–220. doi:10.1080/17517575.2018.1462405.

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