Improved puzzle optimization algorithm with multi-strategy integration and its application

Xiaogang Liu; Wenbo Gao

doi:10.1117/12.2659693

22 November 2022 Improved puzzle optimization algorithm with multi-strategy integration and its application

Xiaogang Liu, Wenbo Gao

Proceedings Volume 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022); 124751M (2022) https://doi.org/10.1117/12.2659693
Event: Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 2022, Hulun Buir, China

Abstract

Aiming at the problems of low solution accuracy, slow convergence speed and easy to fall into local optimization, a multi-strategy fusion improved puzzle optimization algorithm (IPOA) is proposed. Improved Circle mapping strategy, dwarf mongoose optimization (DMO) strategy, and adaptive t-distribution variation strategy were used to increase the diversity of puzzle populations, improve global search capabilities and local development performance. Through the analysis of multiple benchmark function simulation experiments and PID controller parameter optimization problems, the results show that the IPOA algorithm has high optimization accuracy, fast convergence speed and effectiveness in solving practical engineering problems.

Citation Download Citation

Xiaogang Liu and Wenbo Gao "Improved puzzle optimization algorithm with multi-strategy integration and its application", Proc. SPIE 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 124751M (22 November 2022); https://doi.org/10.1117/12.2659693

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