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| 1 | A novel hybrid Cuckoo search algorithm based on simplex operator显示文摘 | Zheng Hongqing Luo Qifang Zhou Yongquan | 2012 | JDC- TA2012，6，13： | 1 |
| 2 | Quantum-Inspired Equilibrium Optimizer for Linear Antenna Array显示文摘With the rapid development of communication technology,the problem of antenna array optimization plays a crucial role.Among many types of antennas,line antenna arrays(LAA)are the most commonly applied,but the side lobe level(SLL)reduction is still a challenging problem.In the radiation process of the linear antenna array,the high side lobe level will interfere with the intensity of the antenna target radiation direction.Many conventional methods are ineffective in obtaining the maximumside lobe level in synthesis,and this paper proposed a quantum equilibrium optimizer(QEO)algorithm for line antenna arrays.Firstly,the linear antenna array model consists of an array element arrangement.Array factor(AF)can be expressed as the combination of array excitation amplitude and position in array space.Then,inspired by the powerful computing power of quantum computing,an improved quantum equilibrium optimizer combining quantum coding and quantum rotation gate strategy is proposed.Finally,the proposed quantum equilibrium optimizer is used to optimize the excitation amplitude of the array elements in the linear antenna array model by numerical simulation to minimize the interference of the side lobe level to the main lobe radiation.Six differentmetaheuristic algorithms are used to optimize the excitation amplitude in three different arrays of line antenna arrays,the experimental results indicated that the quantum equilibrium optimizer is more advantageous in obtaining the maximum side lobe level reduction.Compared with other metaheuristic optimization algorithms,the quantum equilibrium optimizer has advantages in terms of convergence speed and accuracy. | Binwen Zhu Qifang Luo Yongquan Zhou | 2023 | Computer Modeling in Engineering & Sciences2023，，10： | 1 |
| 3 | A novel discrete cuckoo search algorithm for spherical traveling salesman problem显示文摘 | Ouyang Xinxin Zhou Yongquan Luo Qifang | 2013 | Applied Mathematics&Information Sciences2013，7，2： | 1 |
| 4 | Radiation-induced sarcoma of head and neck: 50 years of experience at a single institution in an endemic area of nasopharyngeal carcinoma in China显示文摘 | Zhengbo Wei Ying Xie Jian Xu Yuan Luo Falong Chen Yunli Yang Qifang Huang Anzhou Tang Guangwu Huang | 2012 | Medical Oncology2012，，2： | 1 |
| 5 | Wind Driven Butterfly Optimization Algorithm with Hybrid Mechanism Avoiding Natural Enemies for Global Optimization and PID Controller Design显示文摘This paper presents a Butterfly Optimization Algorithm(BOA)with a wind-driven mechanism for avoiding natural enemies known as WDBOA.To further balance the basic BOA algorithm's exploration and exploitation capabilities,the butterfly actions were divided into downwind and upwind states.The algorithm of exploration ability was improved with the wind,while the algorithm of exploitation ability was improved against the wind.Also,a mechanism of avoiding natural enemies based on Lévy flight was introduced for the purpose of enhancing its global searching ability.Aiming at improving the explorative performance at the initial stages and later stages,the fragrance generation method was modified.To evaluate the effectiveness of the suggested algorithm,a comparative study was done with six classical metaheuristic algorithms and three BOA variant optimization techniques on 18 benchmark functions.Further,the performance of the suggested technique in addressing some complicated problems in various dimensions was evaluated using CEC 2017 and CEC 2020.Finally,the WDBOA algorithm is used proportional-integral-derivative(PID)controller parameter optimization.Experimental results demonstrate that the WDBOA based PID controller has better control performance in comparison with other PID controllers tuned by the Genetic Algorithm(GA),Flower Pollination Algorithm(FPA),Cuckoo Search(CS)and BOA. | Yang He Yongquan Zhou Yuanfei Wei Qifang Luo Wu Deng | 2023 | Journal of Bionic Engineering2023，20，6： | 0 |
| 6 | IBMSMA: An Indicator-based Multi-swarm Slime Mould Algorithm for Multi-objective Truss Optimization Problems显示文摘This work proposes an improved multi-objective slime mould algorithm, called IBMSMA, for solving the multi-objective truss optimization problem. In IBMSMA, the chaotic grouping mechanism and dynamic regrouping strategy are employed to improve population diversity;the shift density estimation is used to assess the superiority of search agents and to provide selection pressure for population evolution;and the Pareto external archive is utilized to maintain the convergence and distribution of the non-dominated solution set. To evaluate the performance of IBMSMA, it is applied to eight multi-objective truss optimization problems. The results obtained by IBMSMA are compared with other 14 well-known optimization algorithms on hypervolume, inverted generational distance and spacing-to-extent indicators. The Wilcoxon statistical test and Friedman ranking are used for statistical analysis. The results of this study reveal that IBMSMA can find the Pareto front with better convergence and diversity in less time than state-of-the-art algorithms, demonstrating its capability in tackling large-scale engineering design problems. | Shihong Yin Qifang Luo Yongquan Zhou | 2023 | Journal of Bionic Engineering2023，20，3： | 0 |
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