The Bald Eagle Search algorithm(BES)is an emerging meta-heuristic algorithm.The algorithm simulates the hunting behavior of eagles,and obtains an optimal solution through three stages,namely selection stage,search sta...The Bald Eagle Search algorithm(BES)is an emerging meta-heuristic algorithm.The algorithm simulates the hunting behavior of eagles,and obtains an optimal solution through three stages,namely selection stage,search stage and swooping stage.However,BES tends to drop-in local optimization and the maximum value of search space needs to be improved.To fill this research gap,we propose an improved bald eagle algorithm(CABES)that integrates Cauchy mutation and adaptive optimization to improve the performance of BES from local optima.Firstly,CABES introduces the Cauchy mutation strategy to adjust the step size of the selection stage,to select a better search range.Secondly,in the search stage,CABES updates the search position update formula by an adaptive weight factor to further promote the local optimization capability of BES.To verify the performance of CABES,the benchmark function of CEC2017 is used to simulate the algorithm.The findings of the tests are compared to those of the Particle Swarm Optimization algorithm(PSO),Whale Optimization Algorithm(WOA)and Archimedes Algorithm(AOA).The experimental results show that CABES can provide good exploration and development capabilities,and it has strong competitiveness in testing algorithms.Finally,CABES is applied to four constrained engineering problems and a groundwater engineeringmodel,which further verifies the effectiveness and efficiency of CABES in practical engineering problems.展开更多
近年来,海上能源发电技术备受瞩目,一种新兴趋势是将波浪能转换器(wave energy converter,WEC)与海上光伏(offshore floating photovoltaic,OFPV)相结合,形成混合光伏-波浪能转换器系统(hybrid PV-wave energy converter,HPV-WEC)。HPV-...近年来,海上能源发电技术备受瞩目,一种新兴趋势是将波浪能转换器(wave energy converter,WEC)与海上光伏(offshore floating photovoltaic,OFPV)相结合,形成混合光伏-波浪能转换器系统(hybrid PV-wave energy converter,HPV-WEC)。HPV-WEC具有提高海上空间利用率,降低成本以及实现功率稳定输出等优势。为了充分利用HPV-WEC系统之间的协同效应,在不增加新设备的情况下提高能源产量,提出了一种基于改进秃鹰优化算法(improved bald eagle search algorithm,IBES)的HPV-WEC阵列布局优化策略。IBES结合了莱维飞行策略和模拟退火(simulated annealing,SA)机制,以平衡局部开发和全局探索之间的关系。为了评估IBES在优化HPV-WEC阵列方面的有效性,进行了5个浮标和8个浮标规模的阵列优化,并将IBES与其他5种算法进行了比较。实验结果表明,IBES表现出实现最大总功率输出并具有显著的收敛特性。展开更多
基金Project of Key Science and Technology of the Henan Province (No.202102310259)Henan Province University Scientific and Technological Innovation Team (No.18IRTSTHN009).
文摘The Bald Eagle Search algorithm(BES)is an emerging meta-heuristic algorithm.The algorithm simulates the hunting behavior of eagles,and obtains an optimal solution through three stages,namely selection stage,search stage and swooping stage.However,BES tends to drop-in local optimization and the maximum value of search space needs to be improved.To fill this research gap,we propose an improved bald eagle algorithm(CABES)that integrates Cauchy mutation and adaptive optimization to improve the performance of BES from local optima.Firstly,CABES introduces the Cauchy mutation strategy to adjust the step size of the selection stage,to select a better search range.Secondly,in the search stage,CABES updates the search position update formula by an adaptive weight factor to further promote the local optimization capability of BES.To verify the performance of CABES,the benchmark function of CEC2017 is used to simulate the algorithm.The findings of the tests are compared to those of the Particle Swarm Optimization algorithm(PSO),Whale Optimization Algorithm(WOA)and Archimedes Algorithm(AOA).The experimental results show that CABES can provide good exploration and development capabilities,and it has strong competitiveness in testing algorithms.Finally,CABES is applied to four constrained engineering problems and a groundwater engineeringmodel,which further verifies the effectiveness and efficiency of CABES in practical engineering problems.
文摘近年来,海上能源发电技术备受瞩目,一种新兴趋势是将波浪能转换器(wave energy converter,WEC)与海上光伏(offshore floating photovoltaic,OFPV)相结合,形成混合光伏-波浪能转换器系统(hybrid PV-wave energy converter,HPV-WEC)。HPV-WEC具有提高海上空间利用率,降低成本以及实现功率稳定输出等优势。为了充分利用HPV-WEC系统之间的协同效应,在不增加新设备的情况下提高能源产量,提出了一种基于改进秃鹰优化算法(improved bald eagle search algorithm,IBES)的HPV-WEC阵列布局优化策略。IBES结合了莱维飞行策略和模拟退火(simulated annealing,SA)机制,以平衡局部开发和全局探索之间的关系。为了评估IBES在优化HPV-WEC阵列方面的有效性,进行了5个浮标和8个浮标规模的阵列优化,并将IBES与其他5种算法进行了比较。实验结果表明,IBES表现出实现最大总功率输出并具有显著的收敛特性。
