Recently,multimodal multiobjective optimization problems(MMOPs)have received increasing attention.Their goal is to find a Pareto front and as many equivalent Pareto optimal solutions as possible.Although some evolutio...Recently,multimodal multiobjective optimization problems(MMOPs)have received increasing attention.Their goal is to find a Pareto front and as many equivalent Pareto optimal solutions as possible.Although some evolutionary algorithms for them have been proposed,they mainly focus on the convergence rate in the decision space while ignoring solutions diversity.In this paper,we propose a new multiobjective fireworks algorithm for them,which is able to balance exploitation and exploration in the decision space.We first extend a latest single-objective fireworks algorithm to handle MMOPs.Then we make improvements by incorporating an adaptive strategy and special archive guidance into it,where special archives are established for each firework,and two strategies(i.e.,explosion and random strategies)are adaptively selected to update the positions of sparks generated by fireworks with the guidance of special archives.Finally,we compare the proposed algorithm with eight state-of-the-art multimodal multiobjective algorithms on all 22 MMOPs from CEC2019 and several imbalanced distance minimization problems.Experimental results show that the proposed algorithm is superior to compared algorithms in solving them.Also,its runtime is less than its peers'.展开更多
Regarding the spatial profile extraction method of a multi-field co-simulation dataset,different extraction directions,locations,and numbers of profileswill greatly affect the representativeness and integrity of data....Regarding the spatial profile extraction method of a multi-field co-simulation dataset,different extraction directions,locations,and numbers of profileswill greatly affect the representativeness and integrity of data.In this study,a multi-field co-simulation data extractionmethod based on adaptive infinitesimal elements is proposed.Themultifield co-simulation dataset based on related infinitesimal elements is constructed,and the candidate directions of data profile extraction undergo dimension reduction by principal component analysis to determine the direction of data extraction.Based on the fireworks algorithm,the data profile with optimal representativeness is searched adaptively in different data extraction intervals to realize the adaptive calculation of data extraction micro-step length.The multi-field co-simulation data extraction process based on adaptive microelement is established and applied to the data extraction process of the multi-field co-simulation dataset of the sintering furnace.Compared with traditional data extraction methods for multi-field co-simulation,the approximate model constructed by the data extracted from the proposed method has higher construction efficiency.Meanwhile,the relative maximum absolute error,root mean square error,and coefficient of determination of the approximationmodel are better than those of the approximation model constructed by the data extracted from traditional methods,indicating higher accuracy,it is verified that the proposed method demonstrates sound adaptability and extraction efficiency.展开更多
高温环境下合金600在压力和输送介质的耦合作用下易发生应力腐蚀开裂,是合金管道的潜在失效模式,在多种影响因素共同作用下,一般参数化模型存在预测精度不高、泛化能力较差的问题,影响合金管道安全评估的准确性。将Faure序列初始种群、...高温环境下合金600在压力和输送介质的耦合作用下易发生应力腐蚀开裂,是合金管道的潜在失效模式,在多种影响因素共同作用下,一般参数化模型存在预测精度不高、泛化能力较差的问题,影响合金管道安全评估的准确性。将Faure序列初始种群、自适应引力全局搜索、精英保留策略局部搜索引入烟花算法,使用改进烟花算法(Improved Fire War Algorithm,IFWA)对结合Lasso回归和随机森林组成的回归增强随机森林算法(Regression-Enhanced Random Forest,RERF)超参数基学习器数量(n_estimate)、树的最大深度(max_depth)寻优,以RMSE为目标值使RERF达到全局搜索和局部搜索最优,形成基于IFWA-RERF的合金600应力腐蚀裂纹扩展速率预测模型,引入MAE和R2作为模型性能评价指标,建立数据集与测试集进行对比。结果表明:使用基于IFWA-RERF的合金600应力腐蚀裂纹扩展速率预测结果最接近实际数据,预测精度和稳定性均优于其他对比模型,有助于建立准确的安全评估模型。展开更多
基金supported in part by the National Natural Science Foundation of China(62071230,62061146002)the Natural Science Foundation of Jiangsu Province(BK20211567)the Deanship of Scientific Research(DSR)at King Abdulaziz University(KAU),Jeddah,Saudi Arabia(FP-147-43)。
文摘Recently,multimodal multiobjective optimization problems(MMOPs)have received increasing attention.Their goal is to find a Pareto front and as many equivalent Pareto optimal solutions as possible.Although some evolutionary algorithms for them have been proposed,they mainly focus on the convergence rate in the decision space while ignoring solutions diversity.In this paper,we propose a new multiobjective fireworks algorithm for them,which is able to balance exploitation and exploration in the decision space.We first extend a latest single-objective fireworks algorithm to handle MMOPs.Then we make improvements by incorporating an adaptive strategy and special archive guidance into it,where special archives are established for each firework,and two strategies(i.e.,explosion and random strategies)are adaptively selected to update the positions of sparks generated by fireworks with the guidance of special archives.Finally,we compare the proposed algorithm with eight state-of-the-art multimodal multiobjective algorithms on all 22 MMOPs from CEC2019 and several imbalanced distance minimization problems.Experimental results show that the proposed algorithm is superior to compared algorithms in solving them.Also,its runtime is less than its peers'.
基金This work is supported by the NationalNatural Science Foundation of China(No.52075350)the Major Science and Technology Projects of Sichuan Province(No.2022ZDZX0001)the Special City-University Strategic Cooperation Project of Sichuan University and Zigong Municipality(No.2021CDZG-3).
文摘Regarding the spatial profile extraction method of a multi-field co-simulation dataset,different extraction directions,locations,and numbers of profileswill greatly affect the representativeness and integrity of data.In this study,a multi-field co-simulation data extractionmethod based on adaptive infinitesimal elements is proposed.Themultifield co-simulation dataset based on related infinitesimal elements is constructed,and the candidate directions of data profile extraction undergo dimension reduction by principal component analysis to determine the direction of data extraction.Based on the fireworks algorithm,the data profile with optimal representativeness is searched adaptively in different data extraction intervals to realize the adaptive calculation of data extraction micro-step length.The multi-field co-simulation data extraction process based on adaptive microelement is established and applied to the data extraction process of the multi-field co-simulation dataset of the sintering furnace.Compared with traditional data extraction methods for multi-field co-simulation,the approximate model constructed by the data extracted from the proposed method has higher construction efficiency.Meanwhile,the relative maximum absolute error,root mean square error,and coefficient of determination of the approximationmodel are better than those of the approximation model constructed by the data extracted from traditional methods,indicating higher accuracy,it is verified that the proposed method demonstrates sound adaptability and extraction efficiency.
文摘高温环境下合金600在压力和输送介质的耦合作用下易发生应力腐蚀开裂,是合金管道的潜在失效模式,在多种影响因素共同作用下,一般参数化模型存在预测精度不高、泛化能力较差的问题,影响合金管道安全评估的准确性。将Faure序列初始种群、自适应引力全局搜索、精英保留策略局部搜索引入烟花算法,使用改进烟花算法(Improved Fire War Algorithm,IFWA)对结合Lasso回归和随机森林组成的回归增强随机森林算法(Regression-Enhanced Random Forest,RERF)超参数基学习器数量(n_estimate)、树的最大深度(max_depth)寻优,以RMSE为目标值使RERF达到全局搜索和局部搜索最优,形成基于IFWA-RERF的合金600应力腐蚀裂纹扩展速率预测模型,引入MAE和R2作为模型性能评价指标,建立数据集与测试集进行对比。结果表明:使用基于IFWA-RERF的合金600应力腐蚀裂纹扩展速率预测结果最接近实际数据,预测精度和稳定性均优于其他对比模型,有助于建立准确的安全评估模型。
