Harris hawks optimization(HHO)algorithm is an efficient method of solving function optimization problems.However,it is still confronted with some limitations in terms of low precision,low convergence speed and stagnat...Harris hawks optimization(HHO)algorithm is an efficient method of solving function optimization problems.However,it is still confronted with some limitations in terms of low precision,low convergence speed and stagnation to local optimum.To this end,an improved HHO(IHHO)algorithm based on good point set and nonlinear convergence formula is proposed.First,a good point set is used to initialize the positions of the population uniformly and randomly in the whole search area.Second,a nonlinear exponential convergence formula is designed to balance exploration stage and exploitation stage of IHHO algorithm,aiming to find all the areas containing the solutions more comprehensively and accurately.The proposed IHHO algorithm tests 17 functions and uses Wilcoxon test to verify the effectiveness.The results indicate that IHHO algorithm not only has faster convergence speed than other comparative algorithms,but also improves the accuracy of solution effectively and enhances its robustness under low dimensional and high dimensional conditions.展开更多
A multi-strategy hybrid whale optimization algorithm(MSHWOA)for complex constrained optimization problems is proposed to overcome the drawbacks of easily trapping into local optimum,slow convergence speed and low opti...A multi-strategy hybrid whale optimization algorithm(MSHWOA)for complex constrained optimization problems is proposed to overcome the drawbacks of easily trapping into local optimum,slow convergence speed and low optimization precision.Firstly,the population is initialized by introducing the theory of good point set,which increases the randomness and diversity of the population and lays the foundation for the global optimization of the algorithm.Then,a novel linearly update equation of convergence factor is designed to coordinate the abilities of exploration and exploitation.At the same time,the global exploration and local exploitation capabilities are improved through the siege mechanism of Harris Hawks optimization algorithm.Finally,the simulation experiments are conducted on the 6 benchmark functions and Wilcoxon rank sum test to evaluate the optimization performance of the improved algorithm.The experimental results show that the proposed algorithm has more significant improvement in optimization accuracy,convergence speed and robustness than the comparison algorithm.展开更多
针对油井采出液含水率不断增加,转油站集输系统效率低、能耗高的问题,对转油站集输系统进行运行参数优化。以掺水温度和掺水量为决策变量,生产能耗费用最低为目标函数,建立转油站运行参数优化模型。采用人工设计与佳点集原理相结合的种...针对油井采出液含水率不断增加,转油站集输系统效率低、能耗高的问题,对转油站集输系统进行运行参数优化。以掺水温度和掺水量为决策变量,生产能耗费用最低为目标函数,建立转油站运行参数优化模型。采用人工设计与佳点集原理相结合的种群初始化策略和引入非线性收敛因子等机制对传统鲸鱼算法进行改进,以大庆PH2转油站为例,采用改进鲸鱼算法对运行参数进行优化,结果表明,改进后的鲸鱼算法综合性能明显提高,并且优化后转油站掺水温度降低9℃,掺水量减少450 m 3/d,日均耗气量下降14.68%,日均耗电量降低34.1%,总体运行费用降低了21.5%,优化效果良好。研究成果可供类似工程参考。展开更多
基金supported by the National Natural Science Foundation of China(61872126)。
文摘Harris hawks optimization(HHO)algorithm is an efficient method of solving function optimization problems.However,it is still confronted with some limitations in terms of low precision,low convergence speed and stagnation to local optimum.To this end,an improved HHO(IHHO)algorithm based on good point set and nonlinear convergence formula is proposed.First,a good point set is used to initialize the positions of the population uniformly and randomly in the whole search area.Second,a nonlinear exponential convergence formula is designed to balance exploration stage and exploitation stage of IHHO algorithm,aiming to find all the areas containing the solutions more comprehensively and accurately.The proposed IHHO algorithm tests 17 functions and uses Wilcoxon test to verify the effectiveness.The results indicate that IHHO algorithm not only has faster convergence speed than other comparative algorithms,but also improves the accuracy of solution effectively and enhances its robustness under low dimensional and high dimensional conditions.
基金the National Natural Science Foundation of China(No.62176146)。
文摘A multi-strategy hybrid whale optimization algorithm(MSHWOA)for complex constrained optimization problems is proposed to overcome the drawbacks of easily trapping into local optimum,slow convergence speed and low optimization precision.Firstly,the population is initialized by introducing the theory of good point set,which increases the randomness and diversity of the population and lays the foundation for the global optimization of the algorithm.Then,a novel linearly update equation of convergence factor is designed to coordinate the abilities of exploration and exploitation.At the same time,the global exploration and local exploitation capabilities are improved through the siege mechanism of Harris Hawks optimization algorithm.Finally,the simulation experiments are conducted on the 6 benchmark functions and Wilcoxon rank sum test to evaluate the optimization performance of the improved algorithm.The experimental results show that the proposed algorithm has more significant improvement in optimization accuracy,convergence speed and robustness than the comparison algorithm.
文摘针对油井采出液含水率不断增加,转油站集输系统效率低、能耗高的问题,对转油站集输系统进行运行参数优化。以掺水温度和掺水量为决策变量,生产能耗费用最低为目标函数,建立转油站运行参数优化模型。采用人工设计与佳点集原理相结合的种群初始化策略和引入非线性收敛因子等机制对传统鲸鱼算法进行改进,以大庆PH2转油站为例,采用改进鲸鱼算法对运行参数进行优化,结果表明,改进后的鲸鱼算法综合性能明显提高,并且优化后转油站掺水温度降低9℃,掺水量减少450 m 3/d,日均耗气量下降14.68%,日均耗电量降低34.1%,总体运行费用降低了21.5%,优化效果良好。研究成果可供类似工程参考。
