A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rat...A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rate and pitch adjusting rate, are encoded as a symbiotic individual of an original individual(i.e., harmony vector). Harmony search operators are applied to evolving the original population. DE is applied to co-evolving the symbiotic population based on feedback information from the original population. Thus, with the evolution of the original population in DEHS, the symbiotic population is dynamically and self-adaptively adjusted, and real-time optimum control parameters are obtained. The proposed DEHS algorithm has been applied to various benchmark functions and two typical dynamic optimization problems. The experimental results show that the performance of the proposed algorithm is better than that of other HS variants. Satisfactory results are obtained in the application.展开更多
Depending on the numerical test approach on a computer, the relationships among relevant parameters, eg branch number, node number, mesh number, computation accuracy, preliminary value of airflow rate, iteration numbe...Depending on the numerical test approach on a computer, the relationships among relevant parameters, eg branch number, node number, mesh number, computation accuracy, preliminary value of airflow rate, iteration number, computation time and convergence in a mine ventilation network analysis, were investigated based on 5 mine ventilation systems. The results show that a higher computation accuracy greatly influences the iteration number. When the accuracy reaches 10-6m3·s-1 for solving a complicated mine ventilation network, the running time is too long though a high-speed computer is used. The preliminary value of airflow rate in the range of 1100m3·s-1 has little effects the iteration number. The structure of network also has some effect on the iteration number.展开更多
基金Project(2013CB733605)supported by the National Basic Research Program of ChinaProject(21176073)supported by the National Natural Science Foundation of China
文摘A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rate and pitch adjusting rate, are encoded as a symbiotic individual of an original individual(i.e., harmony vector). Harmony search operators are applied to evolving the original population. DE is applied to co-evolving the symbiotic population based on feedback information from the original population. Thus, with the evolution of the original population in DEHS, the symbiotic population is dynamically and self-adaptively adjusted, and real-time optimum control parameters are obtained. The proposed DEHS algorithm has been applied to various benchmark functions and two typical dynamic optimization problems. The experimental results show that the performance of the proposed algorithm is better than that of other HS variants. Satisfactory results are obtained in the application.
基金Project (50474050) supported by the National Natural Science Foundation of China
文摘Depending on the numerical test approach on a computer, the relationships among relevant parameters, eg branch number, node number, mesh number, computation accuracy, preliminary value of airflow rate, iteration number, computation time and convergence in a mine ventilation network analysis, were investigated based on 5 mine ventilation systems. The results show that a higher computation accuracy greatly influences the iteration number. When the accuracy reaches 10-6m3·s-1 for solving a complicated mine ventilation network, the running time is too long though a high-speed computer is used. The preliminary value of airflow rate in the range of 1100m3·s-1 has little effects the iteration number. The structure of network also has some effect on the iteration number.
