The backtracking search optimization algorithm（BSA） is one of the most recently proposed population-based evolutionary algorithms for global optimization. Due to its memory ability and simple structure, BSA has powe...The backtracking search optimization algorithm（BSA） is one of the most recently proposed population-based evolutionary algorithms for global optimization. Due to its memory ability and simple structure, BSA has powerful capability to find global optimal solutions. However, the algorithm is still insufficient in balancing the exploration and the exploitation. Therefore, an improved adaptive backtracking search optimization algorithm combined with modified Hooke-Jeeves pattern search is proposed for numerical global optimization. It has two main parts： the BSA is used for the exploration phase and the modified pattern search method completes the exploitation phase. In particular, a simple but effective strategy of adapting one of BSA＇s important control parameters is introduced. The proposed algorithm is compared with standard BSA, three state-of-the-art evolutionary algorithms and three superior algorithms in IEEE Congress on Evolutionary Computation 2014（IEEE CEC2014） over six widely-used benchmarks and 22 real-parameter single objective numerical optimization benchmarks in IEEE CEC2014. The results of experiment and statistical analysis demonstrate the effectiveness and efficiency of the proposed algorithm.展开更多
With consideration of the differences between concrete and steel,three solutions using genetic evolutionary structural optimization algorithm were presented to automatically develop optimal strut-and-tie model for dee...With consideration of the differences between concrete and steel,three solutions using genetic evolutionary structural optimization algorithm were presented to automatically develop optimal strut-and-tie model for deep beams.In the finite element analysis of the first method,the concrete and steel rebar are modeled by a plane element and a bar element,respectively.In the second method,the concrete and steel are assigned to two different plane elements,whereas in the third method only one kind of plane element is used with no consideration of the differences of the two materials.A simply supported beam under two point loads was presented as an example to verify the validity of the three proposed methods.The results indicates that all the three methods can generate optimal strut-and-tie models and the third algorithm has powerful capability in searching more optimal results with less computational effort.The effectiveness of the proposed algorithm III has also been demonstrated by other two examples.展开更多
基金supported by the National Natural Science Foundation of China(61271250)
文摘The backtracking search optimization algorithm（BSA） is one of the most recently proposed population-based evolutionary algorithms for global optimization. Due to its memory ability and simple structure, BSA has powerful capability to find global optimal solutions. However, the algorithm is still insufficient in balancing the exploration and the exploitation. Therefore, an improved adaptive backtracking search optimization algorithm combined with modified Hooke-Jeeves pattern search is proposed for numerical global optimization. It has two main parts： the BSA is used for the exploration phase and the modified pattern search method completes the exploitation phase. In particular, a simple but effective strategy of adapting one of BSA＇s important control parameters is introduced. The proposed algorithm is compared with standard BSA, three state-of-the-art evolutionary algorithms and three superior algorithms in IEEE Congress on Evolutionary Computation 2014（IEEE CEC2014） over six widely-used benchmarks and 22 real-parameter single objective numerical optimization benchmarks in IEEE CEC2014. The results of experiment and statistical analysis demonstrate the effectiveness and efficiency of the proposed algorithm.
基金Project(50908082) supported by the National Natural Science Foundation of ChinaProject(2009ZK3111) supported by the Science and Technology Department of Hunan Province,China
文摘With consideration of the differences between concrete and steel,three solutions using genetic evolutionary structural optimization algorithm were presented to automatically develop optimal strut-and-tie model for deep beams.In the finite element analysis of the first method,the concrete and steel rebar are modeled by a plane element and a bar element,respectively.In the second method,the concrete and steel are assigned to two different plane elements,whereas in the third method only one kind of plane element is used with no consideration of the differences of the two materials.A simply supported beam under two point loads was presented as an example to verify the validity of the three proposed methods.The results indicates that all the three methods can generate optimal strut-and-tie models and the third algorithm has powerful capability in searching more optimal results with less computational effort.The effectiveness of the proposed algorithm III has also been demonstrated by other two examples.
