With the development of parallel computing technology,non-linear inversion calculation efficiency has been improving.However,for single-point search-based non-linear inversion methods,the implementation of parallel al...With the development of parallel computing technology,non-linear inversion calculation efficiency has been improving.However,for single-point search-based non-linear inversion methods,the implementation of parallel algorithms is a difficult issue.We introduce the idea of group search to the single-point search-based non-linear inversion algorithm, taking the quantum Monte Carlo method as an example for two-dimensional seismic wave velocity inversion and practical impedance inversion and test the calculation efficiency of using different node numbers.The results show the parallel algorithm in theoretical and practical data inversion is feasible and effective.The parallel algorithm has good versatility. The algorithm efficiency increases with increasing node numbers but the algorithm efficiency rate of increase gradually decreases as the node numbers increase.展开更多
Differential evolution （DE） is a global optimizer for continuous design variables. To enhance DE, it is necessary to handle discrete design variables. In this paper, a discrete differential evolution （DDE） algorit...Differential evolution （DE） is a global optimizer for continuous design variables. To enhance DE, it is necessary to handle discrete design variables. In this paper, a discrete differential evolution （DDE） algorithm is proposed to handle discrete design variables The proposed DDE is based on the DE/l/rand/bin method. In the proposed DDE, the mutation ratio is regarded as the exchange probability, and thus, no modifications of DE/l/rand/bin are required. In addition, in order to maintain diversity through the search process, we initialize all search points. By introducing the initialization of all search points, global or quasi-optimum solution can be found. We validate the proposed DDE by applying it to several benchmark problems.展开更多
基金supported by National Key S&T Special Projects of Marine Carbonate(No.2008ZX05000-004)CNPC Projects(No.2008E-0610-10)
文摘With the development of parallel computing technology,non-linear inversion calculation efficiency has been improving.However,for single-point search-based non-linear inversion methods,the implementation of parallel algorithms is a difficult issue.We introduce the idea of group search to the single-point search-based non-linear inversion algorithm, taking the quantum Monte Carlo method as an example for two-dimensional seismic wave velocity inversion and practical impedance inversion and test the calculation efficiency of using different node numbers.The results show the parallel algorithm in theoretical and practical data inversion is feasible and effective.The parallel algorithm has good versatility. The algorithm efficiency increases with increasing node numbers but the algorithm efficiency rate of increase gradually decreases as the node numbers increase.
文摘Differential evolution （DE） is a global optimizer for continuous design variables. To enhance DE, it is necessary to handle discrete design variables. In this paper, a discrete differential evolution （DDE） algorithm is proposed to handle discrete design variables The proposed DDE is based on the DE/l/rand/bin method. In the proposed DDE, the mutation ratio is regarded as the exchange probability, and thus, no modifications of DE/l/rand/bin are required. In addition, in order to maintain diversity through the search process, we initialize all search points. By introducing the initialization of all search points, global or quasi-optimum solution can be found. We validate the proposed DDE by applying it to several benchmark problems.
