Hybrid method for global optimization using more accuracy interval computation

【摘要】 In this paper,a novel hybrid method is presented for finding global optimization of an objective function.Based on the interval computation,this hybrid method combines interval deterministic method and stochastic evolution method.It can find global optimization quickly while ensuring the deterministic and stability of the algorithm.When using interval computation,extra width constraints accuracy of interval computation results.In this paper,a splitting method to reduce the extra width is introduced.This method is easy and it can get a more precise interval computation result.When finding the global optimization,it can increase the efficiency of pruning.Several experiments are given to illustrate the advantage of the new hybrid method.更多还原

【Abstract】 In this paper,a novel hybrid method is presented for finding global optimization of an objective function.Based on the interval computation,this hybrid method combines interval deterministic method and stochastic evolution method.It can find global optimization quickly while ensuring the deterministic and stability of the algorithm.When using interval computation,extra width constraints accuracy of interval computation results.In this paper,a splitting method to reduce the extra width is introduced.This method is easy and it can get a more precise interval computation result.When finding the global optimization,it can increase the efficiency of pruning.Several experiments are given to illustrate the advantage of the new hybrid method.更多还原