Regular expression grouping optimization based on shuffled frog leaping algorithm
Liangwei Cai, Yi Haoping · 2016
An optimization method based on improved shuffled frog leaping algorithm (ISFLA) is proposed to solve pattern matching problem of regular expression grouping. The algorithm uses improved individual renewal formula and introduces population update strategy to optimize regular expression grouping combining with Becchi algorithm. It is shown by the experimental results that the proposed algorithm can search for better solution in a global scope, decrease the number of state effectively, diminish the complexity of pattern matching and has a higher search and optimize capability.