关键词: 二进制蛙跳算法, 认知无线电, 种群多样性, 文化倾向性

Abstract:

Binary shuffled frog leaping algorithm (BSFLA) in population diversity is proposed for a cognitive radio allocation model, which is a NP-hard problem. The integer coding manner and the searching method is applied in the shuffled frog leaping algorithm. BSFLA utilizes binary coding manner, explores application of the cultural orientation method to accomplish the searching for the optimal solution. Based on schemata theory, the population diversity is defined using hamming distance in order to judge the premature phenomenon. When the premature phenomenon appears, the population reconstruction is done under the elitist retention conditions to avoid falling into the local optimal point. To demonstrate the effectiveness of the proposed algorithm, An experiment for contrast on 100 various network topologies is done. For three fitness functions, the success rates that the proposed algorithm is superior to particle swarm optimization, genetic algorithm and quantum genetic algorithm are equal to 100%, 75% and 100% respectively.

Key words: binary shuffled frog leaping algorithm, cognitive radio, population diversity, cultural orientation