  A boundary evolution Algorithm (BEA) is proposed by simultaneously taking
into account the bottom and the high-level crossover and mutation, ie., the
boundary of the hierarchical genetic algorithm. Operators and optimal
individuals based on optional annealing are designed. Based on the numerous
versions of genetic algorithm, the boundary evolution approach with crossover
and mutation has been tested on the SAT problem and compared with two competing
methods: a traditional genetic algorithm and another traditional hierarchical
genetic algorithm, and among some others. The results of the comparative
experiments in solving SAT problem have proved that the new hierarchical
genetic algorithm based on simulated annealing and optimal individuals (BEA)
can improve the success rate and convergence speed considerably for SAT problem
due to its avoidance of both divergence and loss of optimal individuals, and by
coronary, conducive to NP problem. Though more extensive comparisons are to be
made on more algorithms, the consideration of the boundary elasticity of
hierarchical genetic algorithm is an implication of evolutionary algorithm.
