一种基于遗传优化的路由控制策略

遗传算法是通过模拟自然进化过程有效解决最优化问题的计算模型,在实际操作中得到广泛应用.但由于遗传算法的选择策略使每一代的优良个体大量的遗传到下一代,且适应度函数设定的差异,使最优个体很快充斥整个群体,缺少物种多样性,导致算法很快收敛于局部最优解,达不到全局优化.针对遗传算法存在的这一问题,结合禁忌搜索算法能够禁忌搜寻过的最优解而引入裂解、增加种群多样性的特性,提出了一种基于遗传优化的路由控制策略.该策略将遗传算法得到的最优解作为禁忌搜索的初始解,提出将染色体模版作为禁忌对象,并以此模版为基础建立邻域的方案.仿真实验表明,该策略能够有效的抑制遗传算法过早收敛的问题,减少了全局能量的消耗,从而延长了网络生命周期.

A routing control strategy based on genetic optimization

The genetic algorithm is a computational model which is used to solve the optimization problem by simulating the natural evolution process; it has been widely used in practical operation. The optimal individual will soon flood the entire group, lacking of species diversity, thus leading the algorithm quickly converges to local optimal solution. It is because each generation of excellent individual substantial genetic to the next generation due to the selection strategies of genetic algorithm and the different functions. In order to solve this problem and in considering the characteristic that tabu search algorithm can taboos the best solution which have been searched and introduce bad solutions which can increase the diversity of population that this characteristic makes searching job traversal of all states, then reaching the global optimum, this paper proposes a routing control strategy that combined with tabu search algorithm based on the genetic algorithm. The optimal strategy obtained by genetic algorithm solution is used as the initial solution of the proposed tabu search algorithm and the chromosome template is used as taboo object. Also, the template is a base for the establishment of neighborhood. Simulation results show that this strategy can restrain premature convergence of genetic algorithms and to find a better solution.