遗传模拟退火算法在无线网络规划中的应用

Application of genetic simulated annealing algorithm to wireless network planning

提出用遗传模拟退火算法,解决无线网络规划中的基站选址问题.实现了用最少的基站数量,达到最大覆盖的优化目标.对交叉算子进行改进,实施最优保留策略,加快了算法的收敛,并避免了早熟.仿真结果表明,遗传模拟退火算法运行结果的覆盖率为95.64%,目标函数值为0.8706;与遗传算法相比,该算法收敛的最优解适值较大,收敛速度较快,能找到符合无线网络建设要求的基站分布方案.

This paper proposes applying genetic simulated annealing algorithm to wireless network planning.The simulation has achieved the optimized goal of using the fewest base stations to provide the most coverage.Moreover,the crosser were improved,and the optimization reserved strategy was used to accelerate the convergence without leading to premature.The result of GSA achieves the coverage of 95.64 percent and the fitness function value is 0.870 6.Compared with GA,GSA converges more rapidly to the bigger fitness function value,and is capable of obtaining the base-station placement which accords with mobile network construction requirement.