Abstract: This paper advances a heuristic algorithm UGA （Uniform Genetic Algorithm） for solving the problem of dynamic overlay, in accordance with the problem of dynamic coverage transformed into the problem of multi-objective optimization. The algorithm defines the multi-objective optimization problem, and then in order to ensure the diversity of the optimal solution, the algorithm proposes a uniform solution strategy （Solution Even Tactics, SET） for updating the fitness of Pareto optimal solution. Experimental results show that, in a different network size and number of iterations, the regional coverage and network lifetime have better improvement compared to traditional classical algorithm.

Key words: dynamic overlay, multi-objective optimization, genetic algorithm, Pareto optimal solution

摘要： 针对[WSN]动态覆盖问题可以转化为多目标优化问题，提出一种解决动态覆盖问题的启发式算法UGA（Uniform Genetic Algorithm）。该算法定义出多目标优化问题，为了保证最优解的多样性，提出一种解均匀策略（Solution Even Tactics，SET）进行[Pareto]最优解适应度更新。实验结果表明，在不同网络规模和迭代次数下，区域覆盖度和网络寿命相对于传统经典算法有较好改进。

关键词: 动态覆盖, 多目标优化, 遗传算法, Pareto最优解