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为求解频率分配问题提出一种改进人工蜂群算法。该算法保持人工蜂群算法原有搜索流程,引入蝙蝠算法回声定位的机制,令蜜蜂拥有蝙蝠的能力,在搜索过程中调节响度和频率逐渐接近目标,以提高频率分配过程中的局部搜索精度和效率。算法利用自然选择阈值来降低搜索过程中对当前全局最优解的依赖,以提高种群多样性,降低陷入局部最优解的可能性。经固定频率分配问题的仿真实验和与其他算法对比结果表明,本文算法不仅具有较快的全局收敛速度,而且有高质量的解和高的效率。
To solve the problem of frequency allocation, an improved artificial bee colony algorithm is proposed. The algorithm preserves the original searching process of artificial bee colony algorithm and introduces the echolocation mechanism of bat algorithm so that the bees possess the ability of bats to adjust the loudness and frequency in the search process to gradually approach the target so as to improve the local search precision in the frequency allocation process and effectiveness. The algorithm uses the natural selection threshold to reduce the dependence on the current global optimal solution in the search process to improve the population diversity and reduce the possibility of falling into the local optimal solution. The simulation experiment on the problem of fixed frequency assignment and the comparison with other algorithms show that the proposed algorithm not only has faster global convergence speed but also has high quality solution and high efficiency.