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通过分析生物在觅食行为中选择资源斑块的理想自由分布模型,提出1种模拟生物理想自由分布模型的萤火虫算法(IFDGSO)。该算法将萤火虫群中几个不重叠的个体最优位置的适应度视为资源斑块的食物数量,根据理想自由分布模型随机分配相应数量的萤火虫到每个资源斑块中,间隔一定的迭代次数,将各资源斑块的萤火虫重新组合,并重新随机分配。标准测试函数的仿真结果表明,改进后的IFDGSO算法比基本GSO算法有更优的性能。将IFDGSO算法用于解决伸缩绳设计和焊接条设计这2个典型的工程约束优化问题,结果表明,该方法具有收敛速度快、优化精度高、稳定性好的特点,具有较好的全局寻优能力。
By analyzing the ideal free distribution model of resource selection patches in foraging behavior, a firefly algorithm (IFDGSO) simulating the free distribution model of biological ideal was proposed. The algorithm considers the fitness of several non-overlapping individuals in the firefly group as the food quantity of the resource patches, randomly allocates a corresponding number of fireflies according to the ideal free-distribution model to each resource patch, with a certain interval of iteration The number of fireflies of various resource patches are reassembled and reassigned randomly. The simulation results of the standard test function show that the improved IFDGSO algorithm has better performance than the basic GSO algorithm. The IFDGSO algorithm is used to solve the two typical engineering constraint optimization problems of telescopic rope design and welding bar design. The results show that this method has the characteristics of fast convergence, high precision and good stability, and has better global optimization ability.