Structural shape optimization of free-form surface shell and property of solution search using firefly algorithm
Structural shape optimization of free-form surface shell and property of solution search using firefly algorithm
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DOI：
10.1007/s12206-015-0317-5
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发表时间：
2015-04
影响因子：
1.6
通讯作者：
Natsuki Tanaka;T. Honma;Yohei Yokosuka
中科院分区：
文献类型：
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作者：
Natsuki Tanaka;T. Honma;Yohei Yokosuka
结构形状优化的计算过程基于启发式优化过程，如群体智能（SI），它使用在自然界观察到的自组织现象中发现的模式。包括粒子群优化（PSO）和人工蜂群优化（ABC）在内的大多数SI技术都能获得全局最优解。萤火虫算法通过设置合适的计算参数，既能得到全局最优解，又能得到局部最优解。但是，设置这些参数的方法比较困难。为了简化这些参数的设置，我们实现了一种设计变量空间中两只萤火虫之间的距离是无因次的计算方案。给出了自由曲面壳结构形状优化中全局最优解的多元解和局部最优解的局部搜索，说明了该算法的有效性和有效性。
The computation procedure for structural shape optimization is based on the heuristic optimization procedures, such as swarm intelligence (SI), that use patterns found in self-organizing phenomena observed in nature. Most SI techniques including particle swarm optimization (PSO) and artificial bee colony (ABC), attain a global optimal solution. The firefly algorithm (FA) can attain both a global optimal and local optimal solutions by setting suitable computational parameters. However, the method for setting these parameters is comparatively difficult. In order to simplify the setting of these parameters, we implement a computational scheme where the distance between two fireflies in the design variable space is dimensionless. The effectiveness and the validity of this FA are clarified by showing the diversified solution for a global optimal solution and local optimal solutions using a local search in the structural shape optimization of a free-form surface shell.