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DSLC-FOA : Improved fruit fly optimization algorithm for application to structural engineering design optimization problems

机译:DSLC-FOA:改进的果蝇优化算法,用于结构工程设计优化问题

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HighlightsA new algorithm named DSLC-FOA is developed.The novel algorithm is tested on four different well-known benchmark problems.It is compared with the GA, PSO, FOA, LGMS-FOA, and CFOA algorithms.Experiments show the superiority of the DSLC-FOA in terms of obtained statistical results.AbstractIn this study, we propose an improved fruit fly optimization algorithm (FOA) based on linear diminishing step and logistic chaos mapping (named DSLC-FOA) for solving benchmark function unconstrained optimization problems and constrained structural engineering design optimization problems. Based on comparisons with genetic algorithm, particle swarm optimization, FOA, LGMS -FOA, and chaotic FOA methods, we demonstrated that DSLC-FOA performed better at searching for the optimal solutions of four typical benchmark functions. The approximate optimal results were obtained using DSLC-FOA for three structural engineering design optimization problems as examples of applications. The numerical results demonstrated that the proposed DSLC-FOA algorithm is superior to the basic FOA and other metaheuristic or deterministic methods.
机译: 突出显示 开发了一种名为DSLC-FOA的新算法。 该新颖算法已针对四个不同的著名基准问题进行了测试。 < / ce:list-item> 与GA,PSO,FOA,LGMS-FOA和CFOA算法。 实验证明了DSLC-F的优越性就获得的统计结果而言,OA。 摘要 在这项研究中,我们提出了一种改进的果蝇优化算法(FOA),该算法基于线性递减步长和逻辑混乱映射(名为DSLC-FOA)来无约束地求解基准函数优化问题和受约束的结构工程设计优化问题。在与遗传算法,粒子群优化,FOA,LGMS -FOA和混沌FOA方法进行比较的基础上,我们证明了DSLC-FOA在搜索四个典型基准函数的最优解方面表现更好。对于三个结构工程设计优化问题,使用DSLC-FOA作为应用实例,可获得近似最佳结果。数值结果表明,所提出的DSLC-FOA算法优于基本的FOA算法和其他元启发式或确定性方法。

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