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A competitive comparison of different types of evolutionary algorithms

机译:不同类型进化算法的竞争性比较

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This paper presents comparison of several stochastic optimization algorithms developed by authors in their previous works for the solution of some problems arising in civil engineering. The introduced optimization methods are: the integer augmented simulated annealing (IASA), the real-coded augmented simulated annealing (RASA) [Comp. Meth. Appl. Mech. Eng. 190 (13―14) (2000) 1629], the differential evolution (DE) in its original fashion developed by Storn and Price [R. Storn, On the usage of differential evolution for function optimization, NAPHIS, 1996] and simplified real-coded differential genetic algorithm (simplified atavistic differential evolution, SADE) [O. Hrstka, A. Kucerova, Search for optimization methods on multi-dimensional real domains, Contributions to Mechanics of Materials and Structures, CTU Reports 4, 2000, pp. 87―104]. Each of these methods was developed for some specific optimization problem; namely the Chebychev trial polynomial problem, the so called type 0 function and two engineering problems―the reinforced concrete beam layout and the periodic unit cell problem, respectively. Detailed and extensive numerical tests were performed to examine the stability and efficiency of proposed algorithms. The results of our experiments suggest that the performance and robustness of RASA, TASA and SADE methods are comparable, while the DE algorithm performs slightly worse. This fact together with a small number of internal parameters promotes the SADE method as the most robust for practical use.
机译:本文介绍了作者在以前的工作中为解决土木工程中出现的一些问题而开发的几种随机优化算法的比较。引入的优化方法是:整数增强模拟退火(IASA),实编码增强模拟退火(RASA)[Comp。方法应用机甲。 190(13-14)(2000)1629],由Storn和Price [R. Storn,关于使用差分进化进行功能优化,NAPHIS,1996年]和简化的实编码差分遗传算法(简化的Atavistic差分进化,SADE)[O。 Hrstka,A. Kucerova,在多维实域上寻找优化方法,《对材料和结构力学的贡献》,CTU报告4,2000,第87-104页。这些方法中的每一种都是针对特定的优化问题而开发的。分别是Chebychev试验多项式问题,所谓的0型函数和两个工程问题-分别是钢筋混凝土梁的布置和周期单位单元的问题。进行了详细而广泛的数值测试,以检验所提出算法的稳定性和效率。我们的实验结果表明,RASA,TASA和SADE方法的性能和鲁棒性相当,而DE算法的性能稍差。这个事实以及少量的内部参数使SADE方法成为实际使用中最可靠的方法。

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