New few parameters differential evolution algorithm with application to structural identification

作     者：Rita Greco Ivo Vanzi 

作者机构：Department of Civil Engineering Environmental Territory Building and Chemical Polytechnic University of Bari Department of Engineering and Geology University of Chieti-Pescara "G.d'Annunzio" 

出 版 物：《Journal of Traffic and Transportation Engineering(English Edition)》 (交通运输工程学报（英文版）)

年 卷 期：2019年第6卷第1期

页      面：1-14页

核心收录：

学科分类：08[工学] 081402[工学-结构工程] 081304[工学-建筑技术科学] 0813[工学-建筑学] 0814[工学-土木工程] 

基　　金：the research project "OptArch-689983 H2020-MSCA-RISE-2015/H2020-MSCA-RISE-20" 

主　　题：Differential evolution Parametric identification Structural identification Optimization 

摘      要：Differential evolution algorithm(DEA) is a stochastic, population-based global optimization method. In this paper, we propose new schemes for both mutation and crossover operators in order to enhance the performances of the standard DEA. The advantage of these proposed operators is that they are parameters-less, without a tuning phase of algorithm parameters that is often a disadvantage of DEA. Once the modified differential evolutions are presented, a large comparative analysis is performed with the aim to assess both correctness and efficiency of the proposed operators. Advantages of proposed DEA are used in an important task of modern structural engineering that is mechanical identification under external dynamic loads. This is because of the importance of using a parametersless algorithm in identification problems whose characteristics typically vary strongly case by case, needing of a continuous set up of the algorithm proposed. This important advantage of proposed optimizers, in front of other identification algorithms, is used to develop a computer code suitable for the automatic identification of a simple supported beam subject to an impact load, that has been tested both using numerical simulations and real standard tests dynamic. The results point out that this algorithm is an interesting candidate for standard applications in structural identification problems.