In most cases, the standard optimization algorithms are capable of identifying the required
number of parameters for a specific design problem; however, this process is difficult and …

In this article, the charged system search (CSS) optimization method is improved to identify
the parameters of a non-linear hysteretic Bouc-Wen differential model. The CSS is suitable …

In the current research, the imperialist competitive algorithm is dramatically enhanced and a
new optimization method dubbed as Enriched Imperialist Competitive Algorithm (EICA) is …

In this paper, a new hybrid algorithm based on charged system search (CSS) and colliding
bodies optimization (CBO) is proposed to identify the parameters of a highly nonlinear semi …

In this paper, a new opposition based charged system search (CSS) is proposed to be used
as a parameter identification of highly nonlinear semi-active magneto-rheological damper …

This article presents a new modified cuckoo search algorithm with dynamic discovery
probability and step-size factor for optimizing the Bouc–Wen Model in magnetorheological …

This paper presents a useful approach to optimally design magnetorheological (MR)
dampers used in structural buildings. To fulfill this aim, damper parameters are regarded as …

Many hysteresis models have been proposed for the simulation of the nonlinear behavior of
structures each of which has certain advantages depending on specific applications and …

In this article, a new two-stage hybrid optimization method based on the Particle Swarm
Optimization and the Big Bang-Big Crunch algorithm (BB-BC) is introduced for identification …

This chapter explores the use of Nelder-Mead simplex (NMS) as an accelerating operator to
improve the performance of metaheuristic algorithms, which are commonly used for solving …