A. Kaveh, A. Zolghadr,
Volume 2, Issue 3 (7-2012)
Abstract
It is well known that damaged structural members may alter the behavior of the structures considerably. Careful observation of these changes has often been viewed as a means to identify and assess the location and severity of damages in structures. Among the responses of a structure, natural frequencies are both relatively easy to obtain and independent from external excitation, and therefore, could be used as a measure of the structure's behavior before and after an extreme event which might have lead to damage in the structure. Inverse problem of detection and assessment of structural damage using the changes in natural frequencies is addressed in this paper. This can be considered as an optimization problem with the location and severity of the damages being its variables. The objective is to set these variables such that the natural frequencies of the finite element model correspond to the experimentally measured frequencies of the actual damaged structure. In practice, although the exact number of damaged elements is unknown, it is usually believed to be small compared to the total number of elements of the structure. In beams and frames particularly, the necessity to divide the structural members into smaller ones in order to detect the location of the cracks more accurately, deepens this difference. This can significantly improve the performance of the optimization algorithms in solving the inverse problem of damage detection. In this paper, the Charged System Search algorithm developed by Kaveh and Talatahari [1] is improved to comprise the above mentioned point. The performance of the improved algorithm is then compared to the standard one in order to emphasize the efficiency of the proposed algorithm in damage detection inverse problems.
A. Kaveh, A. Zolghadr,
Volume 6, Issue 4 (10-2016)
Abstract
This paper presents a novel population-based meta-heuristic algorithm inspired by the game of tug of war. Utilizing a sport metaphor the algorithm, denoted as Tug of War Optimization (TWO), considers each candidate solution as a team participating in a series of rope pulling competitions. The teams exert pulling forces on each other based on the quality of the solutions they represent. The competing teams move to their new positions according to Newtonian laws of mechanics. Unlike many other meta-heuristic methods, the algorithm is formulated in such a way that considers the qualities of both of the interacting solutions. TWO is applicable to global optimization of discontinuous, multimodal, non-smooth, and non-convex functions. Viability of the proposed method is examined using some benchmark mathematical functions and engineering design problems. The numerical results indicate the efficiency of the proposed algorithm compared to some other methods available in literature.
S. A. Hosseini, A. Zolghadr,
Volume 7, Issue 4 (10-2017)
Abstract
Offshore jacket-type towers are steel structures designed and constructed in marine environments for various purposes such as oil exploration and exploitation units, oceanographic research, and undersea testing. In this paper a newly developed meta-heuristic algorithm, namely Cyclical Parthenogenesis Algorithm (CPA), is utilized for sizing optimization of a jacket-type offshore structure. The algorithm is based on some key aspects of the lives of aphids as one of the highly successful organisms, especially their ability to reproduce with and without mating. The optimal design procedure aims to obtain a minimum weight jacket-type structure subjected to API-RP 2A-WSD specifications. SAP2000 and its Open Application Programming Interface (OAPI) feature are utilized to model the jacket-type structure and the corresponding loading. The results of the optimization process are then compared with those of Particle Swarm Optimization (PSO) and its democratic version (DPSO).
