Showing 2 results for Multi-Objective Optimizations
Dr V.r. Mahdavi, Prof. A. Kaveh,
Volume 14, Issue 3 (6-2024)
Abstract
In order to evaluate the damage state, value, and position of structural members more accurately, a multi-objective optimization (MO) method is utilized that is based on changes in natural frequency. The multi-objective optimization dynamic-based damage detection method is first introduced. Two objective functions for optimization are then introduced in terms of changing the natural frequencies and mode shapes. The multi-objective optimization problem (MOP) is formulated by using the two objective functions. Three considered MO algorithms consist of Colliding Bodies Optimization (MOCBO), Particle Swarm Optimization (MOPSO), and non-dominated sorting genetic algorithm (NSGA-II) to achieve the best structural damage detection. The proposed methods are then applied to three planar steel frame structures. Compared to the traditional optimization methods utilizing the single-objective optimization (SO) algorithms, the presented methods provide superior results.
V. R. Mahdavi, A. Kaveh,
Volume 16, Issue 3 (7-2026)
Abstract
This paper uses multi-objective methods to improve the exploration for single-objective problems. This method involved splitting the objective function into two segments and these enhanced using specialized algorithms designed for handling multiple objective functions. Three MO algorithms include Colliding Bodies Optimization (MOCBO), Particle Swarm Optimization (MOPSO), and non-dominated sorting genetic algorithm (NSGA-II), which are used to get the best prediction of structural modal strain energy. The indicated method is then implemented to two spatial truss structures. The recently developed method has superior performance over the previous approach that relied on single-objective optimization (SO) algorithms.
