PARTICLE SWARM-GROUP SEARCH ALGORITHM AND ITS APPLICATION TO SPATIAL STRUCTURAL DESIGN WITH DISCRETE VARIABLES
Authors
Abstract:
Based on introducing two optimization algorithms, group search optimization (GSO) algorithm and particle swarm optimization (PSO) algorithm, a new hybrid optimization algorithm which named particle swarm-group search optimization (PS-GSO) algorithm is presented and its application to optimal structural design is analyzed. The PS-GSO is used to investigate the spatial truss structures with discrete variables and is tested by truss optimization problems. The optimization results are compared with that of the HPSO and GSO algorithm. The results show that the PS-GSO is able to accelerate the convergence rate effectively and has the fastest convergence rate among these three algorithms. The research shows the proposed PS-GSO algorithm can be effectively applied to optimal design of spatial structures with discrete variables.
similar resources
Optimum Structural Design with Discrete Variables Using League Championship Algorithm
In this paper a league championship algorithm (LCA) is developed for structural optimization where the optimization variables are of discrete type and the set of the values possibly obtained by each variable is also given. LCA is a relatively new metaheuristic algorithm inspired from sport championship process. In LCA, each individual can choose to approach to or retreat from other individuals ...
full textA Hybrid Particle Swarm Optimization and Genetic Algorithm for Truss Structures with Discrete Variables
A new hybrid algorithm of Particle Swarm Optimization and Genetic Algorithm (PSOGA) is presented to get the optimum design of truss structures with discrete design variables. The objective function chosen in this paper is the total weight of the truss structure, which depends on upper and lower bounds in the form of stress and displacement limits. The Particle Swarm Optimization basically model...
full textHYBRID PARTICLE SWARM OPTIMIZATION, GRID SEARCH METHOD AND UNIVARIATE METHOD TO OPTIMALLY DESIGN STEEL FRAME STRUCTURES
This paper combines particle swarm optimization, grid search method and univariate method as a general optimization approach for any type of problems emphasizing on optimum design of steel frame structures. The new algorithm is denoted as the GSU-PSO. This method attempts to decrease the search space and only searches the space near the optimum point. To achieve this aim, the whole search space...
full textAN IMPROVED INTELLIGENT ALGORITHM BASED ON THE GROUP SEARCH ALGORITHM AND THE ARTIFICIAL FISH SWARM ALGORITHM
This article introduces two swarm intelligent algorithms, a group search optimizer (GSO) and an artificial fish swarm algorithm (AFSA). A single intelligent algorithm always has both merits in its specific formulation and deficiencies due to its inherent limitations. Therefore, we propose a mixture of these algorithms to create a new hybrid optimization algorithm known as the group search-artif...
full textISOGEOMETRIC STRUCTURAL SHAPE OPTIMIZATION USING PARTICLE SWARM ALGORITHM
One primary problem in shape optimization of structures is making a robust link between design model (geometric description) and analysis model. This paper investigates the potential of Isogeometric Analysis (IGA) for solving this problem. The generic framework of shape optimization of structures is presented based on Isogeometric analysis. By discretization of domain via NURBS functions, the a...
full textApplication of Particle Swarm Optimization and Genetic Algorithm Techniques to Solve Bi-level Congestion Pricing Problems
The solutions used to solve bi-level congestion pricing problems are usually based on heuristic network optimization methods which may not be able to find the best solution for these type of problems. The application of meta-heuristic methods can be seen as viable alternative solutions but so far, it has not received enough attention by researchers in this field. Therefore, the objective of thi...
full textMy Resources
Journal title
volume 2 issue 4
pages 443- 458
publication date 2012-10
By following a journal you will be notified via email when a new issue of this journal is published.
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023