Accelerated Particle Swarm for Optimum Design of Frame Structures-Reference-Cited by-同舟云学术

Accelerated Particle Swarm for Optimum Design of Frame Structures

Published:2013 Issue: Volume:2013 Page:1-6
ISSN:1024-123X
Container-title:Mathematical Problems in Engineering
language:en
Short-container-title:Mathematical Problems in Engineering

Author:

Talatahari S.¹,Khalili E.²,Alavizadeh S. M.³

Affiliation:

1. Marand Faculty of Engineering, University of Tabriz, Tabriz 51666-14766, Iran

2. Department of Engineering, Islamic Azad University, Ahar Branch, Ahar 54516, Iran

3. Department of Structural Engineering, Islamic Azad University, Shabestar Branch, Shabestar 57168-14758, Iran

Abstract

Accelerated particle swarm optimization (APSO) is developed for finding optimum design of frame structures. APSO shows some extra advantages in convergence for global search. The modifications on standard PSO effectively accelerate the convergence rate of the algorithm and improve the performance of the algorithm in finding better optimum solutions. The performance of the APSO algorithm is also validated by solving two frame structure problems.

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

Link

http://downloads.hindawi.com/journals/mpe/2013/649857.pdf

Reference29 articles.

1. Optimal design of skeletal structures via the charged system search algorithm

2. Ant Colony Optimization for Design of Space Trusses

3. A multi-stage particle swarm for optimum design of truss structures

4. Key Issues in Modeling of Complex 3D Structures from Video Sequences

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Metaheuristic optimization algorithms for real-world electrical and civil engineering application: A review;Results in Engineering;2024-09

2. The Parameter Identification of Structure with TMD considering Seismic Soil‐Structure Interaction;Structural Control and Health Monitoring;2024-01

3. Research on section dimension optimization of high-rise steel–concrete composite buildings based on improved dividing rectangle algorithm and combined response surface model;Structures;2023-12

4. Data-driven ensemble learning approach for optimal design of cantilever soldier pile retaining walls;Structures;2023-05

5. Accelerated Particle Swarm Optimization Algorithms Coupled with Analysis of Variance for Intelligent Charging of Plug-in Hybrid Electric Vehicles;Energies;2023-04-02