Volume 13, Issue 1 (1-2023)
IJOCE 2023, 13(1): 127-142 |
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Paknahad M, Hosseini P, Kaveh A. A SELF-ADAPTIVE ENHANCED VIBRATING PARTICLE SYSTEM ALGORITHM FOR CONTINUOUS OPTIMIZATION PROBLEMS. IJOCE 2023; 13 (1) :127-142
URL: http://ijoce.iust.ac.ir/article-1-545-en.html
URL: http://ijoce.iust.ac.ir/article-1-545-en.html
1- Faculty of Engineering, Mahallat Institute of Higher Education, Mahallat, Iran
2- School of Civil Engineering, Iran University of Science and Technology, Narmak, Tehran, Iran
2- School of Civil Engineering, Iran University of Science and Technology, Narmak, Tehran, Iran
Abstract: (7991 Views)
Optimization methods are essential in today's world. Several types of optimization methods exist, and deterministic methods cannot solve some problems, so approximate optimization methods are used. The use of approximate optimization methods is therefore widespread. One of the metaheuristic algorithms for optimization, the EVPS algorithm has been successfully applied to engineering problems, particularly structural engineering problems. As this algorithm requires experimental parameters, this research presents a method for determining these parameters for each problem and a self-adaptive algorithm called the SA-EVPS algorithm. In this study, the SA-EVPS algorithm is compared with the EVPS algorithm using the 72-bar spatial truss structure and three classical benchmarked functions
Keywords: enhanced vibrating particle system, self-adaptive algorithm, SA-EVPS algorithm, metaheuristic algorithms, continuous optimization problems
Type of Study: Research |
Subject:
Optimal design
Received: 2022/11/29 | Accepted: 2023/01/11 | Published: 2023/01/11
Received: 2022/11/29 | Accepted: 2023/01/11 | Published: 2023/01/11
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