Proposal of a novel particle swarm optimization for constrained optimization problems (1st report: Basic study with benchmark problems)
There are many requirements, issues and complexities that engineering design problems must take into account, and these engineering items are often treated as constraints in optimization problems. The constraint optimization problems (COPs) are the most popular type of problems, therefore, optimizat...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | Japanese |
| Published: |
The Japan Society of Mechanical Engineers
2025-04-01
|
| Series: | Nihon Kikai Gakkai ronbunshu |
| Subjects: | |
| Online Access: | https://www.jstage.jst.go.jp/article/transjsme/91/945/91_24-00262/_pdf/-char/en |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849731846309412864 |
|---|---|
| author | So FUKUHARA Nobuhisa KATSUMATA Masao ARAKAWA |
| author_facet | So FUKUHARA Nobuhisa KATSUMATA Masao ARAKAWA |
| author_sort | So FUKUHARA |
| collection | DOAJ |
| description | There are many requirements, issues and complexities that engineering design problems must take into account, and these engineering items are often treated as constraints in optimization problems. The constraint optimization problems (COPs) are the most popular type of problems, therefore, optimization algorithms for the COPs have been attracted more and more attention. Particle swarm optimization is one of the most popular algorithms for solving the COPs due to the simplicity and efficient convergence performance, and various types of PSO are actively developed in recent years. However, despite the popularity, they still have limitations in terms of search efficiency. Notably, it takes a lot of calculation costs to obtain the optimal solution on the boundary of constraints or the complicated feasible area. To overcome the difficulties, this paper presents a novel particle swarm optimization algorithm named independent 2-group particle swarm optimization (I2GPSO). I2GPSO is based on the following ideas - a constraint handling method, a novel structure of particles and a novel local search operator. The constraint handling method uses the existing penalty function method. The structure of particles defines two particle groups that have original roles, efficiently enabling PSO to search globally and locally. The local search operator is introduced into one group and enables particles to search near the boundary of constraints efficiently or candidates of the optimal solution. These novel approaches effectively reinforce the optimization efficiency of the PSO algorithm. The optimization capability and character of I2GPSO is illustrated in 11 benchmark problems. The results are compared with other state-of-the-art PSOs, and it is shown that the proposed algorithm possesses competitive search efficiency. |
| format | Article |
| id | doaj-art-1954fe4811324f87bee906ffeb9b97c6 |
| institution | DOAJ |
| issn | 2187-9761 |
| language | Japanese |
| publishDate | 2025-04-01 |
| publisher | The Japan Society of Mechanical Engineers |
| record_format | Article |
| series | Nihon Kikai Gakkai ronbunshu |
| spelling | doaj-art-1954fe4811324f87bee906ffeb9b97c62025-08-20T03:08:25ZjpnThe Japan Society of Mechanical EngineersNihon Kikai Gakkai ronbunshu2187-97612025-04-019194524-0026224-0026210.1299/transjsme.24-00262transjsmeProposal of a novel particle swarm optimization for constrained optimization problems (1st report: Basic study with benchmark problems)So FUKUHARA0Nobuhisa KATSUMATA1Masao ARAKAWA2Graduate School of Science for Creative Emergence, Kagawa UniversityGraduate School of Science for Creative Emergence, Kagawa UniversityGuraduate School of Information, Production and Systems, Waseda UniversityThere are many requirements, issues and complexities that engineering design problems must take into account, and these engineering items are often treated as constraints in optimization problems. The constraint optimization problems (COPs) are the most popular type of problems, therefore, optimization algorithms for the COPs have been attracted more and more attention. Particle swarm optimization is one of the most popular algorithms for solving the COPs due to the simplicity and efficient convergence performance, and various types of PSO are actively developed in recent years. However, despite the popularity, they still have limitations in terms of search efficiency. Notably, it takes a lot of calculation costs to obtain the optimal solution on the boundary of constraints or the complicated feasible area. To overcome the difficulties, this paper presents a novel particle swarm optimization algorithm named independent 2-group particle swarm optimization (I2GPSO). I2GPSO is based on the following ideas - a constraint handling method, a novel structure of particles and a novel local search operator. The constraint handling method uses the existing penalty function method. The structure of particles defines two particle groups that have original roles, efficiently enabling PSO to search globally and locally. The local search operator is introduced into one group and enables particles to search near the boundary of constraints efficiently or candidates of the optimal solution. These novel approaches effectively reinforce the optimization efficiency of the PSO algorithm. The optimization capability and character of I2GPSO is illustrated in 11 benchmark problems. The results are compared with other state-of-the-art PSOs, and it is shown that the proposed algorithm possesses competitive search efficiency.https://www.jstage.jst.go.jp/article/transjsme/91/945/91_24-00262/_pdf/-char/enparticle swarm optimizationswarm inteligencemetaheuristicconstrained optimization problemsengineering design problems |
| spellingShingle | So FUKUHARA Nobuhisa KATSUMATA Masao ARAKAWA Proposal of a novel particle swarm optimization for constrained optimization problems (1st report: Basic study with benchmark problems) Nihon Kikai Gakkai ronbunshu particle swarm optimization swarm inteligence metaheuristic constrained optimization problems engineering design problems |
| title | Proposal of a novel particle swarm optimization for constrained optimization problems (1st report: Basic study with benchmark problems) |
| title_full | Proposal of a novel particle swarm optimization for constrained optimization problems (1st report: Basic study with benchmark problems) |
| title_fullStr | Proposal of a novel particle swarm optimization for constrained optimization problems (1st report: Basic study with benchmark problems) |
| title_full_unstemmed | Proposal of a novel particle swarm optimization for constrained optimization problems (1st report: Basic study with benchmark problems) |
| title_short | Proposal of a novel particle swarm optimization for constrained optimization problems (1st report: Basic study with benchmark problems) |
| title_sort | proposal of a novel particle swarm optimization for constrained optimization problems 1st report basic study with benchmark problems |
| topic | particle swarm optimization swarm inteligence metaheuristic constrained optimization problems engineering design problems |
| url | https://www.jstage.jst.go.jp/article/transjsme/91/945/91_24-00262/_pdf/-char/en |
| work_keys_str_mv | AT sofukuhara proposalofanovelparticleswarmoptimizationforconstrainedoptimizationproblems1streportbasicstudywithbenchmarkproblems AT nobuhisakatsumata proposalofanovelparticleswarmoptimizationforconstrainedoptimizationproblems1streportbasicstudywithbenchmarkproblems AT masaoarakawa proposalofanovelparticleswarmoptimizationforconstrainedoptimizationproblems1streportbasicstudywithbenchmarkproblems |