Parallel Hybrid Island Metaheuristic Algorithm
This study introduces a novel Parallel Hybrid Island architecture which shows a parallel way to combine different meta-heuristic algorithms by using the island model as the base. The corresponding hybrid algorithm is called Parallel Hybrid Island Metaheuristic Algorithms (PHIMA). The hybrid parallel...
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9751690/ |
| _version_ | 1811302916923850752 |
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| author | Jiawei Li Tad Gonsalves |
| author_facet | Jiawei Li Tad Gonsalves |
| author_sort | Jiawei Li |
| collection | DOAJ |
| description | This study introduces a novel Parallel Hybrid Island architecture which shows a parallel way to combine different meta-heuristic algorithms by using the island model as the base. The corresponding hybrid algorithm is called Parallel Hybrid Island Metaheuristic Algorithms (PHIMA). The hybrid parallel structure exploits the characteristics of the individual metaheuristic algorithms to boost robustness and diversity. Island Genetic Algorithm has been combined with Particle Swarm Optimization and Fireworks Algorithm to build three different PHIMA algorithms: PSO-GA (PHIMA-PGA), FWA-GA (PHIMA-FGA) and FWA-PSO-GA (PHIMA-FPGA). Further, another implementational variation known as “co-evolution” is applied to the sub-GA islands of PHIMA-FPGA to improve the performance on multi-modal high-dimensional problems. This variation is referred to as PHIMA-FPGA-Co. Each PHIMA Algorithm exhibits different advantages and characteristics, and the parallel hybridization using the island model is found to improve robustness and population diversity. The performances of the four new algorithms are compared with each other and that of the traditional Island GAs and all four proposed PHIMA algorithms show better result quality. |
| first_indexed | 2024-04-13T07:37:51Z |
| format | Article |
| id | doaj.art-5b483f9277cc41b78ccafff3f0e8bf0f |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-13T07:37:51Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-5b483f9277cc41b78ccafff3f0e8bf0f2022-12-22T02:56:03ZengIEEEIEEE Access2169-35362022-01-0110422684228610.1109/ACCESS.2022.31658309751690Parallel Hybrid Island Metaheuristic AlgorithmJiawei Li0Tad Gonsalves1https://orcid.org/0000-0001-9424-3078Department of Information and Communication Sciences, Faculty of Science and Technology, Sophia University, Tokyo, JapanDepartment of Information and Communication Sciences, Faculty of Science and Technology, Sophia University, Tokyo, JapanThis study introduces a novel Parallel Hybrid Island architecture which shows a parallel way to combine different meta-heuristic algorithms by using the island model as the base. The corresponding hybrid algorithm is called Parallel Hybrid Island Metaheuristic Algorithms (PHIMA). The hybrid parallel structure exploits the characteristics of the individual metaheuristic algorithms to boost robustness and diversity. Island Genetic Algorithm has been combined with Particle Swarm Optimization and Fireworks Algorithm to build three different PHIMA algorithms: PSO-GA (PHIMA-PGA), FWA-GA (PHIMA-FGA) and FWA-PSO-GA (PHIMA-FPGA). Further, another implementational variation known as “co-evolution” is applied to the sub-GA islands of PHIMA-FPGA to improve the performance on multi-modal high-dimensional problems. This variation is referred to as PHIMA-FPGA-Co. Each PHIMA Algorithm exhibits different advantages and characteristics, and the parallel hybridization using the island model is found to improve robustness and population diversity. The performances of the four new algorithms are compared with each other and that of the traditional Island GAs and all four proposed PHIMA algorithms show better result quality.https://ieeexplore.ieee.org/document/9751690/Meta-heuristic algorithmshybrid algorithmsoptimizationgenetic algorithmparticle swarm algorithmfireworks algorithm |
| spellingShingle | Jiawei Li Tad Gonsalves Parallel Hybrid Island Metaheuristic Algorithm IEEE Access Meta-heuristic algorithms hybrid algorithms optimization genetic algorithm particle swarm algorithm fireworks algorithm |
| title | Parallel Hybrid Island Metaheuristic Algorithm |
| title_full | Parallel Hybrid Island Metaheuristic Algorithm |
| title_fullStr | Parallel Hybrid Island Metaheuristic Algorithm |
| title_full_unstemmed | Parallel Hybrid Island Metaheuristic Algorithm |
| title_short | Parallel Hybrid Island Metaheuristic Algorithm |
| title_sort | parallel hybrid island metaheuristic algorithm |
| topic | Meta-heuristic algorithms hybrid algorithms optimization genetic algorithm particle swarm algorithm fireworks algorithm |
| url | https://ieeexplore.ieee.org/document/9751690/ |
| work_keys_str_mv | AT jiaweili parallelhybridislandmetaheuristicalgorithm AT tadgonsalves parallelhybridislandmetaheuristicalgorithm |