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Parallel Hybrid Island Metaheuristic Algorithm
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DOI：10.1109/ACCESS.2022.3165830.png)
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摘要
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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.
Keyword:
Sparks
Genetic algorithms
Metaheuristics
Statistics
Sociology
Explosions
Heuristic algorithms
Meta-heuristic algorithms
hybrid algorithms
optimization
genetic algorithm
particle swarm algorithm
fireworks algorithm
co-evolution
island model
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
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