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An improved GA and a novel PSO-GA-based hybrid algorithm |
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| Authors: | XH Shi HP Lee LM Wang |
| Affiliation: | a College of Computer Science and Technology, Jilin University, Changchun 130012, China b Institute of High Performance Computing, Singapore 117528, Singapore c Department of Computer Science and Technology, Changchun Taxation College, Changchun 130021, China |
| Abstract: | Inspired by the natural features of the variable size of the population, we present a variable population-size genetic algorithm (VPGA) by introducing the “dying probability” for the individuals and the “war/disease process” for the population. Based on the VPGA and the particle swarm optimization (PSO) algorithms, a novel PSO-GA-based hybrid algorithm (PGHA) is also proposed in this paper. Simulation results show that both VPGA and PGHA are effective for the optimization problems. |
| Keywords: | Algorithms Genetic algorithms Particle swarm optimization Hybrid evolutionary algorithms Optimization |
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