期刊
ADVANCED ENGINEERING INFORMATICS
卷 28, 期 1, 页码 81-90出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.aei.2013.12.003
关键词
Genetic algorithm; Particle swarm optimization; Simulation-based optimization; Energy system optimization; Geothermal power plant
资金
- United States Department of Defense Science, Mathematics, and Research for Transformation (SMART)
The performance of a genetic algorithm is compared with that of particle swarm optimization for the constrained, non-linear, simulation-based optimization of a double flash geothermal power plant. Particle swarm optimization converges to better (higher) objective function values. The genetic algorithm is shown to converge more quickly and more tightly, resulting in a loss of solution diversity. Particle swarm optimization obtains solutions within 0.1% and 0.5% of the best known optimum in significantly fewer objective function evaluations than the genetic algorithm. (C) 2014 Elsevier Ltd. All rights reserved.
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