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- Title
Optimization of the Hydrological Model Using Multi-objective Particle Swarm Optimization Algorithm.
- Authors
Huang Xiao-Min; Lei Xiao-Hui; Wang Yu-Hui; Zhu Lian-Yong
- Abstract
An application of multi-objective particle swarm optimization (MOPSO) algorithm for optimization of the hydrological model (HYMOD) is presented in this paper. MOPSO algorithm is used to find non-dominated solutions with two objectives: high flow Nash-Sutcliffe efficiency and low flow Nash- Sutcliffe efficiency. The two sets' coverage rate and Pareto front spacing metric are two criterions to analyze the performance of the algorithms. MOPSO algorithm surpasses multi-objective shuffled complex evolution metropolis (MOSCEM_UA) algorithm in terms of the two sets' coverage rate. But when we come to Pareto front spacing rate, the non-dominated solutions of MOSCEM_ UA algorithm are better-distributed than that of MOPSO algorithm when the iteration is set to 40 000. In addition, there are obvious conflicts between the two objectives. But a compromise solution can be acquired by adopting the MOPSO algorithm.
- Subjects
PARTICLE swarm optimization; COMPUTER algorithms; SWARM intelligence; MATHEMATICAL optimization; ALGORITHMS
- Publication
Journal of Donghua University (English Edition), 2011, Vol 28, Issue 5, p519
- ISSN
1672-5220
- Publication type
Article