Optimization of the Hydrological Model Using Multi-objective Particle Swarm Optimization Algorithm
- Resource Type
- Academic Journal
- Authors
- HUANG Xiao-min; LEI Xiao-hui; WANG Yu-hui; ZHU Lian-yong
- Source
- 东华大学学报(英文版) / Journal of Donghua University(English Edition). 28(5):519-522
- Subject
- multi-objective particle swarm optimization (MOPSO)
hydrological model (HYMOD)
multi-obiective optimization
- Language
- Chinese
- ISSN
- 1672-5220
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 NashSutcliffe 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.