An improved particle swarm optimization algorithm

An improved particle swarm optimization (IPSO) is proposed in this paper. In the new algorithm, a population of points sampled randomly from the feasible space. Then the population is partitioned into several sub-swarms, each of which is made to evolve based on particle swarm optimization (PSO) algo...

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Bibliographic Details
Published in:Applied mathematics and computation Vol. 193; no. 1; pp. 231 - 239
Main Authors: Jiang, Yan, Hu, Tiesong, Huang, ChongChao, Wu, Xianing
Format: Journal Article
Language:English
Published: New York, NY Elsevier Inc 01.10.2007
Elsevier
Subjects:
Calculus of variations and optimal control
Exact sciences and technology
Global optimization
Hydrologic model
Improved particle swarm optimization
Mathematical analysis
Mathematics
Numerical analysis
Numerical analysis. Scientific computation
Numerical methods in mathematical programming, optimization and calculus of variations
Parameters calibration
Particle swarm optimization
Sciences and techniques of general use
Improved particle swarm optimization
Global optimization
Hydrologic model
Parameters calibration
Particle swarm optimization
Partition
Numerical analysis
Applied mathematics
Optimization method
Global optimum
Algorithm
Mathematical programming
ISSN:0096-3003, 1873-5649
Online Access:Get full text
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Summary:An improved particle swarm optimization (IPSO) is proposed in this paper. In the new algorithm, a population of points sampled randomly from the feasible space. Then the population is partitioned into several sub-swarms, each of which is made to evolve based on particle swarm optimization (PSO) algorithm. At periodic stages in the evolution, the entire population is shuffled, and then points are reassigned to sub-swarms to ensure information sharing. This method greatly elevates the ability of exploration and exploitation. Simulations for three benchmark test functions show that IPSO possesses better ability to find the global optimum than that of the standard PSO algorithm. Compared with PSO, IPSO is also applied to identify the hydrologic model. The results show that IPSO remarkably improves the calculation accuracy and is an effective global optimization to calibrate hydrologic model.
ISSN:0096-3003
1873-5649
DOI:10.1016/j.amc.2007.03.047