Grey wolf optimizer for parameter identification of an activated sludge process model

This paper considers a new meta-heuristic method called Grey Wolf optimizer (GWO). It is inspired by the behavior of grey wolves (Canis lupus) in nature, especially the leadership hierarchy and the hunting mechanism of a pack. This recent optimization method presents an interesting case of study giv...

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Published in:Soft computing (Berlin, Germany) Germany), 2023-10, Vol.27 (20), p.15293-15304
Main Authors: Khoja, Intissar, Majdoub, Nesrine, Ladhari, Taoufik, M’Sahli, Faouzi, Sakly, Anis
Format: Article
Language:English
Subjects:
Activated sludge process
Algorithms
Application of Soft Computing
Artificial Intelligence
Computational Intelligence
Control
Engineering
Genetic algorithms
Heuristic methods
Hunting
Leadership
Mathematical Logic and Foundations
Mathematical models
Mechatronics
Optimization techniques
Parameter estimation
Parameter identification
Particle swarm optimization
Robotics
Search algorithms
Sludge
Social structure
Wastewater treatment
Wolves
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Summary:This paper considers a new meta-heuristic method called Grey Wolf optimizer (GWO). It is inspired by the behavior of grey wolves (Canis lupus) in nature, especially the leadership hierarchy and the hunting mechanism of a pack. This recent optimization method presents an interesting case of study given its promising performance in a variety of engineering fields. We are mainly focusing on the parameter identification problem given its crucial role in systems modeling and control. For this reason, the GWO is investigated to solve this kind of problem for an activated sludge process model used in wastewater treatment. The considered model is a nonlinear hybrid one. It has four unknown parameters to be identified. Simulation results are carried out and compared to other techniques: classical (Nelder–Mead method) and intelligent ones (Genetic Algorithm, Particle Swarm Optimization, Fireflies Algorithm, Cuckoo Search, and Teaching–Learning Based Optimization). The outcome of this comparison shows the satisfactory effectiveness and simplicity of the proposed method versus the others approaches.
ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-023-07952-0