Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Multi‐objective chaotic optimization algorithm and its application in optimal water resources deployment

View through CrossRef
PurposeTo solve the water resources deployment problem which is a multi‐objective nonlinear problem with the characteristic of space‐time variability, involving many factors, such as economy, society, ecology, environment and projects.Design/methodology/approachCoupling the characteristic of multi‐objective with chaotic optimization, a multi‐objective chaotic optimization algorithm (MCOA) is proposed for optimal water resources deployment. The algorithm magnifies the chaotic series generated by logistic mapping to the feasible region, and seeks the best results by iterative comparison which can avoid the difficulties that objective functions and the constraints should be continuous and differentiable. MCOA is a global optimization method and has high efficiency.FindingsThe proposed algorithm is applied to the optimal deployment of water resources in a certain river basin. The rationality of results is verified by the entropy change theory. The results indicate that the optimal water resources deployment can be realized using the proposed algorithm in a more rational way.Research limitations/implicationsThe numbers and the bounds of variables are the main limitations which the algorithm will be applied.Practical implicationsA very useful optimization algorithm for optimal water resources deployment.Originality/valueThe paper highlights the new optimization algorithm for optimal water resources deployment due to the MCOA.
Title: Multi‐objective chaotic optimization algorithm and its application in optimal water resources deployment
Description:
PurposeTo solve the water resources deployment problem which is a multi‐objective nonlinear problem with the characteristic of space‐time variability, involving many factors, such as economy, society, ecology, environment and projects.
Design/methodology/approachCoupling the characteristic of multi‐objective with chaotic optimization, a multi‐objective chaotic optimization algorithm (MCOA) is proposed for optimal water resources deployment.
The algorithm magnifies the chaotic series generated by logistic mapping to the feasible region, and seeks the best results by iterative comparison which can avoid the difficulties that objective functions and the constraints should be continuous and differentiable.
MCOA is a global optimization method and has high efficiency.
FindingsThe proposed algorithm is applied to the optimal deployment of water resources in a certain river basin.
The rationality of results is verified by the entropy change theory.
The results indicate that the optimal water resources deployment can be realized using the proposed algorithm in a more rational way.
Research limitations/implicationsThe numbers and the bounds of variables are the main limitations which the algorithm will be applied.
Practical implicationsA very useful optimization algorithm for optimal water resources deployment.
Originality/valueThe paper highlights the new optimization algorithm for optimal water resources deployment due to the MCOA.

Related Results

Extractraction of non-stationary harmonic from chaotic background based on synchrosqueezed wavelet transform
Extractraction of non-stationary harmonic from chaotic background based on synchrosqueezed wavelet transform
The signal detection in chaotic background has gradually become one of the research focuses in recent years. Previous research showed that the measured signals were often unavoidab...
Fuzzy Chaotic Neural Networks
Fuzzy Chaotic Neural Networks
An understanding of the human brain’s local function has improved in recent years. But the cognition of human brain’s working process as a whole is still obscure. Both fuzzy logic ...
Integrated Water Resources Management Approaches to Improve Water Resources Governance
Integrated Water Resources Management Approaches to Improve Water Resources Governance
The water crisis can alternatively be called a governance crisis. Thus, the demand for good water governance to ensure effective water resources management and to attain specific w...
An improved Coati Optimization Algorithm with multiple strategies for engineering design optimization problems
An improved Coati Optimization Algorithm with multiple strategies for engineering design optimization problems
AbstractAiming at the problems of insufficient ability of artificial COA in the late optimization search period, loss of population diversity, easy to fall into local extreme value...
Modeling Hybrid Metaheuristic Optimization Algorithm for Convergence Prediction
Modeling Hybrid Metaheuristic Optimization Algorithm for Convergence Prediction
The project aims at the design and development of six hybrid nature inspired algorithms based on Grey Wolf Optimization algorithm with Artificial Bee Colony Optimization algorithm ...
Modeling Hybrid Metaheuristic Optimization Algorithm for Convergence Prediction
Modeling Hybrid Metaheuristic Optimization Algorithm for Convergence Prediction
The project aims at the design and development of six hybrid nature inspired algorithms based on Grey Wolf Optimization algorithm with Artificial Bee Colony Optimization algorithm ...
Multi-Objective Optimal Power Flow Solutions Using Improved Multi-Objective Mayfly Algorithm (IMOMA)
Multi-Objective Optimal Power Flow Solutions Using Improved Multi-Objective Mayfly Algorithm (IMOMA)
This paper realizes the implementation of Improved Multi-objective Mayfly Algorithm (IMOMA) for getting optimal solutions related to optimal power flow problem with smooth and nons...

Back to Top