<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Optimal operation of reservoir systems is the most important issue in water resources management. It presents a large variety of multi-objective problems that require powerful optimization tools in order to fully characterize the existing trade-offs. Many optimization methods have been applied based on mathematical programming and evolutionary computation (especially heuristic methods) with various degrees of success more recently. This paper presents an implementation and comparison of multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGA-II) for the optimal operation of two reservoirs constructed on Ozan River catchment in order to maximize income from power generation and flood control capacity using MATLAB software. The alternative solutions were based on Pareto dominance. The results demonstrated superior capacity of the NSGA-II to optimize the operation of the reservoir system, and it provides better coverage of the true Pareto front than MOPSO.</p></abstract>

Optimal operation of reservoir systems is the most important issue in water resources management. It presents a large variety of multi-objective problems that require powerful optimization tools in order to fully characterize the existing trade-offs. Many optimization methods have been applied based on mathematical programming and evolutionary computation (especially heuristic methods) with various degrees of success more recently. This paper presents an implementation and comparison of multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGA-II) for the optimal operation of two reservoirs constructed on Ozan River catchment in order to maximize income from power generation and flood control capacity using MATLAB software. The alternative solutions were based on Pareto dominance. The results demonstrated superior capacity of the NSGA-II to optimize the operation of the reservoir system, and it provides better coverage of the true Pareto front than MOPSO.

Application and comparison of NSGA-II and MOPSO in multi-objective optimization of water resources systems

Journal of Hydrology and Hydromechanics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Optimal operation of reservoir systems is the most important issue in water resources management. It presents a large variety of multi-objective problems that...

Application and comparison of NSGA-II and MOPSO in multi-objective optimization of water resources systems

Data publikacji: 14 sie 2018

Zakres stron: 323 - 329

Otrzymano: 28 gru 2016

Przyjęty: 19 wrz 2017

DOI: https://doi.org/10.2478/johh-2018-0006

Słowa kluczowe
NSGA-II, MOPSO, Multi-objective optimization, Flood control, Hydropower

© 2018 Mohsen Monadi, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Application and comparison of NSGA-II and MOPSO in multi-objective optimization of water resources systems

Data publikacji: 14 sie 2018

Zakres stron: 323 - 329

Otrzymano: 28 gru 2016

Przyjęty: 19 wrz 2017

DOI: https://doi.org/10.2478/johh-2018-0006

Słowa kluczoweNSGA-II, MOPSO, Multi-objective optimization, Flood control, Hydropower

© 2018 Mohsen Monadi, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Słowa kluczowe
NSGA-II, MOPSO, Multi-objective optimization, Flood control, Hydropower