Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Multi-objective optimisation using cellular automata: application to multi-purpose reservoir operation
In this paper, a weighted cellular automata (CA) is proposed to solve bi-objective reservoir operation optimisation problem considering two objectives of water supply and hydropower production. A mathematically derived updating rule is used contributing to the efficiency of the proposed CA method. The updating rule of the problem is derived by converting the bi-objective problem to a single-objective problem using the well-known weighting method. The proposed method is used to operate the Dez reservoir in Iran over various operation periods of 60, 120, 240 and 480 months to test the performance of the method for operational problems of different scales. Performance of the method is also compared with that of a non-dominated sorting genetic algorithm (NSGAII) as one of the most popular multi-objective evolutionary algorithms. The results indicate that the proposed method is highly efficient compared to the NSGAII while producing comparable results. This is in line with the early findings of superior efficiency and comparable effectiveness of the CA method with the existing evolutionary algorithms for single objective optimisation problems.
Multi-objective optimisation using cellular automata: application to multi-purpose reservoir operation
In this paper, a weighted cellular automata (CA) is proposed to solve bi-objective reservoir operation optimisation problem considering two objectives of water supply and hydropower production. A mathematically derived updating rule is used contributing to the efficiency of the proposed CA method. The updating rule of the problem is derived by converting the bi-objective problem to a single-objective problem using the well-known weighting method. The proposed method is used to operate the Dez reservoir in Iran over various operation periods of 60, 120, 240 and 480 months to test the performance of the method for operational problems of different scales. Performance of the method is also compared with that of a non-dominated sorting genetic algorithm (NSGAII) as one of the most popular multi-objective evolutionary algorithms. The results indicate that the proposed method is highly efficient compared to the NSGAII while producing comparable results. This is in line with the early findings of superior efficiency and comparable effectiveness of the CA method with the existing evolutionary algorithms for single objective optimisation problems.
Multi-objective optimisation using cellular automata: application to multi-purpose reservoir operation
Afshar, M. H. (Autor:in) / Hajiabadi, R. (Autor:in)
Civil Engineering and Environmental Systems ; 36 ; 115-132
02.10.2019
18 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
Application of Cellular Automata in Bi-Objective Operation of Multi Reservoir Systems
| DOAJ | 2021
A cellular automata approach for the hydro-power operation of multi-reservoir systems
| Online Contents | 2013
Optimizing Multi-purpose Reservoir Operation Using Particle Swarm Intelligence
| Springer Verlag | 2016
Multi-objective optimization method for the ATO system using Cellular Automata
| British Library Conference Proceedings | 2008
Multi-Objective Optimization of Folsom Reservoir Operation
| British Library Conference Proceedings | 2006