Optimal operation of single and multi-reservoir systems via hybrid shuffled grey wolf optimization algorithm (SGWO)

Fariborz Masoumi*, Sina Masoumzadeh Sayyar, Negin Zafari, Mohammad Javad Emami Skardi

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

7 Sitaatiot (Scopus)

Abstrakti

Reservoir operation is a key issue in the water resources system. In this paper, the Shuffled Grey Wolf Optimizer (SGWO), a hybrid optimization algorithm inspired by Shuffled Complex Evolution (SCE-UA) and Gray Wolf Optimizer (GWO) algorithms, is introduced. The main modification in the proposed algorithm is how it divides and shuffles the population to enhance the information exchange among the individuals. The performance of the SGWO algorithm is compared to famous evolutionary algorithms such as Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) in solving mathematical benchmark functions and multiple types of reservoir operation optimization problems with different scales. Two hypothetical 4 and 10-reservoir system, and the Dez dam in Iran as a single reservoir system were selected as the case study in this research. The capability of the algorithms was compared in terms of …
AlkuperäiskieliEnglanti
Sivut1663-1675
Sivumäärä13
JulkaisuWater Science & Technology: Water Supply
Vuosikerta22
Numero2
DOI - pysyväislinkit
TilaJulkaistu - helmik. 2022
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

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