Application of bi-objective genetic programming for optimizing irrigation rules using two reservoir performance criteria. Issue 1 (2nd January 2021)

• Record Type: Journal Article
• Authors: Ashofteh, Parisa-Sadat; Bozorg-Haddad, Omid; Loáiciga, Hugo A.
• Is Part Of: International journal of river basin management. Volume 19:Issue 1(2021)
• Page Start: 55
• Page End: 65
• Publication Date: 2021-01-02
• Subjects: Bi-objective genetic programming -- Pareto front -- vulnerability -- reliability -- optimal operating rules; Watershed management -- Periodicals; Water resources development -- Periodicals; Hydraulic engineering -- Periodicals; Watershed hydrology -- Periodicals; Water resources development; Watershed management; Watersheds; Periodicals; 551.483
• DOI: 10.1080/15715124.2019.1613415
• Languages: English
• ISSNs: 1814-2060

Abstract

ABSTRACT: A bi-objective genetic programming (BO-GP) algorithm is developed and applied to optimize the operating rules of the Aidoghmoush reservoir (East Azerbaijan in northeastern Iran). The two-objective optimization problem maximizes reservoir reliability and minimizes the vulnerability index associated with the supply of agricultural water. The developed BO-GP algorithm calculates Pareto possibility frontiers representing loci of optimal operating policies. Any operation policy is calculated by the BO-GP based on the inflow volume to reservoir, the storage volume, and the water demand volume that minimize vulnerability and maximize reliability. The application results show a successful performance of the BO-GP algorithm in solving the bi-objective water supply problem with reservoir operation. This paper's results establish that the system vulnerability and its reliability range between 16–41% and 46–78%, respectively.