\documentclass[10pt]{article}

\usepackage{fullpage}
\usepackage{setspace}
\usepackage{parskip}
\usepackage{titlesec}
\usepackage[section]{placeins}
\usepackage{xcolor}
\usepackage{breakcites}
\usepackage{lineno}
\usepackage{hyphenat}





\PassOptionsToPackage{hyphens}{url}
\usepackage[colorlinks = true,
            linkcolor = blue,
            urlcolor  = blue,
            citecolor = blue,
            anchorcolor = blue]{hyperref}
\usepackage{etoolbox}
\makeatletter
\patchcmd\@combinedblfloats{\box\@outputbox}{\unvbox\@outputbox}{}{%
  \errmessage{\noexpand\@combinedblfloats could not be patched}%
}%
\makeatother


\usepackage{natbib}




\renewenvironment{abstract}
  {{\bfseries\noindent{\abstractname}\par\nobreak}\footnotesize}
  {\bigskip}

\titlespacing{\section}{0pt}{*3}{*1}
\titlespacing{\subsection}{0pt}{*2}{*0.5}
\titlespacing{\subsubsection}{0pt}{*1.5}{0pt}


\usepackage{authblk}


\usepackage{graphicx}
\usepackage[space]{grffile}
\usepackage{latexsym}
\usepackage{textcomp}
\usepackage{longtable}
\usepackage{tabulary}
\usepackage{booktabs,array,multirow}
\usepackage{amsfonts,amsmath,amssymb}
\providecommand\citet{\cite}
\providecommand\citep{\cite}
\providecommand\citealt{\cite}
% You can conditionalize code for latexml or normal latex using this.
\newif\iflatexml\latexmlfalse
\providecommand{\tightlist}{\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}%

\AtBeginDocument{\DeclareGraphicsExtensions{.pdf,.PDF,.eps,.EPS,.png,.PNG,.tif,.TIF,.jpg,.JPG,.jpeg,.JPEG}}

\usepackage[utf8]{inputenc}
\usepackage[ngerman,english]{babel}



\usepackage{float}








\begin{document}

\title{Multi-Objective Optimization of Reservoir Operation using Machine
Learning Models. Case study: Hatillo Reservoir in the Dominican Republic}



\author[1]{Carlos Tami}%
\author[2]{G Corzo}%
\author[3]{F Perez}%
\author[1]{G Santos}%
\affil[1]{Escuela Colombiana de Ingeniería Julio Garavito}%
\affil[2]{IHE Delft, Institute for Water Education}%
\affil[3]{Pontificia Universidad Católica Madre y Maestra}%


\vspace{-1em}



  
  \date{May 25, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
Finding optimum balances between conflicting interests in multipurpose
reservoirs often represents an important challenge for decision makers.
This study assesses the use of different computational tools to obtain
optimal reservoir operations applied to the Hatillo dam in the Dominican
Republic. A multiobjective optimization approach is used, in which
non-dominated sorting genetic algorithm II (NSGAII) and multi-objective
evolutionary algorithm based on decomposition (MOEA/D) optimizers are
applied to models that simulate reservoir operations. Three different
Machine Learning (ML) models, namely, the multilayer perceptron (MLP),
the radial basis network (RBN) and the linear function (LF), are
employed to learn the current operation of the system. Subsequently, a
general model is proposed to simulate daily reservoir operations
(2009-2019), integrating water balances, physical constraints of the dam
components and the ML models, the latter defining daily controlled
discharges. In the optimization process, the ML parameters are the
decision variables, while the objectives evaluated are irrigation,
hydropower generation and flood control. The results are compared with
the actual operation of the reservoir. Three dimensional Pareto fronts
are obtained, from which, the wide variety of operations can be
evidenced. The flood control objective was found to have a wide room for
improvement over the current operation of the reservoir, and several of
the solutions found improve the current operation for the three proposed
objectives. The MLP models tend to generate the best results for this
case study and the NSGAII optimizer generates the best optimization
results.%
\end{abstract}%



\sloppy


\textbf{Hosted file}

\verb`essoar.10512447.1.docx`  available at \url{https://authorea.com/users/537380/articles/599312-multi-objective-optimization-of-reservoir-operation-using-machine-learning-models-case-study-hatillo-reservoir-in-the-dominican-republic}

\selectlanguage{english}
\FloatBarrier
\end{document}

