A multi-objective optimization model to plan city-scale water systems with economic and environmental objectives: a case study in Santiago, Chile
Daniela Gormaz-Cuevas,Javiera Riffo-Rivas,Ludovic Montastruc,Mariana Brüning-González,Felipe A. Díaz-Alvarado +4 more
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TLDR
In this paper, a multi-objective mixed-integer programming (MOP) problem is formulated to minimize the environmental and economic impact of the network, minimizing water extracted from natural sources and total cost.About:
This article is published in Journal of Cleaner Production.The article was published on 2021-01-10 and is currently open access. It has received 6 citations till now. The article focuses on the topics: Water scarcity & Reuse.read more
Figures
Fig. 14. Representation of the mass balance of a large newwaste water treatment plant with fresh water output quality. C: collection; DL: large existing DWTPs; DS: small existing DWTPs; ILfs: large industrial consumers with fresh water consumption and sewage discharge; ILfn: large industrial consumers with fresh water consumption and natural water course discharge; S: sink.X 
Fig. 21. Pareto curve obtained for the multi-objective problem. 
Fig. 3. Representation of the mass balance of commercial and residential consumption. DS: existing small DWTPs with surface water consumption; NS: new small DWTPs; MAs: modified small WWTPs with drinking water output quality; NAs: new small WWTPs with drinking water output quality; D: distribution; C: collection; WS: small existing WWTPs; NAs: new small WWTPs with drinking water output quality; NBs: new small WWTPs with fresh water output quality; NCs: new small WWTPs with irrigation water output quality; NDs: new small WWTPs with discharge water output quality; MAs: modified small WWTPs with drinking water output quality; MBs: modified small WWTPs with fresh water output quality; MCs: modified small WWTPs with irrigation water output quality; S: sink. 
Fig. 18. Representation of the mass balance of collection node. RC: residential consumption; CC: commercial consumption; EB: industrial effluent treatment plant connected with large industrial consumers; ELds: related to ILds; ELdn: related to ILdn; WL: large existing DWTPs; NAl: new large WWTPs with drinking water output quality; NBl: new large WWTPs with fresh water output quality; NCl: new large WWTPs with irrigation water output quality; NDl: new large WWTPs with discharge water output quality; MAl: modified large WWTPs with drinking water output quality; MBl: modified large WWTPs with fresh water output quality; MCl: modified large WWTPs with irrigation water output quality; S: sink. 
Fig. 4. Representation of the mass balance of local industrial consumption. DS: existing small DWTPs with surface water consumption; NS: new small DWTPs; MAs: modified small WWTPs with drinking water output quality; NAs: new small WWTPs with drinking water output quality; D: distribution; EB: industrial effluent treatment plant connected with by-district industrial consumers; S: sink. 
Fig. 5. Representation of the mass balance of large industrial consumption supplied with drinking water and discharging into surface water courses. DS: small existing DWTPs; D: distribution; NS: new small DWTPs; NAs: new small WWTPs with drinking water output quality;MAs: modified small WWTPs with drinking water output quality; ELdn: related to ILdn; S: sink.X
Citations
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An optimal resource recovery of biogas, water regeneration, and reuse network integrating domestic and industrial sources
TL;DR: In this article, a non-linear programming (NLP) model was developed to optimize water regeneration and reuse network, as well as biogas generation from selected wastewater streams.
Journal ArticleDOI
Hindcasting and Forecasting Total Suspended Sediment Concentrations Using a NARX Neural Network
TL;DR: In this article, a non-linear autoregressive exogenous neural network (NARX) was used for forecasting sediment concentrations at the exit of Francia Creek watershed (Valparaiso, Chile).
Journal ArticleDOI
Applications of Multi-Objective Optimization to Industrial Processes: A Literature Review
TL;DR: Multi-objective optimization has become a powerful tool to aid the decision-making mechanism in the synthesis, design, operation and control of such processes as mentioned in this paper , and the solution to the mathematical models provides the necessary tools to asses the system performance in terms of different metrics and evaluate the trade-offs between the objectives in conflict.
Journal ArticleDOI
Modeling Frictional Head Loss in the Redesign of City-Scale Water Networks through Multiobjective Optimization: Strategies to Deal with Nonlinear Terms
TL;DR: In this paper , the authors compared four strategies to simplify the nonlinear constraints generated by the extended Bernoulli equation with the Darcy-Weisbach friction term in a city-scale water network, and the best results were obtained with a two-stage strategy to address large MINLP multiobjective problems.
Journal Article
The Evaluation of Parameter M in the Big M Method of Linear Programming
TL;DR: This paper determines a constant M0 and proves that the big M method is convergent to an optimal solution of the primal problem when MM0.
References
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Optimal retrofit of water conservation networks
César Sotelo-Pichardo,José María Ponce-Ortega,Mahmoud M. El-Halwagi,Sergio Frausto-Hernández +3 more
TL;DR: In this paper, a new general mathematical programming model for the optimal retrofit of material conservation networks considering recycle, reuse and regeneration schemes is presented, where the objective function accounts for the minimization of the total annual cost associated to the retrofit process.
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A Multi-Objective Artificial Bee Colony-based optimization approach to design water quality monitoring networks in river basins
TL;DR: In this article, a multi-objective artificial bee colony-based optimization algorithm is designed and implemented in a Geographic Information System framework to minimize the number of stations in a range of values at the same time that the detection of lower compliance areas, the affected population and the relative importance of the river stretches are maximized.
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MILP model for emergy optimization in EIP water networks
TL;DR: In this article, a mixed-integer linear programming (MILP) model for minimizing emergy of an interplant water network in an eco-industrial park is presented, which accounts for the environmental impacts of water use, energy consumption, and capital goods within the EIP in a balanced manner.
Journal ArticleDOI
Design of a water allocation and energy network for multi-contaminant problems using multi-objective optimization
S. De-León Almaraz,Marianne Boix,Ludovic Montastruc,Catherine Azzaro-Pantel,Zuwei Liao,Serge Domenech +5 more
TL;DR: In this paper, a solution strategy based on an optimization formulation is proposed for the design of water allocation and heat exchange networks (WAHEN) in the process industries, where a two-stage methodology is proposed.
Journal ArticleDOI
Generalized mixed-integer nonlinear programming modeling of eco-industrial networks to reduce cost and emissions
TL;DR: In this paper, the authors developed a generalized modeling framework in terms of mixed-integer nonlinear programming of an eco-industrial network, formulated as a multi-objective optimization with the objective to reduce life-cycle emissions and maintaining favorable economics.