abstract

• Nowadays, an adequate design of wastewater treatment plants taking into consideration all sustainability dimensions– economic, environmental and social- is fundamental. This can be achieved by implementing systematic methodologies where conceptual and mathematical tools can be used together. This contribution proposes a framework that uses total cost, consumed energy, and reclaimed wastewater as sustainability metrics. A mixed-integer nonlinear programming problem arises from a general superstructure for wastewater treatment plants. A case study from Mexico City is solved by a hybrid multiobjective optimization approach that combines lexicographic and ε-constraint methods. Solutions are provided in the form of a Pareto front. A modified technique for order of preference by similarity to ideal solution (M-TOPSIS) analysis is used as a multiple criteria decision-making tool to find the best trade-off solution. The optimal sustainable configuration resulted consists of three levels of treatment and 100%25 of treated water reuse. © 2020

authors

• Almaraz S.D.-L.
• Padrón-Páez J.I.
• Román Martínez Alicia

publication date

• 2020-01-01

funding provided via

• Consejo Nacional de Ciencia y Tecnología, CONACYT: 323488  Grant

published in

• Computers and Chemical Engineering  Journal

keywords

• Mixed-integer nonlinear programming problem; Modified technique for order of preference by similarity to ideal solution; Multiobjective optimization; Multiple criteria decision making; Socio-eco-efficient sustainability; Wastewater treatment plants Decision making; Economic and social effects; Integer programming; Multiobjective optimization; Nonlinear programming; Sewage pumping plants; Sustainable development; Wastewater reclamation; Water conservation; Water treatment; Water treatment plants; Epsilon-constraint method; Mixed integer non-linear programming problems; Multiple criteria decision making; Sustainability dimensions; Sustainability metrics; Sustainable wastewater treatments; Systematic methodology; Wastewater treatment plants; Wastewater treatment

Digital Object Identifier (DOI)

• 10.1016/j.compchemeng.2020.106850

start page

end page

volume

• 140