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Journal of Environmental Accounting and Management
António Mendes Lopes (editor), Jiazhong Zhang(editor)
António Mendes Lopes (editor)

University of Porto, Portugal

Email: aml@fe.up.pt

Jiazhong Zhang (editor)

School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, China

Fax: +86 29 82668723 Email: jzzhang@mail.xjtu.edu.cn


Coupling Multi-objective Constrained Optimization, Life Cycle Assessment, and Detailed Process Simulation for Potable Water Treatment Chains

Journal of Environmental Accounting and Management 3(3) (2015) 217--227 | DOI:10.5890/JEAM.2015.09.002

Florin Capitanescu; ElorriIgos; Antonino Marvuglia; Enrico Benetto

Luxembourg Institute of Science and Technology (LIST), Environmental Research and Innovation (ERIN) Department, 41-rue du Brill, L-4422Belvaux, Luxembourg

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Abstract

This paper deals with the optimization of key decision variables of a potable water production plant. To this end we propose a multi-objective constrained optimization approach which trades-off operational costs and environmental impact while satisfying outlet water drinkability criteria. The proposed solution approach consists in coupling a meta-heuristic global optimization algorithmand EVALEAU, which is a state-of-the-art process modelling - life cycle assessment (LCA) tool for simulating potable water treatment chains. The proposed eco-design optimization approach is successfully illustrated on a real-world model of a water production plant, and the relative performances of two highly praised stateof- the-art derivative-free global optimization algorithms,namely the Strength Pareto Evolutionary Algorithm (SPEA2) and Non-dominated Sorting Genetic Algorithm (NSGA-II),are compared.

Acknowledgments

The authors acknowledge the funding from National Research Fund (FNR)Luxembourg in the framework of the OASIS project (CR13/SR/5871061). The authors also wish to thank Dr. Aras Ahmadi (INSA Toulouse, France) for data provided and support in setting-up the multi-objective constrained optimization problem, and Dr. Richard J. Wallace (Insight Centre for Data Analytics, Cork, Ireland) for having initiated the research in this topic during a research visit at the Public Research Centre Henri Tudor (which has now become part of the LIST), and for providing his code which lighten our programming effort regarding the use of Umberto functionalities.

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