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A process optimization method has been developed for the design of reverse osmosis (RO) processes. RO process configurations are systematically generated using a flexible superstructure and evaluated by economical (investment and operating costs), technical (energy requirement, water recovery rate) and environmental performance indicators (Life Cycle Assessment). The simultaneous optimization of the RO process layout and operating conditions constitutes a mixed-integer nonlinear programming (MINLP) problem, which is solved using a multi-objective optimization (MOO) approach. The MOO identifies the best technological alternatives for the set of selected objectives. In a given context, it allows to define a set of optimal solutions representing the trade-off between conflicting objectives such as economical costs and environmental impacts. As a case study, the methodology is applied on a brackish water reverse osmosis (BWRO) desalination project, for which the optimal design is characterized depending on the economical conditions.