An Eco-Industrial Park (EIP) is a community of businesses that seeks to reduce the global impact by sharing material. The connections among the industrial participants within this park improve the environmental performance of the industrial network. However, the connectivity also propagates failures. This risk is an important point of criticism and a barrier to industrial plants when evaluate their integration to an EIP. This paper proposes an indicator to follow the resilience of an EIP so as to improve the security of the whole system, considering the dynamic of the participants to endure a disruptive event. This metric could be used by decision-makers in order to include the resilience in the design phase of an EIP. Solving these security problems would expand the set of experiences of cleaner production, facilitating the integration of industrial processes. The proposed resilience indicator is based on two main characteristics of an industrial network: the number of connections among participants, and the capacity of each flow to change its magnitude when a participant suddenly stops sharing flows within the park. A network is separated in independent layers to quantify its flexibility when substituting flows. Each layer includes a single shared material. The resilience of a multi-layer park is then calculated as a weighted summation. This indicator is applied over two illustrative cases to study: Kalundborg, in Denmark; and Ulsan, in South Korea. These applications show consistent results when compared with reality. Although the proposed resilience indicator has been developed for material networks, it can be adapted to heat integration networks. In this case, special attention should be payed to physical constraints as minimal temperature gradients.

Water resource management is a crucial issue today when global warming is advancing, generating water shortages in several world countries. Mathematical and optimization tools have addressed these problems, including new alternative water sources. Water networks are designed to cover consumption. In this context, pumping is critical in modeling water networks through optimization techniques because of the nonlinear terms from the extended Bernoulli equation with the Darcy−Weisbach friction term. This paper compares four strategies to simplify these terms, focusing on the nonlinear constraints generated by the extended Bernoulli equation with the Darcy−Weisbach friction term. This equation has a significant impact on operation costs because of pumping power. The four simplification strategies were compared with a focus on (i) solution, (ii) error, and (iii) execution time. The best results were obtained with a two-stage strategy to address large MINLP multiobjective problems. This strategy is applied to a model with three objective functions (freshwater inlet, global warming potential, and total cost) to illustrate the simplification performance in a city-scale water network. The problem is focused on a case study in Santiago, Chile, and is based on a previous formulation. By solving the multiobjective problem, some results and changes in the network are obtained. When the three objective functions have all the same importance, the results show the following: (i) The current location of water treatment plants is suboptimal. (ii) Water recycling in the city is the best option, with drinking and irrigation qualities. (iii) With the optimal configuration, Santiago can reduce their water consumption by 30%, increasing the economic cost by 108% and the global warming potential by 49%. Finally, this model can be implemented in other contexts to approach nonlinearities by the extended Bernoulli equation with the Darcy−Weisbach friction term in large-scale water networks.

This paper proposes an iterative algorithm to calculate the stability region of parameters in mixed-integer non-linear programing (MINLP) problems. It is based on a previous algorithm developed for MILP problems with modifications to accelerate the search: (i) initial point is calculated; (ii) search region is bounded by context information; (iii) time limit for iterations is estimated; and (iv) the output is a stability index. The novelties of this research are the first algorithm for MINLP cases and a stability index that recognizes the critical parameters to the resilience of the solution. The proposed algorithm is applied to the water network design, and the stability region is calculated for six parameters. The modifications reduce the implementation time by 96.6% in the case study compared to the referential version. A potential direction for this work is to include a more detailed analysis of the mathematical expressions to make the algorithm faster.