The design and optimization of industrial water networks in eco-industrial parks is studied by formulating and solving multi-leader-follower (MLFG) game models. The methodology is explained by demonstrating its advantages against multi-objective optimization (MOO) approaches. The approach is validated on a case study of water integration in EIP with regeneration units. Each enterprise’s objective is to minimize the total annualized cost, while the EIP authority objective is to minimize the consumption of freshwater within the ecopark.
On the other hand, flexibility of the methodology is studied by varying parameters in the case study such as the capacity of the regeneration units. The MLFG is transformed into a mathematical problem with complementarity constraints (MPCC) and solved using GAMS® as with a NLP formulation. The methodology proposed is proved to be very reliable in multi-criteria scenarios compared to MOO approaches, providing numerical Nash equilibrium solutions and specifically in EIP design and optimization. This method is proven to be reliable in this context because it proposes to obtain one solution instead of a set of optimal solutions that takes directly into account the preferences of the decision maker. © 2016 Elsevier B.V.