Robustness in optimal design of Eco-Industrial Parks under the lens of two-stage stochastic optimization

An eco-industrial park (EIP) is a community of businesses located together on a common property, that seek to reduce environmental and economical impact of their operation by collaborating and sharing materials and wastes. In practice, operations within an EIP have daily variations, and therefore are constantly facing uncertainty. In this work, a methodology to design efficient EIPs that are also robust to daily (uncertain) variations of the nominal operation of the enterprises is proposed. The attention is mainly focused in water exchange networks. Probability functions are used to measure robustness and propose a Sample Average Approximation technique to solve the associated optimization problem. Simulations based on literature examples are performed to illustrate the approach.