Fuzzy optimization of topologically constrained eco-industrial resource conservation networks with incomplete information

• Main Authors: Aviso, Kathleen B., Tan, Raymond Girard R., Culaba, Alvin B., Foo, Dominic C.Y., Hallale, Nick
• Format: text
• Published: Animo Repository 2011
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/1027; https://animorepository.dlsu.edu.ph/context/faculty_research/article/2026/type/native/viewcontent
• Institution: De La Salle University

It is possible to minimize industrial resource consumption by establishing eco-industrial resource conservation networks (RCN) between different plants. The establishment of these networks requires the satisfaction of quality criteria for material properties deemed significant by an industry. It also necessitates cooperation among the different firms based on the satisfaction of individual cost or resource consumption goals. Furthermore, there may be varying degrees of incomplete information regarding the process data of the participating plants. Eco-industrial RCNs may also be topologically constrained with respect to the number of links connecting different plants. These design aspects are incorporated in the optimization model through fuzzy mixed integer linear programming (FMILP) or fuzzy mixed integer non-linear programming (FMINLP). Case studies from literature involving water integration and hydrogen recovery are used to illustrate the methodology. The model is able to identify the topologically constrained network that achieves the highest level of overall satisfaction among participating plants. © 2011 Taylor & Francis.