ORIGINAL RESEARCH PAPER A Disjunctive Programming Approach for Optimizing Carbon, Hydrogen, and Oxygen Symbiosis Networks Maricruz Juárez-García 1 & José María Ponce-Ortega 1 & Mahmoud M. El-Halwagi 2,3 Received: 28 May 2018 /Revised: 5 August 2018 /Accepted: 7 August 2018 # Springer Nature Singapore Pte Ltd. 2018 Abstract Recently, the synthesis of carbon–hydrogen–oxygen symbiosis networks (CHOSYNs) has been proposed for the multi-scale integration of process industries that deal mainly with hydrocarbons while enabling chemical reactions, separation, heating/ cooling, pressurization/depressurization, and allocation of the participating streams and species. Because of the complexity of the design problem, there is a need for efficient optimization approaches to solve the problem. In this paper, two optimization approaches are presented based on disjunctive programming. Several objective functions are used to target resource conservation (e.g., minimum fresh usage and minimum waste discharge) and economics (e.g., minimum cost, maximum profit). The optimi- zation formulations include the tracking of species and streams, the potential installation of industrial facilities to carry out chemical conversions and other tasks, and the allocation of streams from sources to sinks via newly added interceptors. The first approach is a two-stage mathematical programming method. In the first stage, an optimization model based on atomic balances is used to determine the targets for fresh resources and discharges of the system. In the second stage, a disjunctive optimization model with an economic objective is employed to determine the configuration and allocation of the network considering existing and new industrial plants involved in the eco-industrial plant. The second approach is a simultaneous method based on a disjunctive optimization model to determine the targets and network configuration. A case study is presented to show the applicability of the proposed approaches. Keywords Mass integration . Recycling and reuse networks . Eco-industrial parks . Optimization Introduction The proper use of resources in the chemical and petrochemical industries has been the subject of several research contribu- tions in the past few decades. This is an important trend be- cause raw material usage and waste discharge are among the most important factors impacting the cost and sustainability of industrial processes. Recently, there has been a growing interest in integrating multiple industrial plants through the notion of industrial symbiosis (Chertow 2000). A primary approach to enhancing industrial symbiosis is the creation of eco-industrial parks (EIPs) that share natural resources, byproducts, wastes, and infrastructure (Lowe 1997). In this context, several optimization approaches have been developed to synthesize exchange, recycle, and reuse networks in EIPs for optimization of water usage and discharge using mass integration (Boix et al. 2015). For example, Chew et al. (2008) presented a mathematical programming approach for designing inter-plant water networks, Lovelady and El- Halwagi (2009) incorporated the management of external wa- ter resources in the design of EIPs, Aviso et al. (2010) in- volved fuzzy mathematical programming in designing EIPs, Rubio-Castro et al. (2010) reported a global optimization ap- proach for designing EIPs, and Rubio-Castro et al. (2011) extended this model to consider multiple pollutants. Then, Rubio-Castro et al. (2013) incorporated property constraints in designing EIPs, and Lira-Barragan et al. (2013) accounted for the surrounding watershed. In addition to managing water * José María Ponce-Ortega jmponce@umich.mx 1 Chemical Engineering Department, Universidad Michoacana de San Nicolás de Hidalgo, Av. Francisco J. Mújica, S/N, Ciudad Universitaria, Edificio V1, 58060 Morelia, Michoacán, Mexico 2 Chemical Engineering Department, Texas A&M University, College Station, TX 77843, USA 3 Adjunct Faculty at the Chemical and Materials Engineering Department, King Abdulaziz University, Jeddah, Saudi Arabia Process Integration and Optimization for Sustainability https://doi.org/10.1007/s41660-018-0065-y