Industrial symbiotic networks (ISNs) can support the transition from a conventional linear economy to a circular economy by using industrial waste and by-products as resources. However, the early design and development stages of ISNs are fraught with challenges as a result of limited information (supply, demand, potential synergies, etc.), and the need to consider conflicting sustainability objectives. ISN development is a combinatorial problem and can be expressed as a Multi Objective Optimization (MOO) model, the solution of which can aid practitioners in early decision-making and the identification of appropriate industrial synergistic partners. Inspired by the principles of self-organization among stakeholders to further sustainability, an ISN resulting by applying a hybrid MOO approach to tackle end of life photovoltaic (PV) modules in Arizona has been modeled. The hybrid MOO method is capable of balancing the sustainability objectives, while allocating material strategically such that resources do not get landfilled. The resulting ISN is compared with alternate ISN configurations arising from different scenarios. For instance, simply landfilling EoL PVs can result in economic losses of close to 3 million USD and a significant environmental burden (~27 thousand ton CO₂ eq). In contrast, an ISN where recovered material is consumed completely results in cost savings of 53 million USD and avoided environmental impacts of 18 thousand-ton CO₂ eq. Sensitivity analyses to account for the uncertainty related to landfilling and warehousing costs, and the distances between synergistic partners have been undertaken.