Extensive research has been done on the components that constitute the sulfur supply chain, including sulfur recovery, storage, forming, and distribution. The research focus was on improving the efficiency and environmental sustainability of each of these areas rather than focusing on the supply chain as a whole. The aim of this work is to design a sulfur supply chain that integrates these components within a single framework. It represents a starting point in understanding the trade-offs involved in the sulfur supply chain from an optimization point of view. Optimization and mathematical modeling techniques were implemented to generate a decision support system that will provide an indication of the optimal design and configuration of sulfur supply chains. The resulting single-period mixed-integer linear programming (MILP) model was aimed at minimizing total infrastructural and operational costs. The model was illustrated through a case study based on Albertas Industrial Heartland (AIH). A deterministic approach in an uncertain environment was implemented to investigate the effect of supply and demand variability on the design of the supply chain. This was applied to two scenarios, which are steady state operation and sulfur surplus accumulation. The results for the investigated case study reveal that the optimum sulfur supply chain might consist of medium-to-large sulfur forming facilities serving multiple producers. The model also identified the locations of forming facilities, the forming, storage and transportation technologies, and their capacities.