The increasing awareness of sustainability issues has driven the industry and society to pursue more economically, environmentally and socially sustainable strategies in the design and operations of supply chains. Systematic methods based on computational optimization frameworks using a life cycle perspectives play an important role in this quest. These computational frameworks integrate life cycle analysis and technoeconomic assessment with multiobjective superstructure optimization to improve overall sustainability performance of the supply chains. This talk will explore some recent results on the development of large-scale mixed-integer nonlinear programming models and algorithms for life cycle optimization of sustainable supply chains. I will specifically focus on two frameworks. The first one is concerned with the functional unit-based life cycle optimization of sustainable supply chains under economic and environmental criterions. The second one addresses the life cycle optimization in a decentralized, non-cooperative supply chains under a leader-follower game structure. We will discuss general modeling frameworks and case studies on hydrocarbon biofuels and shale gas supply chains. Along with these applications, I will also present recent developments in the theory and solution algorithms for solving large-scale mixed-integer fractional programming and mixed-integer bilevel programming problems.