For decades, nuclear energy development was based on the expectation that recycling of the fissionable materials in the used fuel from today's light water reactors into advanced (fast) reactors would be implemented as soon as technically feasible in order to extend the nuclear fuel resources. More recently, arguments have been made for deployment of fast reactors in order to reduce the amount of higher actinides, hence the longevity of radioactivity, in the materials destined to a geologic repository. The cost of the fast reactors, together with concerns about the proliferation of the technology of extraction of plutonium from used LWR fuel as well as the large investments in construction of reprocessing facilities have been the basis for arguments to defer the introduction of recycling technologies in many countries including the US. In this thesis, the impacts of alternative reactor technologies on the fuel cycle are assessed. Additionally, metrics to characterize the fuel cycles and systematic approaches to using them to optimize the fuel cycle are presented. The fuel cycle options of the 2010 MIT fuel cycle study are re-examined in light of the expected slower rate of growth in nuclear energy today, using the CAFCA (Code for Advanced Fuel Cycle Analysis). The Once Through Cycle (OTC) is considered as the base-line case, while advanced technologies with fuel recycling characterize the alternative fuel cycle options available in the future. The options include limited recycling in LWRs and full recycling in fast reactors and in high conversion LWRs. Fast reactor technologies studied include both oxide and metal fueled reactors. Additional fuel cycle scenarios presented for the first time in this work assume the deployment of innovative recycling reactor technologies such as the Reduced Moderation Boiling Water Reactors and Uranium-235 initiated Fast Reactors. A sensitivity study focused on system and technology parameters of interest has been conducted to test the robustness of the conclusions presented in the MIT Fuel Cycle Study. These conclusions are found to still hold, even when considering alternative technologies and different sets of simulation assumptions. Additionally, a first of a kind optimization scheme for the nuclear fuel cycle analysis is proposed and the applications of such an optimization are discussed. Optimization metrics of interest for different stakeholders in the fuel cycle (economics, fuel resource utilization, high level waste, transuranics/proliferation management, and environmental impact) are utilized for two different optimization techniques: a linear one and a stochastic one. Stakeholder elicitation provided sets of relative weights for the identified metrics appropriate to each stakeholder group, which were then successfully used to arrive at optimum fuel cycle configurations for recycling technologies. The stochastic optimization tool, based on a genetic algorithm, was used to identify non-inferior solutions according to Pareto's dominance approach to optimization. The main tradeoff for fuel cycle optimization was found to be between economics and most of the other identified metrics.