This dissertation presents a pair of models designed to assist in the management of multiple deteriorating real assets, given financial and environmental concerns. Whether the assets are buildings or vehicles or machines, their purchase and upkeep can be costly, making optimal management policies valuable. The models presented build upon a strong literature. They incorporate numerous factors which have been modeled previously, though generally not together. These include technological change, linked decisions for multiple assets, and non-steady-state demand. They stand out from previous literature due to their ability to model retrofits, as well as repairs and replacements. These retrofits can have initial as well as ongoing costs, and can impact externalities, making them relatively general. The integer program model is fast and well suited to analysis requiring large numbers of runs, such as the comparison of a wide range of regulatory alternatives. The approximate dynamic program, while slower, is able to handle stochastic asset failures and repair costs for large asset portfolios, something which previous models have struggled to accomplish without strong simplifying assumptions. A customized value iteration approach produces good solutions within a few hours for sample problems involving a fleet of well over a thousand vehicles subject to clean diesel regulation.