Multi-objective decision making in multi-period acquisition planning under deep uncertainty

Abstract

Acquisition planning involves decisions to be made regarding the number of assets to be acquired initially and the type and timing of replacement and upgrade actions to maintain performance measures efficiently. Acquisition planning is challenging for high-valued assets because of considerable uncertainties in their long-term life cycle. This article proposes an approach to determine which acquisition strategy---i.e. what initial number of assets, what number of new acquisitions, and in what time throughout a long-term planning period---can robustly fulfil multiple performance objectives in the face of plausible future scenarios. The article incorporates robust optimization for the treatment of uncertainty inside the simulation multi-objective optimization process where the robustness of different acquisition strategies in future scenarios is analyzed by running many simulations. A fleet management system is used as an illustrative hypothetical example. The results show an adaptation map of robust acquisition strategies over the life cycle of the fleet.