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.
We use AnyLogic investment risk management and simulation software to build a simulation model for the exploratory process. The model simulates the performance of a fleet (e.g. availability, waiting time, and cost) under different acquisition and maintenance strategies. AnyLogic investment analysis software allowed us to build resource-based model which considers the availability and usage of different resources (e.g. crews, manpower, docks) for performing different activities (e.g. maintenance, operation). The model has a modular structure and uses a combined discrete event and system dynamics approach. The model is run as a Java applet. We consider the investigation period of 9 years with a weekly time-step for simulation. We use the Exploratory Modelling Workbench for performing computational experiments using this simulation model and for implementing multi-objective robust optimization.
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