Ship design evaluation subject to carbon emission policymaking using a Markov decision process framework

Abstract

This paper outlines a novel ship design evaluation framework rooted in Markov decision analysis and derived metrics. The framework synthesizes concepts from dynamic network optimization, decision theory, and scenario analysis to holistically manage exogenous uncertainty and value ship system changeability. A Markov decision process is used to analyze development and operational paths over a ship׳s life cycle and to identify system characteristics consistent within high performing designs. Decision metrics then contextualize a fuller extent of design engineer and operator preferences toward tradeoffs between value creation and active ship management. The case study specifically examines future scenarios subject to carbon emission regulations and uncertainty surrounding enforcement of the Energy Efficient Design Index. Results inform decisions about when, where, and how to incorporate the changeability that maximizes expected life cycle rewards.