Life Cycle Evaluation under Uncertain Environmental Policies Using a Ship-Centric Markov Decision Process Framework.
TL;DRAbstract
A novel design evaluation framework is offered to improve early stage design decisions relating to environmental policy change and similar non-technical disturbances. The goal of this research is to overcome the traditional treatment of policy as a static, external constraint and to address in early stage design the potential disruptions to performance posed by regulatory policy change. While a designer’s primary purpose is not to affect policy, it is the responsibility of the designer to be cognizant of how policy can change, of how to assess the implications of a policy change, and of how to deliver performance despite change. This research addresses a present need for a rigorous means to keep strategic pace with policy evolution. Use of a Markov Decision Process (MDP) framework serves as a unifying foundation for incorporating temporal activities into early stage design considerations. The framework employs probabilistic methods via a state-based structure to holistically address po
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A novel design evaluation framework is offered to improve early stage design decisions relating to environmental policy change and similar non-technical disturbances. The goal of this research is to overcome the traditional treatment of policy as a static, external constraint and to address in early stage design the potential disruptions to performance posed by regulatory policy change. While a designer’s primary purpose is not to affect policy, it is the responsibility of the designer to be cognizant of how policy can change, of how to assess the implications of a policy change, and of how to deliver performance despite change. This research addresses a present need for a rigorous means to keep strategic pace with policy evolution. Use of a Markov Decision Process (MDP) framework serves as a unifying foundation for incorporating temporal activities into early stage design considerations. The framework employs probabilistic methods via a state-based structure to holistically address po
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