In previous work, the technology portfolio problem was formulated and used in conjunction with environmental goals for the 2020-2025 timeframe to identify a Pareto frontier of solutions using multi-objective genetic algorithms. Continuation of this work includes decoupling environmental goals from regulatory standards by introducing absolute valued analogues to isolate metric performance and identify the Pareto frontier in the absolute valued objective space. The Pareto-optimal technology combinations are characterized in terms of its corners, underlying performance tradeoffs, and salient features. Favorable regions within the Pareto frontier are also examined by quantifying the gap to prescribed environmental goals while identifying pervasive technologies. In addition, a technology maturation resource constraint based on Technology Readiness Level (TRL) is formulated and used to study the tradeoff between resource burden and solution performance. Also, Pareto frontier evolution is studied as the resource constraint is made more stringent, and a critical value of is identified corresponding to the onset of a rapid performance degradation and regression of the Pareto frontier.
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