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Robustness Theory: Holy Grail or Voodoo Science?

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Abstract:

Robust. Its dictionary meaning is simply “strong” or “vigorous,” but to some it means more, describing a cutting-edge approach to infrastructure management or policy-making, a sort of holy grail for modern times. To most of us, “robust” sounds like something we want our utilities to be – even if we're not sure exactly what it means.

Definitions and theories vary, but the basic concept of robustness is that, in the face of an uncertain future, there is more value in achieving “good enough” performance with very high reliability than “optimizing” performance for a single calculated future that will not likely occur. Framed this way, robustness certainly sounds like a great idea. Indeed, many talented scientists and practitioners have developed theories and methodologies for robustness. It behooves us as utility managers to understand robustness, its current value to us as managers, and its future implications.

A first reason why robustness is so appealing to us is that it seems to be how nature itself seems to work. Many organic systems, from ant colonies to ground squirrels, seem to employ some of the basic tenets of robustness. Ant colonies continue to function even after suffering devastating losses. Squirrels, rather than pursuing a simple optimization goal such as “maximize caloric intake,” appear at times to follow robustness-centered rules that may maximize their chance of survival even when things don't go according to plan.

A second reason why robustness is appealing is that it appears to address an ingravescent need, that of coping with deep uncertainties such as those posed by climate change. Uncertainties of this scale prompt nearly everybody to ask themselves “what if” the future turns out differently than predicted by a given model, and to desire solutions that work well for a wide range of futures even if not optimally for any specific future.

A third reason for the appeal of robustness is its potential to solve a problem we've brought on ourselves. The 1980s brought electronic computing power to the desktop. We suddenly had the power to “optimize” nearly everything, from the size of a pipe to the maintenance schedule for a truck. With that power of optimization came a new risk, the risk that we optimize for a particular future that likely will not occur while leaving performance against other likely futures poor or unknown. In short, the risk is that the power of computing has sharpened our vision for individual trees and potentially blinded us to seeing the forest.

This paper surveys the available tools for robustness in the context of utility management challenges. Theories discussed include Robust Decision Making theory, info-gap satisficing, and genetic algorithms. Applications discussed include climate change adaption.

Document Type: Research Article

DOI: https://doi.org/10.2175/193864712811694910

Publication date: 2012-01-01

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