(283c) Survey-Driven Sustainability Assessment Using Global Optimization Techniques

Authors: 
Conner, J. A., University of California, Los Angeles
Manousiouthakis, V., University of California Los Angeles, Los Angeles
In this work, we pursue an extension of our previously-developed Sustainability Index Interval (SII) method [1] that directly incorporates the opinions of the public into the scheme.

A case study involving the sustainability assessment and ranking of leading aluminum-producing enterprises will be pursued to demonstrate the proposed method. Appropriate sustainability assessment metrics and basic indicators (e.g. greenhouse gas emissions) are selected from Phillis et al. [2] and our previous work [1]. Values (or ranges of values) for each of the metrics are obtained for all enterprises via publicly-available documentation. Once this data is obtained, surveys listing this data are compiled and then presented to three groups of people: the general public, university students, and university professors. Each group’s opinion is sought on each enterprise’s sustainability efforts regarding the aforementioned metrics. The results of these surveys are then incorporated into an SII for each enterprise. Subsequently, recommendations for each enterprise are developed on areas in which sustainability improvements will yield the greatest SII improvement.

References:

[1] Conner, J.A., Phillis, Y.A., Manousiouthakis, V.I. (2012), “On a Sustainability Interval Index and Its Computation Through Global Optimization”, AIChE Journal, 58(9), 2743-2757.

[2] Phillis, Y.A, Davis, B.J. (2009), “Assessment of Corporate Sustainability via Fuzzy Logic”, J Intell Robot Syst., 55 3-20.