(456h) A Framework for Multi-Stakeholder Decision-Making and Conflict Resolution

The design and control of engineering systems is a complex decision-making process in which multiple conflicting objectives of social, economic, and environmental nature must be taken into account. Moreover, many decisions-making processes involve multiple stakeholders who disagree on how to prioritize the conflicting objectives. This is especially true in the field of sustainability, where hundreds of metrics may be considered and prioritized differently by a diverse population of stakeholders, such as different communities, regulatory agencies and companies. For even a moderate number of dimensions, however, exhaustively characterizing the trade-offs between objectives (i.e., computing the entire Pareto set) is computationally intractable.

We use the conditional-value-at-risk (CVaR) metric to create a general multi-stakeholder decision-making framework. We observe that stakeholder dissatisfactions (distance to their individual ideal solutions) can be interpreted as random variables. We thus shape the dissatisfaction distribution and find an optimal compromise solution by solving a CVaR minimization problem parameterized in the probability level. This enables us to generalize multi-stakeholder settings previously proposed in the literature that minimize average and worst-case dissatisfactions. We use the concept of the CVaR norm to give a geometric interpretation to this problem and use the properties of this norm to prove that the CVaR minimization problem yields Pareto optimal solutions for any choice of the probability level. We discuss a broad range of potential applications of the framework. We demonstrate the framework in a biowaste processing facility location case study, where we seek compromise solutions (facility locations) that balance stakeholder priorities on transportation, safety, water quality, and capital costs.

Reference:

Dowling, A. W., Ruiz-Mercado, G., Zavala, V. M. (2016), A framework for multi-stakeholder decision-making and conflict resolution, Computers & Chemical Engineering, in press.