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