Group decision support with the analytic hierarchy process
Decision Support Systems
Comparison of weighting judgments in multiattribute utility measurement
Management Science
Multicriteria Optimization
Stochastic multi-objective models for network design problem
Expert Systems with Applications: An International Journal
A stochastic multiobjective optimization framework for wireless sensor networks
EURASIP Journal on Wireless Communications and Networking - Special issue on theoretical and algorithmic foundations of wireless ad hoc and sensor networks
SIAM Journal on Optimization
Searching for robust pareto-optimal solutions in multi-objective optimization
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Multi-step ranking of alternatives in a multi-criteria and multi-expert decision making environment
Information Sciences: an International Journal
| Hi-index | 0.00 |
We introduce and study a family of models for multiexpert multiobjective/criteria decision making. These models use a concept of weight robustness to generate a risk-averse decision. In particular, the multiexpert multicriteria robust weighted sum approach (McRow) introduced in this paper identifies a (robust) Pareto decision that minimizes the worst-case weighted sum of objectives over a given weight region. The corresponding objective value, called the robust value of a decision, is shown to be increasing and concave in the weight set. We study compact reformulations of the McRow model with polyhedral and conic descriptions of the weight regions. The McRow model is developed further for stochastic multiexpert multicriteria decision making by allowing ambiguity or randomness in the weight region as well as the objective functions. The properties of the proposed approach are illustrated with a few textbook examples. The usefulness of the stochastic McRow model is demonstrated using a disaster planning example and an agriculture revenue management example.