Using the WOWA criterion for two-stage decision making problems

TL;DR

This paper introduces the application of the WOWA aggregation criterion to two-stage decision making problems under uncertainty, providing decomposition algorithms and demonstrating their effectiveness on location-transportation problems with uncertain demands.

Contribution

It presents novel decomposition algorithms for two-stage problems using the WOWA criterion, extending decision-making methods under uncertainty.

Findings

Algorithms effectively solve location-transportation problems with uncertain demands.

WOWA generalizes many decision criteria under uncertainty.

Computational results validate the approach.

Abstract

The weighted OWA (WOWA) is a function that aggregates a set of values with weights assigned based on the rank and relative importance of each value. The weighted OWA of uncertain objective functions can generalize many of the criteria that is used in decision making under uncertainty. In this paper, we apply the WOWA criterion to two-stage decision making problems, and present decomposition algorithms to solve them. The algorithms are applied to location-transportation problem with uncertain demands and computational results are presented.