Fuzzy-Control-Based Chance-Constrained Programming for Humanitarian Relief Allocation Problem

In this article, the issue of multicenter and single-area humanitarian relief allocation with uncertain travel time and imprecise transportation information is investigated. Expert human knowledge using fuzzy control is employed to select rescue paths, and the considered problem is formulated as a fuzzy chance-constrained model to ensure that the allocated goods can be delivered to the disaster area on time within a desired probability. A new method is presented to transform chance-constrained programming into a mixed-integer model utilizing triangle fuzzy numbers and the robust optimization problem. A practical example is used to test the validity of the theoretic results obtained.