on ‎t‎he fractional minimal cost flow problem of a belief degree based uncertain network‎

A fractional minimal cost ow problem under linear type belief degree based uncertainty is studied for the first time. this type of uncertainty is useful when no historical information of an uncertain event is available. the problem is crisped using an uncertain chance-constrained programming approach and its non-linear objective function is linearized by a variable changing approach. an illustrative example is solved to prove the efficiency of the proposed formulation.