On fuzzy fractional quadratic programming problems with an application in the tourism sector

In the corporations working with logistics, many management issues involving optimization require fractional quadratic programming. Further, crisp parameters are unable to model the real life problems, where impreciseness is involved. In the present study, fuzzy fractional quadratic programming problem is studied using a hybrid method that combines analytic and numerical approaches. The original problem is converted to a crisp multiobjective problem, wherein the constraint coefficients are handled by variation of parameter technique through an interactive manner. The proposed method attempts to alleviate existing problems of straightforward conversion to a deterministic model by making constraint parameters vary as per α_r∈(0,1]. The flexibility of choices in constraint parameters with α_r=0 leading to best solution and α_r=1 resulting in worst solution, indicates the robust nature of proposed algorithm. The theorems have been constructed and proved to show the equivalence between the original and transformed problem. A numerical example and a transportation problem in tourism sector switching between both balanced and unbalanced cases is modelled and later solved using the proposed methodology.