The multi-objective semi-infinite fractional optimization problem with uncertain information is studied. The robust correspondence model is transformed into a general multi-objective optimization problem by means of a newly defined vector arithmetic relation, and the relationship between the two is presented. The optimality conditions for uncertain multi-objective semi-infinite fractional programming are studied through the robust subdifferential constraint specifications and generalized convex functions, and the corresponding mixed duality is also studied. The results of the study mainly improve the necessary optimality conditions for semi-infinite fractional programming and study the sufficient conditions under the new defined type-I function condition.
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