We consider the min-max fractional programming problem in which it is necessary to find ν∗ = f(x∗) = min x∈S max i∈I φi(x) ψi(x) , (1) where φi(x), i ∈ I;−ψi(x), i ∈ I are convex functions in Rn and φi(x) ≥ 0, i ∈ I. Additionally ψi(x) > 0, i ∈ I for x ∈ S, where S = {x : hk(x) ≤ 0,k = 1,p}. For studying and solving this problem we use the following two problems: 1. The generalized fractional-convex programming problem ν∗ = f(x∗) = min x∈S max i∈I  i∈I uiφi(x)  i∈I uiψi(x) , where U = {u ∈ Rm : m i=1 ui = 1; ui ≥ 0, i = 1,m}; 2. The parametric programming problem F(u, ν) = min x∈S  Z(x, u, ν) =  i∈I ui(φi(x) − νψi(x))  .Using these auxiliary problems a special decomposition scheme and subgradient methods for solving problem (1) have been elaborated. Some approaches for studying and solving these class of problems are analysed in [1].