In the present paper, two types of second order dual models are formulated for a minmax fractional programming problem. The concept of η-bonvexity/ generalized η-bonvexity is adopted in order to discuss weak, strong and strict converse duality theorems.

In this paper, we start our discussion with a pair of multiobjective MondWeir type second-order symmetric dual fractional programming problem and derive weak, strong and strict duality theorems under second-order (φ, ρ)-invexity assumptions.

subject to Gj(x, t) ≤ 0 for all t ∈ Tj , j ∈ q, Hk(x, s) = 0 for all s ∈ Sk, k ∈ r, x ∈ X, where q and r are positive integers, X is a nonempty open convex subset of Rn (n-dimensional Euclidean space), for each j ∈ q ≡ {1, 2, . . . , q} and k ∈ r, Tj and Sk are compact subsets of complete metric spaces, f and g are real-valued functions defined on X, for each j ∈ q, z → Gj(z, t) is a real-value...

In this paper, we introduce a fractional domination game arising from fractional domination problems on graphs and focus on its balancedness and concavity. We first characterize the core of the fractional domination game and show that its core is always non-empty taking use of dual theory of linear programming. Furthermore we study concavity of this game.

This paper presents alternatives to Lavine's algorithm, currently the most popular method for calculation of expectation bounds induced by sets of probability distributions. The White-Snow algorithm is rst analyzed and demonstrated to be superior to Lavine's algorithm in a variety of situations. The calculation of posterior bounds is then reduced to a fractional programming problem. From the un...

In this paper, the concept of ∂-quasiconvexity is introduced by using convexifactors. Mond-Weir-type and Schaible-type duals are associated with a multiobjective fractional programming problem, and various duality results are established under the assumptions of ∂-pseudoconvexity and ∂-quasiconvexity.

The purpose of this paper is to develop a fairly large number of sets of global parametric sufficient optimality conditions under various generalized (F, b, φ, ρ, θ)univexity assumptions for a continuous minmax fractional programming problem involving arbitrary norms.

For some management programming problems, multiple objectives to be optimized rather than a single objective, and objectives can be expressed with ratio equations such as return/investment, operating profit/net-sales, profit/manufacturing cost, etc. In this paper, we proposed the transformation characteristics to solve the multi objective linear fractional programming (MOLFP) problems. If a MOL...