Optimality and duality for the multiobjective fractional programming with the generalized (F,ρ) convexity
暂无分享,去创建一个
Abstract A class of multiobjective fractional programmings (MFP) are first formulated, where the involved functions are local Lipschitz and Clarke subdifferentiable. In order to deduce our main results, we give the definitions of the generalized ( F , ρ ) convex class about the Clarke subgradient. Under the above generalized convexity assumption, the alternative theorem is obtained, and some sufficient and necessary conditions for optimality are also given related to the properly efficient solution for the problems. Finally, we formulate the two dual problems (MD) and (MD1) corresponding to (MFP), and discuss the week, strong and reverse duality.
[1] Frank H. Clarke,et al. A New Approach to Lagrange Multipliers , 1976, Math. Oper. Res..
[2] F. Clarke. Optimization And Nonsmooth Analysis , 1983 .
[3] P. Kanniappan,et al. Necessary conditions for optimality of nondifferentiable convex multiobjective programming , 1983 .
[4] V. Jeyakumar. Equivalence of saddle-points and optima, and duality for a class of non-smooth non-convex problems , 1988 .