Semistrictly quasiconvex mappings and non-convex vector optimization

Semistrictly quasiconvex mappings and non-convex vector optimization

0.00 Avg rating0 Votes
Article ID: iaor20051133
Country: Germany
Volume: 59
Issue: 1
Start Page Number: 129
End Page Number: 145
Publication Date: Jan 2004
Journal: Mathematical Methods of Operations Research (Heidelberg)
Authors:
Abstract:

This paper introduces a new class of non-convex vector functions strictly larger than that of P-quasiconvexity, with P ⊆ ℝm being the underlying order cone, called semistrictly (ℝm\ −int P)-quasiconvex functions. This notion allows us to unify various results on existence of weakly efficient (weakly Pareto) optima. By imposing a coercivity condition we establish also the compactness of the set of weakly Pareto solutions. In addition, we provide various characterizations for the non-emptiness, convexity and compactness of the solution set for a subclass of quasiconvex vector optimization problems on the real-line. Finally, it is also introduced the notion of explicit (ℝm\ −int P)-quasiconvexity (equivalently explicit (int P)-quasiconvexity) which plays the role of explicit quasiconvexity (quasiconvexity and semistrict quasiconvexity) of real-valued functions.

Reviews

Required fields are marked *. Your email address will not be published.