Goberna, Miguel A., Kanzi, Nader
Optimality conditions in convex multiobjective SIP
Mathematical Programming. 2017, 164(1): 167-191. doi:10.1007/s10107-016-1081-8
URI: http://hdl.handle.net/10045/67476
DOI: 10.1007/s10107-016-1081-8
ISSN: 0025-5610 (Print)
Abstract: 
The purpose of this paper is to characterize the weak efficient solutions, the efficient solutions, and the isolated efficient solutions of a given vector optimization problem with finitely many convex objective functions and infinitely many convex constraints. To do this, we introduce new and already known data qualifications (conditions involving the constraints and/or the objectives) in order to get optimality conditions which are expressed in terms of either Karusk–Kuhn–Tucker multipliers or a new gap function associated with the given problem.
Keywords:Multi-objective and goal programming, Optimality conditions, duality, Convex programming
Springer Berlin Heidelberg
info:eu-repo/semantics/article