3 papers
math.OC2026
IPAS: An Adaptive Sample Size Method for Weighted Finite Sum Problems with Linear Equality Constraints
NataÅ¡a KrejiÄ, NataÅ¡a Krklec JerinkiÄ, Sanja RapajiÄ +1
Optimization problems with the objective function in the form of weighted sum and linear equality constraints are considered. Given that the number of local cost functions can be l…
math.OC2026
SMOP: Stochastic trust region method for multi-objective problems
NataÅ¡a KrejiÄ, NataÅ¡a Krklec JerinkiÄ, Luka RuteÅ¡iÄ
The problem we consider is a multi-objective optimization problem, in which the goal is to find an optimal value of a vector function representing various criteria. The aim of this…
math.OC2026
ASMOP: Additional sampling stochastic trust region method for multi-objective problems
NataÅ¡a Krklec JerinkiÄ, Luka RuteÅ¡iÄ, Ilaria Trombini
We consider unconstrained multi-criteria optimization problems with finite sum objective functions. The proposed algorithm belongs to a non-monotone trust region framework where ad…