Optimization in Data Science – Page 9

Stochastic nested primal-dual method for nonconvex constrained composition optimization

Published: 2022/08/14, Updated: 2024/04/29

Constrained Nonlinear Optimization, Data Science Algorithms, Stochastic Programming augmented Lagrangian function, complementary slackness, composition, feasibility, iteration complexity, nonconvex constraints, sample complexity, stationarity

\(\) In this paper we study the nonconvex constrained composition optimization, in which the objective contains a composition of two expected-value functions whose accurate information is normally expensive to calculate. We propose a STochastic nEsted Primal-dual (STEP) method for such problems. In each iteration, with an auxiliary variable introduced to track the inner layer function … Read more

Computing Tchebychev weight space decomposition for multiobjective discrete optimization problems

Published: 2022/08/04

Tyler Perini

Integer Programming, Multi-Criteria Optimization, Optimization in Data Science multiobjective optimization, Tchebychev scalarization, triobjective discrete optimization, weight space decomposition

Multiobjective discrete optimization (MODO) techniques, including weight space decomposition, have received increasing attention in the last decade. The primary weight space decomposition technique in the literature is defined for the weighted sum utility function, through which sets of weights are assigned to a subset of the nondominated set. Recent work has begun to study the … Read more