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A first-order regularized approach to the order-value optimization problem

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Author(s):
Alvarez, G. Q. ; Birgin, E. G.
Total Authors: 2
Document type: Journal article
Source: OPTIMIZATION METHODS & SOFTWARE; v. N/A, p. 25-pg., 2025-02-12.
Abstract

Minimization of the order-value function is part of a large family of problems involving functions whose value is calculated by sorting values from a set or subset of other functions. The order-value function has as particular cases the minimum and maximum functions of a set of functions and is well suited for applications involving robust estimation. In this paper, a first-order method with quadratic regularization to solve the problem of minimizing the order-value function is proposed. An optimality condition for the problem and theoretical results of iteration complexity and evaluation complexity for the proposed method are presented. The applicability of the problem and method to parameter estimation problems with outliers is illustrated. (AU)

FAPESP's process: 23/08706-1 - Numerical optimization
Grantee:Ernesto Julián Goldberg Birgin
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 22/05803-3 - Cutting, packing, lot-sizing, scheduling, routing and location problems and their integration in industrial and logistics settings
Grantee:Reinaldo Morabito Neto
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:Francisco Louzada Neto
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC