On the stability for parametric set optimization problems via improvement sets without the strict convexity

In this paper, we aim to discuss the stability of parametric set optimization problems via improvement sets.First, we establish some convergence results for set-valued mappings.Next, under new assumptions, the Berge upper and lower semicontinuity of upper level mappings for parametric set optimization problems with the upper relation are investigated.Then, under suitable assumptions, the sufficient conditions for Berge upper and lower semicontinuity of (weak) minimal solution mappings for parametric set optimization problems via improvement sets are established.

Publication Details

Journal
Journal of Nonlinear and Variational Analysis
Published
2025-05-20
DOI
https://doi.org/10.23952/jnva.9.2025.5.01
Primary Topic
Optimization and Variational Analysis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

On the stability for parametric set optimization problems via improvement sets without the strict convexity

Journal of Nonlinear and Variational Analysis
Optimization and Variational Analysis
article

On the stability for parametric set optimization problems via improvement sets without the strict convexity

article en

Abstract

In this paper, we aim to discuss the stability of parametric set optimization problems via improvement sets.First, we establish some convergence results for set-valued mappings.Next, under new assumptions, the Berge upper and lower semicontinuity of upper level mappings for parametric set optimization problems with the upper relation are investigated.Then, under suitable assumptions, the sufficient conditions for Berge upper and lower semicontinuity of (weak) minimal solution mappings for parametric set optimization problems via improvement sets are established.

Journal of Nonlinear and Variational AnalysisVol. 9(5)
National Natural Science Foundation of China, Centre Scientifique et Technique du Bâtiment, Shenzhen Research Institute of Big Data, Shenzhen Research Institute, City University of Hong Kong
Openalex Percentile: Top 88%
Optimization and Variational Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.