{"title":"Analysis of Subdifferentials of Marginal and Performance Functions","authors":"Duong Thi Viet An, Jean-Paul Penot","doi":"10.1007/s00245-025-10251-9","DOIUrl":null,"url":null,"abstract":"<div><p>We study generalized derivatives of value functions for optimization problems depending on a parameter <i>w</i>. Interpretations of the results obtained with these substitutes to derivatives are known to be important. We endeavour to answer the question: can one obtain these results without knowing the nature of these substitutes and their constructions? Is there a means to obtain them in a unified way?</p></div>","PeriodicalId":55566,"journal":{"name":"Applied Mathematics and Optimization","volume":"91 3","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Mathematics and Optimization","FirstCategoryId":"100","ListUrlMain":"https://link.springer.com/article/10.1007/s00245-025-10251-9","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
We study generalized derivatives of value functions for optimization problems depending on a parameter w. Interpretations of the results obtained with these substitutes to derivatives are known to be important. We endeavour to answer the question: can one obtain these results without knowing the nature of these substitutes and their constructions? Is there a means to obtain them in a unified way?
期刊介绍:
The Applied Mathematics and Optimization Journal covers a broad range of mathematical methods in particular those that bridge with optimization and have some connection with applications. Core topics include calculus of variations, partial differential equations, stochastic control, optimization of deterministic or stochastic systems in discrete or continuous time, homogenization, control theory, mean field games, dynamic games and optimal transport. Algorithmic, data analytic, machine learning and numerical methods which support the modeling and analysis of optimization problems are encouraged. Of great interest are papers which show some novel idea in either the theory or model which include some connection with potential applications in science and engineering.