A Proximal Method for Multiobjective Quasiconvex Minimization on the Nonnegative Orthant and its Application to Demand Theory in Microeconomy

Erik Alex Papa Quiroz, Dante Borda Marcatinco, Frank Collantes Sánchez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper we propose an inexact proximal point method to solve multiobjective minimization problems with locally Lipschitz quasiconvex objective functions on the nonnegative orthant. Assuming that the function is also bounded from below, lower semicontinuous and using proximal distances, we obtain the convergence of the sequences generated by the algorithm. We give some computational results and an application to demand theory is presented.

Original languageEnglish
Title of host publicationProceedings of the 2020 3rd International Conference on Robot Systems and Applications, ICRSA 2020
PublisherAssociation for Computing Machinery
Pages75-81
Number of pages7
ISBN (Electronic)9781450387644
DOIs
StatePublished - 14 Jun 2020
Event3rd International Conference on Robot Systems and Applications, ICRSA 2020 - Chengdu, China
Duration: 14 Jun 202016 Jun 2020

Publication series

NameACM International Conference Proceeding Series

Conference

Conference3rd International Conference on Robot Systems and Applications, ICRSA 2020
Country/TerritoryChina
CityChengdu
Period14/06/2016/06/20

Bibliographical note

Publisher Copyright:
© 2020 ACM.

Keywords

  • Microeconomy
  • nonnegative orthant
  • proximal method
  • quasiconvex multiobjective minimization

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