A Survey on Proximal Point Type Algorithms for Solving Vector Optimization Problems

Sorin Mihai Grad

doi:10.1007/978-3-030-25939-6_11

A Survey on Proximal Point Type Algorithms for Solving Vector Optimization Problems

Sorin Mihai Grad

C/o Faculty of Mathematics of the University of Vienna

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

8 Citations (Scopus)

Abstract

In this survey paper we present the existing generalizations of the proximal point method from scalar to vector optimization problems, discussing some of their advantages and drawbacks, respectively, presenting some open challenges and sketching some possible directions for future research.

Original language	English
Title of host publication	Splitting Algorithms, Modern Operator Theory, and Applications
Publisher	Springer International Publishing
Pages	269-308
Number of pages	40
ISBN (Electronic)	9783030259396
ISBN (Print)	9783030259389
DOIs	https://doi.org/10.1007/978-3-030-25939-6_11
Publication status	Published - 1 Jan 2019
Externally published	Yes

Keywords

Efficient solution
Multiobjective optimization problem
Proximal point algorithm
Scalarization function
Splitting method
Vector function
Vector optimization problem
Weakly efficient solution

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10.1007/978-3-030-25939-6_11

Cite this

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title = "A Survey on Proximal Point Type Algorithms for Solving Vector Optimization Problems",

abstract = "In this survey paper we present the existing generalizations of the proximal point method from scalar to vector optimization problems, discussing some of their advantages and drawbacks, respectively, presenting some open challenges and sketching some possible directions for future research.",

keywords = "Efficient solution, Multiobjective optimization problem, Proximal point algorithm, Scalarization function, Splitting method, Vector function, Vector optimization problem, Weakly efficient solution",

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AB - In this survey paper we present the existing generalizations of the proximal point method from scalar to vector optimization problems, discussing some of their advantages and drawbacks, respectively, presenting some open challenges and sketching some possible directions for future research.

KW - Efficient solution

KW - Multiobjective optimization problem

KW - Proximal point algorithm

KW - Scalarization function

KW - Splitting method

KW - Vector function

KW - Vector optimization problem

KW - Weakly efficient solution

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EP - 308

BT - Splitting Algorithms, Modern Operator Theory, and Applications

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ER -

A Survey on Proximal Point Type Algorithms for Solving Vector Optimization Problems

Abstract

Keywords

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