Quasi-Newton methods for solving multiobjective optimization

Shaojian Qu; Mark Goh; Tung Sun Chan

doi:10.1016/j.orl.2011.07.008

Quasi-Newton methods for solving multiobjective optimization

Shaojian Qu
, Mark Goh
, Tung Sun Chan

Research output: Journal article publication › Journal article › Academic research › peer-review

94 Citations (Scopus)

Abstract

This paper presents a quasi-Newton-type algorithm for nonconvex multiobjective optimization. In this algorithm, the iterations are repeated until termination conditions are met, which is when a suitable descent direction cannot be found anymore. Under suitable assumptions, global convergence is established.

Original language	English
Pages (from-to)	397-399
Number of pages	3
Journal	Operations Research Letters
Volume	39
Issue number	5
DOIs	https://doi.org/10.1016/j.orl.2011.07.008
Publication status	Published - 1 Sept 2011

Keywords

Critical point
Global convergence
Multiobjective optimization
Pareto optimality
Quasi-Newton methods

ASJC Scopus subject areas

Software
Management Science and Operations Research
Industrial and Manufacturing Engineering
Applied Mathematics

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10.1016/j.orl.2011.07.008

Cite this

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title = "Quasi-Newton methods for solving multiobjective optimization",

abstract = "This paper presents a quasi-Newton-type algorithm for nonconvex multiobjective optimization. In this algorithm, the iterations are repeated until termination conditions are met, which is when a suitable descent direction cannot be found anymore. Under suitable assumptions, global convergence is established.",

keywords = "Critical point, Global convergence, Multiobjective optimization, Pareto optimality, Quasi-Newton methods",

author = "Shaojian Qu and Mark Goh and Chan, \{Tung Sun\}",

year = "2011",

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doi = "10.1016/j.orl.2011.07.008",

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journal = "Operations Research Letters",

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AU - Goh, Mark

AU - Chan, Tung Sun

PY - 2011/9/1

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N2 - This paper presents a quasi-Newton-type algorithm for nonconvex multiobjective optimization. In this algorithm, the iterations are repeated until termination conditions are met, which is when a suitable descent direction cannot be found anymore. Under suitable assumptions, global convergence is established.

AB - This paper presents a quasi-Newton-type algorithm for nonconvex multiobjective optimization. In this algorithm, the iterations are repeated until termination conditions are met, which is when a suitable descent direction cannot be found anymore. Under suitable assumptions, global convergence is established.

KW - Critical point

KW - Global convergence

KW - Multiobjective optimization

KW - Pareto optimality

KW - Quasi-Newton methods

UR - https://www.scopus.com/pages/publications/80052568656

U2 - 10.1016/j.orl.2011.07.008

DO - 10.1016/j.orl.2011.07.008

M3 - Journal article

SN - 0167-6377

VL - 39

SP - 397

EP - 399

JO - Operations Research Letters

JF - Operations Research Letters

IS - 5

ER -

Quasi-Newton methods for solving multiobjective optimization

Abstract

Keywords

ASJC Scopus subject areas

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