Minimax programming as a tool for studying robust multi-objective optimization problems
This paper aims to investigate optimality conditions for a weakly Pareto solution to a robust multi-objective optimization problem with locally Lipschitzian data. We do this by using a minimax programming approach , namely, by establishing the necessary optimality condition for a (local) optimal sol...
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| Veröffentlicht in: | Annals of operations research 2022-12, Vol.319 (2), p.1589-1606 |
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| container_title | Annals of operations research |
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| creator | Hong, Zhe Bae, Kwan Deok Kim, Do Sang |
| description | This paper aims to investigate optimality conditions for a weakly Pareto solution to a robust multi-objective optimization problem with locally Lipschitzian data. We do this by using a
minimax programming approach
, namely, by establishing the necessary optimality condition for a (local) optimal solution to a robust
minimax
optimization problem under a suitable constraint qualification, we then employ it to arrive in the desired target. In addition, some duality results for both robust minimax optimization problems and robust multi-objective optimization problems are also provided. |
| doi_str_mv | 10.1007/s10479-021-04179-w |
| format | Article |
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minimax programming approach
, namely, by establishing the necessary optimality condition for a (local) optimal solution to a robust
minimax
optimization problem under a suitable constraint qualification, we then employ it to arrive in the desired target. In addition, some duality results for both robust minimax optimization problems and robust multi-objective optimization problems are also provided.</description><identifier>ISSN: 0254-5330</identifier><identifier>EISSN: 1572-9338</identifier><identifier>DOI: 10.1007/s10479-021-04179-w</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Applied mathematics ; Business and Management ; Combinatorics ; Game theory ; Integer programming ; Linear programming ; Mathematical optimization ; Mathematical programming ; Minimax technique ; Multiple objective analysis ; Operations research ; Operations Research/Decision Theory ; Optimization ; Original Research ; Pareto optimization ; Pareto principle ; Robustness (mathematics) ; Theory of Computation</subject><ispartof>Annals of operations research, 2022-12, Vol.319 (2), p.1589-1606</ispartof><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021</rights><rights>COPYRIGHT 2022 Springer</rights><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c353t-e76094a074dbdd1ef06ab49af0f68f618e9c1f2018a996bf8f5fc52b8172bfab3</citedby><cites>FETCH-LOGICAL-c353t-e76094a074dbdd1ef06ab49af0f68f618e9c1f2018a996bf8f5fc52b8172bfab3</cites><orcidid>0000-0003-4191-2295</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10479-021-04179-w$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10479-021-04179-w$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Hong, Zhe</creatorcontrib><creatorcontrib>Bae, Kwan Deok</creatorcontrib><creatorcontrib>Kim, Do Sang</creatorcontrib><title>Minimax programming as a tool for studying robust multi-objective optimization problems</title><title>Annals of operations research</title><addtitle>Ann Oper Res</addtitle><description>This paper aims to investigate optimality conditions for a weakly Pareto solution to a robust multi-objective optimization problem with locally Lipschitzian data. We do this by using a
minimax programming approach
, namely, by establishing the necessary optimality condition for a (local) optimal solution to a robust
minimax
optimization problem under a suitable constraint qualification, we then employ it to arrive in the desired target. In addition, some duality results for both robust minimax optimization problems and robust multi-objective optimization problems are also provided.</description><subject>Applied mathematics</subject><subject>Business and Management</subject><subject>Combinatorics</subject><subject>Game theory</subject><subject>Integer programming</subject><subject>Linear programming</subject><subject>Mathematical optimization</subject><subject>Mathematical programming</subject><subject>Minimax technique</subject><subject>Multiple objective analysis</subject><subject>Operations research</subject><subject>Operations Research/Decision Theory</subject><subject>Optimization</subject><subject>Original Research</subject><subject>Pareto optimization</subject><subject>Pareto principle</subject><subject>Robustness (mathematics)</subject><subject>Theory of Computation</subject><issn>0254-5330</issn><issn>1572-9338</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>N95</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kctq3TAQhkVJoCeXF8jK0G2djC627GUITVpI6KYhSyHZkquDbZ1q5Nyevjo9hSQQwoBmGL5_Bs1PyAmFUwogz5CCkG0JjJYgaK4ePpEVrSQrW86bPbICVomy4hw-kwPENQBQ2lQrcnfjZz_px2ITwxD1NPl5KDQWukghjIULscC09E_bdgxmwVRMy5h8Gczadsnf2yJskp_8s04-zNsxZrQTHpF9p0e0x__zIbm9_Pbr4nt5_fPqx8X5ddnxiqfSyhpaoUGK3vQ9tQ5qbUSrHbi6cTVtbNtRx4A2um1r4xpXua5ipqGSGacNPyRfdnPz4j-LxaTWYYlzXqmYFEAlF4K_UIMerfKzCynqbvLYqXPJZFtxWdeZOn2HytHbyXdhts7n_hvB11eCfBw_W8wP-uF3wkEviG9xtsO7GBCjdWoT8-3jk6KgtjaqnY0q26j-2agesojvRJjhebDx5YMfqP4CCrWg9A</recordid><startdate>20221201</startdate><enddate>20221201</enddate><creator>Hong, Zhe</creator><creator>Bae, Kwan Deok</creator><creator>Kim, Do Sang</creator><general>Springer US</general><general>Springer</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>N95</scope><scope>3V.</scope><scope>7TA</scope><scope>7TB</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88I</scope><scope>8AL</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>KR7</scope><scope>L.-</scope><scope>L6V</scope><scope>M0C</scope><scope>M0N</scope><scope>M2P</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0003-4191-2295</orcidid></search><sort><creationdate>20221201</creationdate><title>Minimax programming as a tool for studying robust multi-objective optimization problems</title><author>Hong, Zhe ; 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We do this by using a
minimax programming approach
, namely, by establishing the necessary optimality condition for a (local) optimal solution to a robust
minimax
optimization problem under a suitable constraint qualification, we then employ it to arrive in the desired target. In addition, some duality results for both robust minimax optimization problems and robust multi-objective optimization problems are also provided.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s10479-021-04179-w</doi><tpages>18</tpages><orcidid>https://orcid.org/0000-0003-4191-2295</orcidid></addata></record> |
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| subjects | Applied mathematics Business and Management Combinatorics Game theory Integer programming Linear programming Mathematical optimization Mathematical programming Minimax technique Multiple objective analysis Operations research Operations Research/Decision Theory Optimization Original Research Pareto optimization Pareto principle Robustness (mathematics) Theory of Computation |
| title | Minimax programming as a tool for studying robust multi-objective optimization problems |
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