Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 정인재 | - |
dc.date.accessioned | 2022-11-02T06:50:46Z | - |
dc.date.available | 2022-11-02T06:50:46Z | - |
dc.date.issued | 2021-02 | - |
dc.identifier.citation | ENGINEERING OPTIMIZATION, v. 53, no. 2, page. 185-205 | en_US |
dc.identifier.issn | 0305-215X; 1029-0273 | en_US |
dc.identifier.uri | https://www.tandfonline.com/doi/full/10.1080/0305215X.2019.1698035 | en_US |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/176244 | - |
dc.description.abstract | This article considers linear multi-objective programming problems with block angular structure, which are analogous to multi-disciplinary optimization environments where disciplines must collaborate to achieve a common overall goal. In this decentralized environment, a mechanism to guide locally optimized decision makers’ solutions to a Pareto-optimal solution without sharing the entire local information is developed. The mechanism is based on an augmented Lagrangian approach to generate a solution and is separated into two phases: phase I determines an ideal point for each of the single objectives and phase II searches for a compromise solution starting from a single ideal point. Theoretical results show that the algorithm converges and the solution generated is Pareto optimal. The algorithm’s effectiveness is demonstrated via an illustrative example and a real-world bi-objective re-entrant flow-shop production planning problem. The real-world experimental results showed that the decentralized method had an average 50% better performance compared to other centralized methods. | en_US |
dc.description.sponsorship | This work was supported by the Basic Science Research Program through the National Research Foundation of Korea, funded by theMinistry of Education [grant number 2014R1A1A2058147] and theMinistry of Science, ICT and Future Planning (grant number 2017R1E1A1A03070435). | en_US |
dc.language | en | en_US |
dc.publisher | TAYLOR & FRANCIS LTD | en_US |
dc.subject | Collaborative optimization; decentralized coordination; multi-objective linear programming; block angular structure; multi-agent | en_US |
dc.title | A decentralized coordination algorithm for multi-objective linear programming with block angular structure | en_US |
dc.type | Article | en_US |
dc.relation.no | 2 | - |
dc.relation.volume | 53 | - |
dc.identifier.doi | 10.1080/0305215X.2019.1698035 | en_US |
dc.relation.page | 185-205 | - |
dc.relation.journal | ENGINEERING OPTIMIZATION | - |
dc.contributor.googleauthor | Okpoti, Evans Sowah | - |
dc.contributor.googleauthor | Jeong, In-Jae | - |
dc.relation.code | 2021001063 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | DEPARTMENT OF INDUSTRIAL ENGINEERING | - |
dc.identifier.pid | ijeong | - |
dc.identifier.orcid | https://orcid.org/0000-0001-7824-6391 | - |
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