Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 이동희 | - |
dc.date.accessioned | 2019-11-26T06:15:49Z | - |
dc.date.available | 2019-11-26T06:15:49Z | - |
dc.date.issued | 2017-06 | - |
dc.identifier.citation | 대한산업공학회지, v. 43, no. 3, page. 164-175 | en_US |
dc.identifier.issn | 1225-0988 | - |
dc.identifier.issn | 2234-6457 | - |
dc.identifier.uri | http://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE07183377 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/114666 | - |
dc.description.abstract | Dual response surface optimization (DRSO) attempts to optimize mean and variability of a process response variable using a response surface methodology. In general, mean and variability of the response variable are often in conflict. In such a case, the process engineer need to understand the tradeoffs between the mean and variability in order to obtain a satisfactory solution. Recently, a Posterior preference articulation approach to DRSO (P-DRSO) has been proposed. P-DRSO generates a number of non-dominated solutions and allows the process engineer to select the most preferred solution. By observing the non-dominated solutions, the DM can explore and better understand the trade-offs between the mean and variability. However, the non-dominated solutions generated by the existing P-DRSO is often incomprehensive and unevenly distributed which limits the practicability of the method. In this regard, we propose a modified P-DRSO using multiple objective genetic algorithms. The proposed method has an advantage in that it generates comprehensive and evenly distributed non-dominated solutions. | en_US |
dc.description.sponsorship | 이 논문은 2015년도 정부(미래창조과학부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(No. NRF-2015R1C1A1A01051952). | en_US |
dc.language.iso | ko_KR | en_US |
dc.publisher | 대한산업공학회 | en_US |
dc.subject | Response Surface Methodology | en_US |
dc.subject | Dual Response Surface Optimization | en_US |
dc.subject | Multiple Objective Genetic Algorithm | en_US |
dc.subject | Posterior Preference Articulation Approach | en_US |
dc.title | 다목적 유전 알고리즘을 이용한 쌍대반응표면최적화 | en_US |
dc.title.alternative | Dual Response Surface Optimization using Multiple Objective Genetic Algorithms | en_US |
dc.type | Article | en_US |
dc.relation.no | 3 | - |
dc.relation.volume | 43 | - |
dc.identifier.doi | 10.7232/JKIIE.2017.43.3.164 | - |
dc.relation.page | 164-175 | - |
dc.relation.journal | 대한산업공학회지 | - |
dc.contributor.googleauthor | 이동희 | - |
dc.contributor.googleauthor | 김보라 | - |
dc.contributor.googleauthor | 양진경 | - |
dc.contributor.googleauthor | 오선혜 | - |
dc.contributor.googleauthor | Lee, Dong-Hee | - |
dc.contributor.googleauthor | Kim, Bo-Ra | - |
dc.contributor.googleauthor | Yang, Jin-Kyung | - |
dc.contributor.googleauthor | Oh, Seon-Hye | - |
dc.relation.code | 2017019037 | - |
dc.sector.campus | S | - |
dc.sector.daehak | DIVISION OF INDUSTRIAL INFORMATION STUDIES[S] | - |
dc.sector.department | DIVISION OF INDUSTRIAL INFORMATION STUDIES | - |
dc.identifier.pid | dh | - |
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