Aircraft conceptual design by genetic/gradient-guided optimization
In the present article, which describes the results of a Ph.D. research study (Bos, A.H.W., 1996a. Multidisciplinary Design Optimization of a Second-Generation Supersonic Transport Aircraft using a Hybrid Genetic/Gradient-guided Algorithm., Ph.D. Dissertation, Delft University of Technology, Bos, A....
Saved in:
| Published in | Engineering applications of artificial intelligence Vol. 11; no. 3; pp. 377 - 382 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.06.1998
|
| Subjects | |
| Online Access | Get full text |
| ISSN | 0952-1976 1873-6769 |
| DOI | 10.1016/S0952-1976(98)00009-8 |
Cover
| Abstract | In the present article, which describes the results of a Ph.D. research study (Bos, A.H.W., 1996a. Multidisciplinary Design Optimization of a Second-Generation Supersonic Transport Aircraft using a Hybrid Genetic/Gradient-guided Algorithm., Ph.D. Dissertation, Delft University of Technology, Bos, A.H.W., 1996b. Multidisciplinary Design Optimization of a Supersonic Transport Aircraft using a Hybrid Genetic/Guided-based Algorithm. AIAA 96-4055), a new design procedure based on the combination of a genetic and a gradient-guided optimization algorithm is presented. The procedure was applied to the design of a second-generation supersonic transport aircraft since the interdisciplinary couplings are particularly strong for this kind of aeroplane. Furthermore, since the design space for the defined design problem is extremely small (and even non-existent in cases where all the environmental constraints are imposed) it is very hard—if not impossible—to realize a feasible design by means of classic design procedures.
It was established that the method presented here can actually be used as a practical design tool, since it is capable of generating a feasible design from scratch without the necessity to create a baseline design first. The optimization methods minimize constraint violations, and thus actually create a design instead of just adapting a baseline designed according to more traditional methods. |
|---|---|
| AbstractList | In the present article, which describes the results of a Ph.D. research study (Bos, A.H.W., 1996a. Multidisciplinary Design Optimization of a Second-Generation Supersonic Transport Aircraft using a Hybrid Genetic/Gradient-guided Algorithm., Ph.D. Dissertation, Delft University of Technology, Bos, A.H.W., 1996b. Multidisciplinary Design Optimization of a Supersonic Transport Aircraft using a Hybrid Genetic/Guided-based Algorithm. AIAA 96-4055), a new design procedure based on the combination of a genetic and a gradient-guided optimization algorithm is presented. The procedure was applied to the design of a second-generation supersonic transport aircraft since the interdisciplinary couplings are particularly strong for this kind of aeroplane. Furthermore, since the design space for the defined design problem is extremely small (and even non-existent in cases where all the environmental constraints are imposed) it is very hard—if not impossible—to realize a feasible design by means of classic design procedures.
It was established that the method presented here can actually be used as a practical design tool, since it is capable of generating a feasible design from scratch without the necessity to create a baseline design first. The optimization methods minimize constraint violations, and thus actually create a design instead of just adapting a baseline designed according to more traditional methods. |
| Author | Bos, A.H.W |
| Author_xml | – sequence: 1 givenname: A.H.W surname: Bos fullname: Bos, A.H.W organization: Delft University of Technology, Kluyverweg 1, 2629 HS, Delft, The Netherlands |
| BookMark | eNqFkE1LAzEQhoNUsK3-BGGPeojNx242wYPU4hcUPKjnkE0mS6TdLdlUqL_e7VY8eOlc5vI-LzPPBI2atgGELim5oYSK2RtRBcNUleJKyWvSj8LyBI2pLDkWpVAjNP6LnKFJ1332GS5zMUb38xBtND5ltm0sbNLWrDIHXaibrNplNTSQgp3V0bgATcL1NjhwWbtJYR2-TQptc45OvVl1cPG7p-jj8eF98YyXr08vi_kSW07KhAvOFTfAQAKvmM9ZrggX1JvKVIoaLz1nzJROEWkM82VOmSi4IK7IgTNF-RTdHnptbLsugtc2pOGCFE1YaUr0XocedOj9r1pJPejQsqeLf_QmhrWJu6Pc3YGD_rWvAFF3tjdhwYUINmnXhiMNP3aDegE |
| CitedBy_id | crossref_primary_10_1007_s10796_008_9112_5 crossref_primary_10_1016_j_ast_2017_02_016 crossref_primary_10_1016_j_compstruct_2013_04_025 crossref_primary_10_1002_cae_22216 crossref_primary_10_2514_1_J051835 crossref_primary_10_2208_jscej_2000_658_93 crossref_primary_10_1016_j_ast_2014_06_012 crossref_primary_10_3724_SP_J_1249_2013_02173 crossref_primary_10_1016_j_asoc_2017_09_030 crossref_primary_10_1088_0964_1726_19_4_045007 crossref_primary_10_1016_j_enconman_2019_01_098 crossref_primary_10_1016_j_aei_2007_10_001 crossref_primary_10_1016_j_asr_2014_10_027 crossref_primary_10_1080_10426910802612270 crossref_primary_10_1016_j_ast_2020_106440 crossref_primary_10_1007_s00500_015_1651_3 crossref_primary_10_3390_aerospace9030160 |
| Cites_doi | 10.2514/6.1996-4055 |
| ContentType | Journal Article |
| Copyright | 1998 Elsevier Science Ltd |
| Copyright_xml | – notice: 1998 Elsevier Science Ltd |
| DBID | AAYXX CITATION |
| DOI | 10.1016/S0952-1976(98)00009-8 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Applied Sciences Computer Science |
| EISSN | 1873-6769 |
| EndPage | 382 |
| ExternalDocumentID | 10_1016_S0952_1976_98_00009_8 S0952197698000098 |
| GroupedDBID | --K --M .DC .~1 0R~ 1B1 1~. 1~5 29G 4.4 457 4G. 5GY 5VS 7-5 71M 8P~ 9JN AABNK AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AAXUO AAYFN ABBOA ABMAC ABXDB ABYKQ ACDAQ ACGFS ACNNM ACRLP ACZNC ADBBV ADEZE ADJOM ADMUD ADTZH AEBSH AECPX AEKER AENEX AFKWA AFTJW AGHFR AGUBO AGYEJ AHHHB AHJVU AHZHX AIALX AIEXJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD ASPBG AVWKF AXJTR AZFZN BJAXD BKOJK BLXMC CS3 DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 F5P FDB FEDTE FGOYB FIRID FNPLU FYGXN G-2 G-Q GBLVA GBOLZ HLZ HVGLF HZ~ IHE J1W JJJVA KOM LG9 LY7 M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 R2- RIG ROL RPZ SBC SDF SDG SDP SES SET SEW SPC SPCBC SST SSV SSZ T5K TN5 UHS WUQ ZMT ~G- AATTM AAXKI AAYWO AAYXX ABJNI ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP CITATION EFKBS ~HD |
| ID | FETCH-LOGICAL-c307t-53393ae2e8e3b2f42490361fabab91af8f322a7d908aa2f741265360d54e32913 |
| IEDL.DBID | AIKHN |
| ISSN | 0952-1976 |
| IngestDate | Wed Oct 01 01:50:51 EDT 2025 Thu Apr 24 22:54:33 EDT 2025 Fri Feb 23 02:26:51 EST 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 3 |
| Keywords | multidisciplinary design optimization computer aided design genetic algorithms |
| Language | English |
| License | https://www.elsevier.com/tdm/userlicense/1.0 |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c307t-53393ae2e8e3b2f42490361fabab91af8f322a7d908aa2f741265360d54e32913 |
| PageCount | 6 |
| ParticipantIDs | crossref_citationtrail_10_1016_S0952_1976_98_00009_8 crossref_primary_10_1016_S0952_1976_98_00009_8 elsevier_sciencedirect_doi_10_1016_S0952_1976_98_00009_8 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 1900 |
| PublicationDate | 1998-06-01 |
| PublicationDateYYYYMMDD | 1998-06-01 |
| PublicationDate_xml | – month: 06 year: 1998 text: 1998-06-01 day: 01 |
| PublicationDecade | 1990 |
| PublicationTitle | Engineering applications of artificial intelligence |
| PublicationYear | 1998 |
| Publisher | Elsevier Ltd |
| Publisher_xml | – name: Elsevier Ltd |
| References | Sobieszczanski-Sobieski, J., 1982. A Linear Decomposition Method for Large Optimization Problems—Blueprint for Development. NASA TM 83248 Bos, A.H.W., 1996b. Multidisciplinary Design Optimization of a Supersonic Transport Aircraft using a Hybrid Genetic/Gradient-Based Algorithm. AIAA 96-4055 Grefenstette, J.J., 1990. A User’s Guide to GENESIS. Version 5.0 Goldberg, D.E., 1989. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading, U.S.A. Bos, A.H.W., 1996a. Multidisciplinary Design Optimization of a Second-Generation Supersonic Transport Aircraft using a Hybrid Genetic/Gradient-guided Algorithm. Ph.D. dissertation, Delft University of Technology Sobieszczanski-Sobieski, J., 1988. Optimization by Decomposition: a Step from Hierarchic to Non-hierarchic Systems. NASA CP-3031 part 1 10.1016/S0952-1976(98)00009-8_BIB3 10.1016/S0952-1976(98)00009-8_BIB4 10.1016/S0952-1976(98)00009-8_BIB5 10.1016/S0952-1976(98)00009-8_BIB6 10.1016/S0952-1976(98)00009-8_BIB1 10.1016/S0952-1976(98)00009-8_BIB2 |
| References_xml | – reference: Bos, A.H.W., 1996a. Multidisciplinary Design Optimization of a Second-Generation Supersonic Transport Aircraft using a Hybrid Genetic/Gradient-guided Algorithm. Ph.D. dissertation, Delft University of Technology – reference: Goldberg, D.E., 1989. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading, U.S.A. – reference: Sobieszczanski-Sobieski, J., 1982. A Linear Decomposition Method for Large Optimization Problems—Blueprint for Development. NASA TM 83248 – reference: Sobieszczanski-Sobieski, J., 1988. Optimization by Decomposition: a Step from Hierarchic to Non-hierarchic Systems. NASA CP-3031 part 1 – reference: Bos, A.H.W., 1996b. Multidisciplinary Design Optimization of a Supersonic Transport Aircraft using a Hybrid Genetic/Gradient-Based Algorithm. AIAA 96-4055 – reference: Grefenstette, J.J., 1990. A User’s Guide to GENESIS. Version 5.0 – ident: 10.1016/S0952-1976(98)00009-8_BIB5 – ident: 10.1016/S0952-1976(98)00009-8_BIB6 – ident: 10.1016/S0952-1976(98)00009-8_BIB2 doi: 10.2514/6.1996-4055 – ident: 10.1016/S0952-1976(98)00009-8_BIB4 – ident: 10.1016/S0952-1976(98)00009-8_BIB1 doi: 10.2514/6.1996-4055 – ident: 10.1016/S0952-1976(98)00009-8_BIB3 |
| SSID | ssj0003846 |
| Score | 1.6143973 |
| Snippet | In the present article, which describes the results of a Ph.D. research study (Bos, A.H.W., 1996a. Multidisciplinary Design Optimization of a Second-Generation... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 377 |
| SubjectTerms | computer aided design genetic algorithms multidisciplinary design optimization |
| Title | Aircraft conceptual design by genetic/gradient-guided optimization |
| URI | https://dx.doi.org/10.1016/S0952-1976(98)00009-8 |
| Volume | 11 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: Elsevier SD Complete Freedom Collection [SCCMFC] customDbUrl: eissn: 1873-6769 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0003846 issn: 0952-1976 databaseCode: ACRLP dateStart: 19950201 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection customDbUrl: eissn: 1873-6769 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0003846 issn: 0952-1976 databaseCode: .~1 dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection customDbUrl: eissn: 1873-6769 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0003846 issn: 0952-1976 databaseCode: AIKHN dateStart: 19950201 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier – providerCode: PRVLSH databaseName: Elsevier Journals customDbUrl: mediaType: online eissn: 1873-6769 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0003846 issn: 0952-1976 databaseCode: AKRWK dateStart: 19880301 isFulltext: true providerName: Library Specific Holdings |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV07T8MwED71sbDwRpRHlYEBBrdJnDT2WCqqQkUHoKJbZCdOVQnaKqQDC7-dc-K0ICGQmBKdcqfo7Lv7bN1nA1wkVESRmwTERixKNGAn0pcxETF3pUcVtZXeGrgfdQZj727iTyrQK7kwuq3S5P4ip-fZ2kjaxpvt5WzWfkRwgOEWdDjLgQ6rQh3rD2M1qHdvh4PROiFTVvB18HuiFTZEnsJILrzk7Cq3Q9jPJepL2envwrbBi1a3-KU9qKj5PuwY7GiZyHxDUXk9Qyk7gOvuLI1SkWRWVHATV2gozjs2LPlu4czRBMb2NM27vjIyXc1itLnAJPJq2JmHMO7fPPUGxFyZQCIM1owgeONUKFcxRaWbeLi4whLlJEIKyR2RsAQDWAQxt5kQOESe43Z82rFj31PU5Q49gtp8MVfHYPkxl1Kh6yJHeRqo4MqEBxTfpZPYjmiAV3opjMx54vpai5dw0ziGzg21c0POwty5IWtAa622LA7U-EuBlUMQfpsZISb931VP_q96ClsF-1Dvt5xBLUtX6hzhRyabUG19OE0zyfRz-PA8_AQIdtQ2 |
| linkProvider | Elsevier |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV07T8MwELZKGWDhjSjPDAwwuHk4D3ssFahA24VW6mbZiVNFgrYK6cDCb-ecOBQkBBJbdPKdorPv_Nm6z4fQZUpEHHtphB3AolgDdiwDmWCRME_6RBFH6auBwTDsjf2HSTBpoG7NhdFllSb3Vzm9zNZGYhtv2osss58AHEC4RSGjJdCha2jdD7xIn8Da76s6D0Irtg6Mxnr4isZTmSiFV4xel1Yw_XmD-rLp3O2gLYMWrU71Q7uooWZ7aNsgR8vE5SuI6uYMtWwf3XSyPM5FWlhxxUxcgqGkrNew5JsF60bTF-1pXtZ8FXi6zBKwOYcU8mK4mQdofHc76vawaZiAYwjVAgN0Y0QoT1FFpJf6cLSCDcpNhRSSuSKlKYSviBLmUCFggnzXCwMSOkngK-Ixlxyi5mw-U0fIChImpQLXxa7yNUyBcwmLCHxLN3Vc0UJ-7SUem9fEdVOLZ74qGwPncu1czigvnctpC7U_1RbVcxp_KdB6Cvi3dcEh5f-uevx_1Qu00RsN-rx_P3w8QZsVD1HfvJyiZpEv1RkAkUKelwvtAxy_01s |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Aircraft+conceptual+design+by+genetic%2Fgradient-guided+optimization&rft.jtitle=Engineering+applications+of+artificial+intelligence&rft.au=Bos%2C+A.H.W&rft.date=1998-06-01&rft.issn=0952-1976&rft.volume=11&rft.issue=3&rft.spage=377&rft.epage=382&rft_id=info:doi/10.1016%2FS0952-1976%2898%2900009-8&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_S0952_1976_98_00009_8 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0952-1976&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0952-1976&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0952-1976&client=summon |