


下載本文檔
版權(quán)說(shuō)明:本文檔由用戶提供并上傳,收益歸屬內(nèi)容提供方,若內(nèi)容存在侵權(quán),請(qǐng)進(jìn)行舉報(bào)或認(rèn)領(lǐng)
文檔簡(jiǎn)介
一種增廣拉格朗日優(yōu)化方案及其非連續(xù)變形分析實(shí)現(xiàn)1.IntroductionTheaugmentedLagrangianoptimizationmethodisapowerfultechniqueforsolvingoptimizationproblemswithconstraints.ItcombinesthebenefitsofbothLagrangianandpenaltymethodsandhasbeenwidelyusedinvariousfieldsincludingengineering,economics,andfinance.However,thetraditionalaugmentedLagrangianmethodsuffersfromslowconvergenceandweakfeasibilityconditions.Toaddresstheseissues,severalenhancedversionsoftheaugmentedLagrangianmethodhavebeenproposed,oneofwhichistheaugmentingLagrangianwithnonlinearconstraints.Inthispaper,wepresentanovelaugmentedLagrangianoptimizationschemewithnonlinearconstraintsanddiscussitsnon-continuousdeformationanalysisimplementation.2.LiteratureReviewThetraditionalaugmentedLagrangianoptimizationmethodwasfirstintroducedbyHestenesandPowellin1969.Inthismethod,apenaltyfunctionisaddedtotheLagrangianfunctiontopenalizetheviolationofconstraints.However,thismethodhasslowconvergenceandweakfeasibilityconditions,whichcancausenumericalinstabilityinsomecases.Toovercometheselimitations,severalvariantsoftheaugmentedLagrangianmethodhavebeenproposed,suchasthemethodofmultipliers,thesequentialquadraticprogrammingmethod,andtheinteriorpointmethod.AnotherapproachistoincorporatenonlinearconstraintsintotheaugmentedLagrangianmethod.Thistechniquehasbeenshowntoimprovetheconvergencerateandfeasibilityconditions.ThenonlinearconstraintscanbeaddedtotheLagrangianfunctioninvariousforms,suchastheexponentialform,thelogarithmicform,orthepowerform.ThechoiceoftheformdependsontheproblemathandandthedesiredpropertiesoftheaugmentedLagrangianmethod.3.AugmentedLagrangianOptimizationSchemeInthispaper,weproposeanaugmentedLagrangianoptimizationschemewithnonlinearconstraints.TheschemeisbasedonthefollowingLagrangianfunction:L(x,λ,r)=f(x)+λ?g(x)+0.5?r?||g(x)||2wherexistheoptimizationvariable,λistheLagrangemultiplier,g(x)isthenonlinearconstraint,risthepenaltyparameter,and||?||denotesthenormofavector.TheLagrangianfunctioncombinestheobjectivefunctionf(x)withthenonlinearconstraintg(x)andapenaltytermthatpenalizestheviolationoftheconstraint.TheoptimizationproblemistofindxthatminimizestheLagrangianfunctionwithrespecttoλandr.Thiscanbeachievedbythefollowingiterationscheme:xk+1=argminxL(x,λk,rk)λk+1=λk+rk?g(xk+1)rk+1=α?rkwhereαisascalarthatcontrolstheincreaseinthepenaltyparameterateachiteration.Theiterationschemeupdatestheoptimizationvariablex,theLagrangemultiplierλ,andthepenaltyparameterrsequentially.Thealgorithmconvergeswhentheconstraintviolationissufficientlysmall,andtheoptimizationvariablesatisfiesthenecessaryconditionsforoptimality.TheproposedschemehasseveraladvantagesovertraditionalaugmentedLagrangianoptimizationmethods.Firstly,itincorporatesnonlinearconstraintsintotheoptimizationframework,whichcanimprovetheconvergencerateandfeasibilityconditions.Secondly,itusesaquadraticpenaltyterm,whichislessseverethanthelinearpenaltytermusedintraditionalmethods.Thiscanhelptoavoidnumericalinstabilitiesandimprovetheoverallperformanceofthealgorithm.4.Non-ContinuousDeformationAnalysisImplementationTheproposedaugmentedLagrangianoptimizationschemecanbeappliedtonon-continuousdeformationanalysisproblems.Non-continuousdeformationanalysisisatechniquethatsimulatesthedeformationofthree-dimensionalobjectsunderexternalloads.Itinvolvessolvingacomplexsetofequationsthatconsistofnonlinearconstraints,whichmakesitdifficulttoobtainanaccuratesolution.Toapplytheproposedschemetonon-continuousdeformationanalysis,weuseafiniteelementmethodtodiscretizethedeformationequations.ThenonlinearconstraintsarethenaddedtotheLagrangianfunction,andthepenaltyparameterischosenbasedonthestiffnessoftheobject.TheiterationschemeisusedtominimizetheLagrangianfunctionwithrespecttothedegreesoffreedomoftheobject.Thenon-continuousdeformationanalysisimplementationoftheproposedschemehasseveralbenefits.Firstly,itcanhandlecomplexthree-dimensionalobjectswithnonlinearmaterialproperties,whicharedifficulttosimulateusingtraditionalmethods.Secondly,itcanaccuratelypredictthebehaviorofastructureunderexternalloads,whichisimportantinengineeringandconstruction.5.ConclusionInthispaper,wepresentedanovelaugmentedLagrangianoptimizationschemewithnonlinearconstraintsanddiscusseditsnon-continuousdeformationanalysisimplementation.TheproposedschemehasseveraladvantagesovertraditionalaugmentedLagrangianoptimizationmethodsandcanbeappliedtonon-continuousdeformationanalysisproblems.Theimplementationoftheschemecanaccuratelypredicttheb
溫馨提示
- 1. 本站所有資源如無(wú)特殊說(shuō)明,都需要本地電腦安裝OFFICE2007和PDF閱讀器。圖紙軟件為CAD,CAXA,PROE,UG,SolidWorks等.壓縮文件請(qǐng)下載最新的WinRAR軟件解壓。
- 2. 本站的文檔不包含任何第三方提供的附件圖紙等,如果需要附件,請(qǐng)聯(lián)系上傳者。文件的所有權(quán)益歸上傳用戶所有。
- 3. 本站RAR壓縮包中若帶圖紙,網(wǎng)頁(yè)內(nèi)容里面會(huì)有圖紙預(yù)覽,若沒(méi)有圖紙預(yù)覽就沒(méi)有圖紙。
- 4. 未經(jīng)權(quán)益所有人同意不得將文件中的內(nèi)容挪作商業(yè)或盈利用途。
- 5. 人人文庫(kù)網(wǎng)僅提供信息存儲(chǔ)空間,僅對(duì)用戶上傳內(nèi)容的表現(xiàn)方式做保護(hù)處理,對(duì)用戶上傳分享的文檔內(nèi)容本身不做任何修改或編輯,并不能對(duì)任何下載內(nèi)容負(fù)責(zé)。
- 6. 下載文件中如有侵權(quán)或不適當(dāng)內(nèi)容,請(qǐng)與我們聯(lián)系,我們立即糾正。
- 7. 本站不保證下載資源的準(zhǔn)確性、安全性和完整性, 同時(shí)也不承擔(dān)用戶因使用這些下載資源對(duì)自己和他人造成任何形式的傷害或損失。
最新文檔
- 初中數(shù)學(xué)冀教版七年級(jí)上冊(cè)2.2 點(diǎn)和線練習(xí)題
- 2025年室內(nèi)裝飾高級(jí)設(shè)計(jì)師考試模擬試卷:空間創(chuàng)意設(shè)計(jì)與施工組織
- 2025年教師教學(xué)成果獎(jiǎng)評(píng)選中的可持續(xù)發(fā)展教育理念
- 2025年家政服務(wù)員中級(jí)模擬試題:家居保潔與收納專業(yè)能力評(píng)測(cè)
- 2025年香港特別行政區(qū)中一上學(xué)期期末物理試題(含答案)-其他專項(xiàng)認(rèn)證考試
- 甘肅省金太陽(yáng)暨隴南一診2025屆高三上學(xué)期1月期末考-語(yǔ)文試卷+答案
- 2025年高中地理選修五地質(zhì)災(zāi)害防治案例分析試卷:深度解析
- 電力調(diào)度專業(yè)核心要點(diǎn)解析
- 傳染病科普宣傳知識(shí)
- 急救藥品管理使用規(guī)范
- 杭州市2025年中考作文《勇敢自信》寫作策略與范文
- 起重機(jī)司機(jī)(限橋式)Q2特種設(shè)備作業(yè)人員資格鑒定參考試題(附答案)
- 熱點(diǎn)主題作文寫作指導(dǎo):古樸與時(shí)尚(審題指導(dǎo)與例文)
- 河南省洛陽(yáng)市2025屆九年級(jí)下學(xué)期中考一模英語(yǔ)試卷(原卷)
- 電網(wǎng)工程設(shè)備材料信息參考價(jià)2025年第一季度
- 江蘇南京茉莉環(huán)境投資有限公司招聘筆試題庫(kù)2025
- 吸氧并發(fā)癥預(yù)防及處理
- 針刺傷預(yù)防與處理(中華護(hù)理學(xué)會(huì)團(tuán)體標(biāo)準(zhǔn))
- 2024年安徽省初中學(xué)業(yè)水平考試生物試題含答案
- 2024年浙江省中考英語(yǔ)試題卷(含答案解析)
- MOOC 理解馬克思-南京大學(xué) 中國(guó)大學(xué)慕課答案
評(píng)論
0/150
提交評(píng)論