【正文】 并通過對(duì)一組編碼表示進(jìn)行簡(jiǎn)單的遺傳操作和優(yōu)勝劣汰的自然選擇來指導(dǎo)學(xué)習(xí)和確定搜索的方向。 VB weave.青島理工大學(xué)本科畢業(yè)設(shè)計(jì)（論文）說明書III目錄摘要 .......................................................................................................................IABSTRACT ............................................................................................................II目錄 ....................................................................................................................III第 1 章 緒論 .......................................................................................................1 課題研究的背景和意義及其研究現(xiàn)狀 ..............................................................................1 論 文主要研究?jī)?nèi)容 ..............................................................................................................3第 2 章 遺傳算法的原理及改進(jìn) .......................................................................4 遺傳算法概述 ......................................................................................................................4 算法的基本步驟 ..................................................................................................................5 遺傳算法的基本要點(diǎn) ..........................................................................................................7 遺傳算法的約束問題處理方式 ........................................................................................11 遺傳算法的發(fā)展前景 ........................................................................................................13第 3 章 傳動(dòng)優(yōu)化數(shù)學(xué)模型的建立 .................................................................15 彈簧相關(guān)參數(shù)的選擇確定……………………………………………………………… 彈簧優(yōu)化設(shè)計(jì)數(shù)學(xué)模型的建立………………………………………………………… 第 4 章 齒輪傳動(dòng)優(yōu)化設(shè)計(jì)的遺傳算法實(shí)現(xiàn)方法 .........................................21 設(shè)計(jì)變量的編碼 ................................................................................................................21 群體規(guī)模的選擇 ................................................................................................................23 初始解的產(chǎn)生 ....................................................................................................................23 目標(biāo)函數(shù)和適應(yīng)函數(shù)的產(chǎn)生 ............................................................................................24 選擇復(fù)制操作 ....................................................................................................................26 交叉操作 ............................................................................................................................27 變異運(yùn)算 ............................................................................................................................28青島理工大學(xué)本科畢業(yè)設(shè)計(jì)（論文）說明書IV 終止規(guī)則 ............................................................................................................................31 優(yōu)化算例 ............................................................................................................................31 優(yōu)化設(shè)計(jì)程序代碼 ..........................................................................................................31結(jié)論 .....................................................................................................................44參考文獻(xiàn) .............................................................................................................45致謝 .....................................................................................................................47附錄 1 英文參考資料附錄 2 英文參考資料的中文翻譯青島理工大學(xué)本科畢業(yè)設(shè)計(jì)（論文）說明書1第 1 章 緒論 課題研究的背景和意義及其研究現(xiàn)狀 課題研究的背景和意義遺傳算法(Geic Algorithm, GA) 是近年來迅速發(fā)展起來的一種全新的隨機(jī)搜索與優(yōu)化算法,其基本思想是基于Darw in的進(jìn)化論和Mendel的遺傳學(xué)說。 geic algorithm 。At last ,build the mathematic model and get the optimation result by author does the optimation design by utilizing the VB weave and by utilizing the real variable accoding to the character of the variable of the sping. Compared with the experiential design ,using the optimization design can cut down the cost and is efficient and the optimization design owns the wide view in the machining design .Key words : pressing spring 。關(guān)鍵詞：壓縮彈簧；優(yōu)化設(shè)計(jì)；遺傳算法；整數(shù)變量；VB編程青島理工大學(xué)本科畢業(yè)設(shè)計(jì)（論文）說明書IIAbstractThere are many optimization design methods ,which are generally to optimize all the parameters of a spring by using the pure caculation and mathematic equation and there are more and newer methods to do it such as Matlab geic algorithm and so on since then . In the optimization design of the various machinery and ponents ,the character of the parameter takes a great effect on the design .There are some real number ,some integer of all the variable parameters ,which decide the choice of the parameters used including real variable or integeral variable and even mixed variable in the design The paper dissertates the optimation design of the pressing ,ascertain the object function and the design variable 。與經(jīng)驗(yàn)設(shè)計(jì)方法相比較，采用優(yōu)化設(shè)計(jì)方法可節(jié)約原材料，并且有效實(shí)用。首先,要確定目標(biāo)函數(shù)與設(shè)計(jì)變量；其次，確定約束函數(shù)；最后，建立數(shù)學(xué)模型，利用計(jì)算機(jī)求出優(yōu)化結(jié)果。其中變量參數(shù)有些是實(shí)數(shù)，還有些是整數(shù)，這就影響了在設(shè)計(jì)中用到的變量有著不同的選擇，可以是實(shí)數(shù)變量或者整數(shù)變量甚至是混合變量。青島理工大學(xué)本科畢業(yè)設(shè)計(jì)（論文）說明書I摘要 優(yōu)化設(shè)計(jì)的方法有多種，一般的就只是單純的計(jì)算，運(yùn)用數(shù)學(xué)方程式對(duì)彈簧的各個(gè)參數(shù)加以優(yōu)化，后來人們有了更多更新的方法對(duì)其進(jìn)行優(yōu)化，例如，蟻群算法、Matlab、遺傳算法等等。在不同的機(jī)構(gòu)或零件優(yōu)化設(shè)計(jì)中，參數(shù)的性質(zhì)也對(duì)優(yōu)化設(shè)計(jì)有著至關(guān)重大的影響。此次論文對(duì)壓縮彈簧進(jìn)行優(yōu)化設(shè)計(jì)。此次設(shè)計(jì)運(yùn)用了vb編程，并且根據(jù)彈簧參數(shù)特性運(yùn)用了實(shí)數(shù)變量進(jìn)行優(yōu)化設(shè)計(jì)。因此，優(yōu)化設(shè)計(jì)方法在機(jī)械設(shè)計(jì)行業(yè)具有廣闊的發(fā)展前景。Second ,ascertain the restriction function 。 optimization design 。integeral variable 。該算法由密執(zhí)安大學(xué)教授Holland 及其學(xué)生于1975年創(chuàng)建。與此同時(shí)，基于遺傳算法的機(jī)械優(yōu)化設(shè)計(jì)是以數(shù)學(xué)規(guī)劃論為理論基礎(chǔ)，運(yùn)用計(jì)算機(jī)求機(jī)械設(shè)計(jì)最優(yōu)參數(shù)的現(xiàn)代先進(jìn)設(shè)計(jì)方法．利用計(jì)算機(jī)進(jìn)行優(yōu)化設(shè)計(jì)，無論在機(jī)構(gòu)綜合、通用機(jī)構(gòu)零部件設(shè)計(jì)方面，還是在各種專業(yè)機(jī)械和工藝裝備的設(shè)計(jì)方面都取得了顯著成果．彈簧的優(yōu)化設(shè)計(jì)有其結(jié)構(gòu)要求或其它規(guī)定，諸如強(qiáng)度、剛度、穩(wěn)定性、結(jié)構(gòu)等的限制．因此彈簧優(yōu)化設(shè)計(jì)的含意是：選擇設(shè)計(jì)變量，使目標(biāo)函數(shù)值為最優(yōu)(極大或極小)，并滿足所有的技術(shù)性能及其它要求． 研究現(xiàn)狀壓縮彈簧優(yōu)化設(shè)計(jì)的基本原理是在滿足強(qiáng)度等約束前提下，對(duì)彈簧的簧絲直徑、彈簧中徑、彈簧圈數(shù)等參數(shù)進(jìn)行優(yōu)化設(shè)計(jì)，以達(dá)到減小體積或提高運(yùn)行可靠性、承載能力等目的。傳統(tǒng)的經(jīng)驗(yàn)設(shè)計(jì)方法 [ ]。隨著優(yōu)化技術(shù)的發(fā)展，李智基于蟻群算法對(duì)齒輪傳動(dòng)進(jìn)行了優(yōu)化設(shè)計(jì) [7]，計(jì)算結(jié)果表明，該算法計(jì)算效率高，不失為一種多參數(shù)復(fù)雜約束條件下的有效的優(yōu)化算法。青島理工大學(xué)本科畢業(yè)設(shè)計(jì)（論文）說明書2遺傳算法在彈簧優(yōu)化設(shè)計(jì)中已有應(yīng)用 [14~17]，但大都應(yīng)用二進(jìn)制編碼遺傳算法進(jìn)行彈簧優(yōu)化設(shè)計(jì)時(shí) [18,19,20]，對(duì)于連續(xù)變量存在精度低、存儲(chǔ)量大的缺點(diǎn)，非連續(xù)的離散標(biāo)準(zhǔn)值優(yōu)化后需進(jìn)行圓整處理，從而無法保證結(jié)果的最優(yōu)性。論文通過設(shè)計(jì)變量的選取、目標(biāo)函數(shù)和約束條件的確定，建立了壓縮彈簧的優(yōu)化設(shè)計(jì)數(shù)學(xué)模型，利用遺傳算法進(jìn)行求解，最后借助 VB 語言編制優(yōu)化程序，得到了彈簧的優(yōu)化參數(shù)。（2）壓縮彈簧數(shù)學(xué)模型的建立。（