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龐特里亞金極小原理及生產(chǎn)貯利潤最優(yōu)建模

2023-08-06 20:15 作者:艾琳娜的糖果屋  | 我要投稿

? ? ? ? ?古典變分法雖然強(qiáng)大,但是也有它的局限性,它要求容許函數(shù)是可以任意取的,但實際上容許函數(shù)往往是有限定的,就好比一元函數(shù)求極值一樣在給定的區(qū)間內(nèi)求其最大或最小,往往在邊界取得而非極值點(diǎn)處。對于此類問題,就需要利用龐特里亞金極小值(極大)原理解決,下面形式上的給出原理的推導(dǎo),并利用它建立一個生產(chǎn)-貯存-銷售模型。

考察如下泛函%0AJ%3D%5Cvarphi%20%5Cleft(%20t_2%2Cx_2%20%5Cright)%20%2B%5Cint_%7Bt_1%7D%5E%7Bt_2%7D%7BF%5Cleft(%20t%2Cx%2Cu%20%5Cright)%20%5Cmathrm%7Bd%7Dt%7D%5C%2C%5C%2C%20x%5Cprime%5Cleft(%20t%20%5Cright)%20%3Df%5Cleft(%20t%2Cx%2Cu%20%5Cright)%20%5C%2C%5C%2C%20u%5Cin%20D%5C%2C%5C%2Ct_2%0A%0A自由,%0Ax_2%0A%0A自由

構(gòu)造哈密爾頓函數(shù)%0AH%5Cleft(%20t%2Cx%2Cu%2C%5Clambda%20%5Cright)%20%3DF%5Cleft(%20t%2Cx%2Cu%20%5Cright)%20%2B%5Clambda%20%5Cleft(%20t%20%5Cright)%20f%5Cleft(%20t%2Cx%2Cu%20%5Cright)%20%0A%0A

假設(shè)u是使J取極小值的最優(yōu)控制,由約束條件可以得到最優(yōu)控制條件下的狀態(tài)方程x(t)?

對于微擾?%0A%5Cdelta%20u%0A%0A泛函變動到%0A%5Cvarphi%20%5Cleft(%20t_2%2B%5Cdelta%20t_2%2Cx_2%2B%5Cdelta%20x_2%20%5Cright)%20%2B%5Cint_%7Bt_1%7D%5E%7Bt_2%2B%5Cdelta%20t_2%7D%7B%5Cleft%5C%7B%20H%5Cleft(%20t%2Cx%2B%5Cdelta%20x%2Cu%2B%5Cdelta%20u%2C%5Clambda%20%2B%5Cdelta%20%5Clambda%20%5Cright)%20-%5Clambda%20%5Cleft(%20t%20%5Cright)%20f%5Cleft(%20t%2Cx%2B%5Cdelta%20x%2Cu%2B%5Cdelta%20u%20%5Cright)%20%5Cright%5C%7D%20%5Cmathrm%7Bd%7Dt%7D%0A%0A

且有%0AJ%5Cleft%5B%20x%2B%5Cdelta%20x%2Cu%2B%5Cdelta%20u%20%5Cright%5D%20-J%5Cleft%5B%20x%2Cu%20%5Cright%5D%20%5Cgeqslant%200%0A%0A

%0AJ%5Cleft%5B%20x%2B%5Cdelta%20x%2Cu%2B%5Cdelta%20u%20%5Cright%5D%20-J%5Cleft%5B%20x%2Cu%20%5Cright%5D%20%3D%0A%5Cvarphi%20%5Cleft(%20t_2%2B%5Cdelta%20t_2%2Cx_2%2B%5Cdelta%20x_2%20%5Cright)%20-%5Cvarphi%20%5Cleft(%20t_2%2Cx_2%20%5Cright)%20%2B%5C%5C%5Cint_%7Bt_1%7D%5E%7Bt_2%7D%7B%5Cleft%5C%7B%20H%5Cleft(%20t%2Cx%2B%5Cdelta%20x%2Cu%2B%5Cdelta%20u%2C%5Clambda%20%2B%5Cdelta%20%5Clambda%20%5Cright)%20-H%5Cleft(%20t%2Cx%2Cu%2C%5Clambda%20%5Cright)%20%2B%5Clambda%20%5Cleft(%20t%20%5Cright)%20f%5Cleft(%20t%2Cx%2Cu%20%5Cright)%20-%5Clambda%20%5Cleft(%20t%20%5Cright)%20f%5Cleft(%20t%2Cx%2B%5Cdelta%20x%2Cu%2B%5Cdelta%20u%20%5Cright)%20%5Cright%5C%7D%20%5Cmathrm%7Bd%7Dt%7D%5C%5C%2B%5Cleft(%20H-%5Clambda%20x%5Cprime%5Cmid_%7Bt%3Dt_2%7D%5E%7B%7D%20%5Cright)%20%5Cdelta%20t_2%2B%5Cvarepsilon%20%0A%0A%0A

%3D%0A%5Cleft(%20%5Cvarphi%20_%7Bt_2%7D%2B%5Cleft%5B%20H-%5Clambda%20x%5Cprime%20%5Cright%5D%20%5Cmid_%7Bt%3Dt_2%7D%5E%7B%7D%20%5Cright)%20%5Cdelta%20t_2%2B%5Cvarphi%20_%7Bx_2%7D%5Cdelta%20x_2%2Bo%5Cleft(%20%5Cdelta%20t_2%20%5Cright)%20%2Bo%5Cleft(%20%5Cdelta%20x_2%20%5Cright)%20-%5Cint_%7Bt_1%7D%5E%7Bt_2%7D%7B%5Clambda%20%5Cleft(%20t%20%5Cright)%20%5Cdelta%20x%5Cprime%5Cmathrm%7Bd%7Dt%7D%2B%5C%5C%5Cint_%7Bt_1%7D%5E%7Bt_2%7D%7B%5Cleft%5C%7B%20H%5Cleft(%20t%2Cx%2B%5Cdelta%20x%2Cu%2B%5Cdelta%20u%2C%5Clambda%20%2B%5Cdelta%20%5Clambda%20%5Cright)%20-H%5Cleft(%20t%2Cx%2Cu%2B%5Cdelta%20u%2C%5Clambda%20%2B%5Cdelta%20%5Clambda%20%5Cright)%20%2BH%5Cleft(%20t%2Cx%2Cu%2B%5Cdelta%20u%2C%5Clambda%20%2B%5Cdelta%20%5Clambda%20%5Cright)%20-H%5Cleft(%20t%2Cx%2Cu%2C%5Clambda%20%5Cright)%20%5Cright%5C%7D%20%5Cmathrm%7Bd%7Dt%7D%2B%5Cvarepsilon%20%0A%0A

%0A%3D%5Cleft(%20%5Cvarphi%20_%7Bt_2%7D%2BH%5Cmid_%7Bt%3Dt_2%7D%5E%7B%7D%20%5Cright)%20%5Cdelta%20t_2%2B%5Cleft(%20%5Cvarphi%20_%7Bx_2%7D-%5Clambda%20%5Cmid_%7Bt%3Dt_2%7D%5E%7B%7D%20%5Cright)%20%5Cdelta%20x_2%2B%5Cint_%7Bt_1%7D%5E%7Bt_2%7D%7B%5Cleft(%20H_x%2B%5Clambda%20%5E%7B%5Cprime%7D%5Cleft(%20t%20%5Cright)%20%5Cright)%20%5Cdelta%20x%5Cmathrm%7Bd%7Dt%7D%2B%5C%5C%5Cint_%7Bt_1%7D%5E%7Bt_2%7D%7B%5Cleft%5C%7B%20H%5Cleft(%20t%2Cx%2Cu%2B%5Cdelta%20u%2C%5Clambda%20%2B%5Cdelta%20%5Clambda%20%5Cright)%20-H%5Cleft(%20t%2Cx%2Cu%2C%5Clambda%20%5Cright)%20%5Cright%5C%7D%20%5Cmathrm%7Bd%7Dt%7D%2Bo%5Cleft(%20%5Cdelta%20t_2%20%5Cright)%20%2Bo%5Cleft(%20%5Cdelta%20x_2%20%5Cright)%20%2Bo%5Cleft(%20%5Cdelta%20x%20%5Cright)%20%2B%5Cvarepsilon%20%0A%0A

現(xiàn)在選定%0A%5Clambda%20%5Cleft(%20t%20%5Cright)%20%0A%0A滿足方程%0AH_x%2B%5Clambda%20%5E%7B%5Cprime%7D%5Cleft(%20t%20%5Cright)%20%3D0%0A%0A

以及終端的橫截條件%0A%5Cvarphi%20_%7Bt_2%7D%2BH%5Cmid_%7Bt%3Dt_2%7D%5E%7B%7D%3D0%20%3B%5Cvarphi%20_%7Bx_2%7D-%5Clambda%20%5Cmid_%7Bt%3Dt_2%7D%5E%7B%7D%3D0%0A%0A

那么可以猜測成立%0AH%5Cleft(%20t%2Cx%2Cu%2B%5Cdelta%20u%2C%5Clambda%20%2B%5Cdelta%20%5Clambda%20%5Cright)%20-H%5Cleft(%20t%2Cx%2Cu%2C%5Clambda%20%5Cright)%20%5Cgeqslant%200%0A%0A,這就是極小原理,我們可以對對控制函數(shù)分段以及積分分段處理去證明它,這里就不再證明了,極大情況相同。

此不等式的意思就是說哈密爾頓函數(shù)關(guān)于控制u(t)在最優(yōu)控制的情況下取得極小。

下面通過極小(極大)原理來建立(瞎扯)一個生產(chǎn)—貯存—銷售的最優(yōu)模型。

? ? ? ?我們假設(shè)貯存函數(shù)為x(t),生產(chǎn)速率函數(shù)為u(t),銷售速率函數(shù)為v(t),那么它們之間滿足

%0Ax%5Cprime%5Cleft(%20t%20%5Cright)%20%3Du%5Cleft(%20t%20%5Cright)%20-v%5Cleft(%20t%20%5Cright)%20%0A%0A,其次假定初始情況下貯存量%0Ax%5Cleft(%20t_0%20%5Cright)%20%3Dx_0%0A%0A,那么如何選取生產(chǎn)速率函數(shù),使得總利潤最大呢?為了分析的方便我們來簡化一下銷售速率函數(shù),一般情況下銷售的大小和生產(chǎn)的大小成正相關(guān),與貯存成負(fù)相關(guān)由此我們假定。%0Av%5Cleft(%20t%20%5Cright)%20%3Dk_1u%5Cleft(%20t%20%5Cright)%20-k_2x%5Cprime%5Cleft(%20t%20%5Cright)%20%5C%2C%5C%2Ck_1%2Ck_2%3E0%0A%0A

其次在時間段%0A%5Bt_0%2Ct_1%5D%0A%0A內(nèi)產(chǎn)品的銷售價格是不變的記為p,同時貯存會產(chǎn)生貯存費(fèi)用,記單位產(chǎn)品產(chǎn)生的貯存費(fèi)用為q,生產(chǎn)原材料的成本也是固定的為C,并且實際生產(chǎn)過程中生產(chǎn)速率具有一定的約束,不可能無限增加即,

%0A0%3Cu_%7B%5Cmin%7D%5Cleqslant%20u%5Cleft(%20t%20%5Cright)%20%5Cleqslant%20u_%7B%5Cmax%7D%0A%0A,那么此時間段內(nèi)總利潤函數(shù)可以表示為

%0AJ%3D%5Cint_%7Bt_0%7D%5E%7Bt_1%7D%7Bpv%5Cleft(%20t%20%5Cright)%20%5Cmathrm%7Bd%7Dt%7D-qx%5Cleft(%20t_1%20%5Cright)%20-C%3D%5Cint_%7Bt_0%7D%5E%7Bt_1%7D%7Bp%5Cleft(%20k_1u%5Cleft(%20t%20%5Cright)%20-k_2x%5Cprime%5Cleft(%20t%20%5Cright)%20%5Cright)%20%5Cmathrm%7Bd%7Dt%7D-qx%5Cleft(%20t_1%20%5Cright)%20-C%5C%2C%5C%2C%20%20%20%0A%0A

因此問題歸結(jié)為在約束條件%0A%5C%2C%5C%2Cx%5Cprime%5Cleft(%20t%20%5Cright)%20%3D%5Cfrac%7B1-k_1%7D%7B1-k_2%7Du%5Cleft(%20t%20%5Cright)%20%2C0%3Cu_%7B%5Cmin%7D%5Cleqslant%20u%5Cleft(%20t%20%5Cright)%20%5Cleqslant%20u_%7B%5Cmax%7D%0A%0A下求泛函

%0AJ%3D-qx%5Cleft(%20t_1%20%5Cright)%20-C%2B%5Cint_%7Bt_0%7D%5E%7Bt_1%7D%7Bp%5Cleft(%20k_1u%5Cleft(%20t%20%5Cright)%20-k_2x%5Cprime%5Cleft(%20t%20%5Cright)%20%5Cright)%20%5Cmathrm%7Bd%7Dt%7D%0A%0A的最大值

構(gòu)造哈密爾頓函數(shù):%0AH%3Dp%5Cleft(%20k_1u%5Cleft(%20t%20%5Cright)%20-k_2x%5Cprime%5Cleft(%20t%20%5Cright)%20%5Cright)%20%2B%5Cfrac%7B1-k_1%7D%7B1-k_2%7D%5Clambda%20%5Cleft(%20t%20%5Cright)%20u%5Cleft(%20t%20%5Cright)%20%0A

橫截條件:%0AH_x%3D0%3D-%5Clambda%20%5Cprime%5Cleft(%20t%20%5Cright)%20%0A%0A%3B%5Cvarphi%20_%7Bx_1%7D%3D-q%3D%5Clambda%20%5Cleft(%20t_1%20%5Cright)%20%0A%0A

由此得到%0A%5Clambda%20%5Cleft(%20t%20%5Cright)%20%3D-q%3BH%3D-k_2px%5Cprime%5Cleft(%20t%20%5Cright)%20%2B%5Cleft(%20pk_1-q%5Cfrac%7B1-k_1%7D%7B1-k_2%7D%20%5Cright)%20u%5Cleft(%20t%20%5Cright)%20%0A%0A

于是最大利潤下的生產(chǎn)速率函數(shù)、貯存函數(shù)的選取應(yīng)該滿足

%0Au%5Cleft(%20t%20%5Cright)%20%3D%5Cbegin%7Bcases%7D%0A%09u_%7B%5Cmax%7D%26%09%09%5Cfrac%7Bp%7D%7Bq%7D%3E%5Cfrac%7B1%7D%7Bk_1%7D%5Cfrac%7B1-k_1%7D%7B1-k_2%7D%5C%5C%0A%09u_%7B%5Cmin%7D%26%09%09%5Cfrac%7Bp%7D%7Bq%7D%3C%5Cfrac%7B1%7D%7Bk_1%7D%5Cfrac%7B1-k_1%7D%7B1-k_2%7D%5C%5C%0A%5Cend%7Bcases%7D%0A%0A%0Ax%5Cleft(%20t%20%5Cright)%20%3D%5Cbegin%7Bcases%7D%0A%09u_%7B%5Cmax%7D%5Cfrac%7B1-k_1%7D%7B1-k_2%7D%5Cleft(%20t-t_0%20%5Cright)%20%2Bx_0%26%09%09%5Cfrac%7Bp%7D%7Bq%7D%3E%5Cfrac%7B1%7D%7Bk_1%7D%5Cfrac%7B1-k_1%7D%7B1-k_2%7D%5C%5C%0A%09u_%7B%5Cmin%7D%5Cfrac%7B1-k_1%7D%7B1-k_2%7D%5Cleft(%20t-t_0%20%5Cright)%20%2Bx_0%26%09%09%5Cfrac%7Bp%7D%7Bq%7D%3C%5Cfrac%7B1%7D%7Bk_1%7D%5Cfrac%7B1-k_1%7D%7B1-k_2%7D%5C%5C%0A%5Cend%7Bcases%7D%0A%0A

上述假設(shè)中可以發(fā)現(xiàn),極值函數(shù)剛好取在某一個邊界上,如果假設(shè)銷售速率函數(shù)與貯存量有關(guān),即%0A%0A%0A%0Av%5Cleft(%20t%20%5Cright)%20%3Dk_1u%5Cleft(%20t%20%5Cright)%20-k_2x%5Cleft(%20t%20%5Cright)%20%5C%2C%5C%2Ck_1%2Ck_2%3E0%0A%0A此時最大利潤可以表示為

%0AJ%3D-qx%5Cleft(%20t_1%20%5Cright)%20-C%2B%5Cint_%7Bt_0%7D%5E%7Bt_1%7D%7Bp%5Cleft(%20k_1u%5Cleft(%20t%20%5Cright)%20-k_2x%5Cleft(%20t%20%5Cright)%20%5Cright)%20%5Cmathrm%7Bd%7Dt%7D%5C%2C%5C%2C%0A%0A以及約束條件

%0A%5C%2C%5C%2Cx%5Cprime%5Cleft(%20t%20%5Cright)%20%3D%5Cleft(%201-k_1%20%5Cright)%20u%5Cleft(%20t%20%5Cright)%20%2Bk_2x%5Cleft(%20t%20%5Cright)%20%3B0%3Cu_%7B%5Cmin%7D%5Cleqslant%20u%5Cleft(%20t%20%5Cright)%20%5Cleqslant%20u_%7B%5Cmax%7D%0A%0A

構(gòu)造哈密爾頓函數(shù)%0AH%3D%5Cleft%5C%7B%20pk_1%2B%5Cleft(%201-k_1%20%5Cright)%20%5Clambda%20%5Cleft(%20t%20%5Cright)%20%5Cright%5C%7D%20u%5Cleft(%20t%20%5Cright)%20%2Bk_2x%5Cleft(%20t%20%5Cright)%20%5Cleft%5C%7B%20%5Clambda%20%5Cleft(%20t%20%5Cright)%20-p%20%5Cright%5C%7D%20%0A%0A

橫截條件:%0AH_x%3Dk_2%5Clambda%20%5Cleft(%20t%20%5Cright)%20-k_2p%3D-%5Clambda%20%5Cprime%5Cleft(%20t%20%5Cright)%20%5C%2C%5C%2C%20%20%5Cvarphi%20_%7Bx_1%7D%3D%5Clambda%20%5Cleft(%20t_2%20%5Cright)%20%3D-q%0A%0A

解得%0A%0A%5Clambda%20%5Cleft(%20t%20%5Cright)%20%3Dp-%5Cleft(%20p%2Bq%20%5Cright)%20e%5E%7Bk_2%5Cleft(%20t_2-t%20%5Cright)%7D%0A%0A%0A,同時假定0%3Ck_1%3C1

得到利潤最大時候的生產(chǎn)速率函數(shù)和貯存函數(shù)

%0A%0Au%5Cleft(%20t%20%5Cright)%20%3D%5Cbegin%7Bcases%7D%0A%09u_%7B%5Cmin%7D%26%09%09t_0%5Cleqslant%20t%3Ct%5E*%5C%5C%0A%09u_%7B%5Cmax%7D%26%09%09t%5E*%3Ct%5Cleqslant%20t_1%5C%5C%0A%5Cend%7Bcases%7D%3Bt%5E*%3D%5C%2C%5C%2Ct_1-%5Cfrac%7B1%7D%7Bk_2%7D%5Clog%20%5Cfrac%7Bp%7D%7B%5Cleft(%201-k_1%20%5Cright)%20%5Cleft(%20p%2Bq%20%5Cright)%7D%0A%0A

%0Ax%5Cleft(%20t%20%5Cright)%20%3D%5Cbegin%7Bcases%7D%0A%09-u_%7B%5Cmin%7D%5Cfrac%7B1-k_1%7D%7Bk_2%7D%2B%5Cleft(%20x_0%2Bu_%7B%5Cmin%7D%5Cfrac%7B1-k_1%7D%7Bk_2%7D%20%5Cright)%20e%5E%7Bk_2%5Cleft(%20t-t_0%20%5Cright)%7D%26%09%09t_0%5Cleqslant%20t%5Cleqslant%20t%5E*%5C%5C%0A%09-u_%7B%5Cmax%7D%5Cfrac%7B1-k_1%7D%7Bk_2%7D%2B%5Cleft(%20x%5Cleft(%20t%5E*%20%5Cright)%20%2Bu_%7B%5Cmax%7D%5Cfrac%7B1-k_1%7D%7Bk_2%7D%20%5Cright)%20e%5E%7Bk_2%5Cleft(%20t-t%5E*%20%5Cright)%7D%26%09%09t%5E*%5Cleqslant%20t%5Cleqslant%20t_1%5C%5C%0A%5Cend%7Bcases%7D%5C%2C%5C%2C%0A%0A

如果k_1%3E1,那么利潤最大時的生產(chǎn)速率函數(shù)和貯存函數(shù)則為

%0Au%5Cleft(%20t%20%5Cright)%20%3Du_%7B%5Cmax%7D%5C%2C%5C%2C%20%20%20t_0%5Cleqslant%20t%5Cleqslant%20t_1%0A%5C%5C%0Ax%5Cleft(%20t%20%5Cright)%20%3D-u_%7B%5Cmax%7D%5Cfrac%7B1-k_1%7D%7Bk_2%7D%2B%5Cleft(%20x_0%2Bu_%7B%5Cmax%7D%5Cfrac%7B1-k_1%7D%7Bk_2%7D%20%5Cright)%20e%5E%7Bk_2%5Cleft(%20t-t_0%20%5Cright)%7D%5C%2C%5C%2C%20t_0%5Cleqslant%20t%5Cleqslant%20t_1%0A%0A

當(dāng)然,以上都是比較簡單的理想化的假設(shè),以至于能夠直接解出微分方程。



%0A%0A



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龐特里亞金極小原理及生產(chǎn)貯利潤最優(yōu)建模的評論 (共 條)

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