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Mathematics LibreTexts

6: Exercises

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Exercises

[exer:1] Find the point on the plane 2x+3y+z=7 closest to (1,2,3).

[exer:2] Find the extreme values of f(x,y)=2x+y subject to x2+y2=5.

[exer:3] Suppose that a,b>0 and aα2+bβ2=1. Find the extreme values of f(x,y)=βx+αy subject to ax2+by2=1.

[exer:4] Find the points on the circle x2+y2=320 closest to and farthest from (2,4).

[exer:5] Find the extreme values of f(x,y,z)=2x+3y+z\quad subject to\quadx2+2y2+3z2=1.

[exer:6] Find the maximum value of f(x,y)=xy on the line ax+by=1, where a,b>0.

[exer:7] A rectangle has perimeter p. Find its largest possible area.

[exer:8] A rectangle has area A. Find its smallest possible perimeter.

[exer:9] A closed rectangular box has surface area A. Find it largest possible volume.

[exer:10] The sides and bottom of a rectangular box have total area A. Find its largest possible volume.

[exer:11] A rectangular box with no top has volume V. Find its smallest possible surface area.

[exer:12] Maximize f(x,y,z)=xyz subject to xa+yb+zc=1, where a, b, c>0.

[exer:13] Two vertices of a triangle are (a,0) and (a,0), and the third is on the ellipse x2a2+y2b2=1. Find its largest possible area.

[exer:14] Show that the triangle with the greatest possible area for a given perimeter is equilateral, given that the area of a triangle with sides x, y, z and perimeter s is A=s(sx)(sy)(sz).

[exer:15] A box with sides parallel to the coordinate planes has its vertices on the ellipsoid x2a2+y2b2+z2c2=1. Find its largest possible volume.

[exer:16] Derive a formula for the distance from (x1,y1,z1) to the plane ax+by+cz=σ.

[exer:17] Let Xi=(xi,yi,zi), 1in. Find the point in the plane ax+by+cz=σ for which ni=1|XXi|2 is a minimum. Assume that none of the Xi are in the plane.

[exer:18] Find the extreme values of f(X)=ni=1(xici)2 subject to ni=1x2i=1.

[exer:19] Find the extreme values of f(x,y,z)=2xy+2xz+2yz\quad subject to\quadx2+y2+z2=1.

[exer:20] Find the extreme values of f(x,y,z)=3x2+2y2+3z2+2xz\quad subject to\quadx2+y2+z2=1.

[exer:21] Find the extreme values of f(x,y)=x2+8xy+4y2\quad subject to\quadx2+2xy+4y2=1.

[exer:22] Find the extreme value of f(x,y)=α+βxy subject to (ax+by)2=1. Assume that ab0.

[exer:23] Find the extreme values of f(x,y,z)=x+y2+2z subject to 4x2+9y236z2=36.

[exer:24] Find the extreme values of f(x,y,z,w)=(x+z)(y+w) subject to x2+y2+z2+w2=1.

[exer:25] Find the extreme values of f(x,y,z,w)=(x+z)(y+w) subject to x2+y2=1\;and \;\;z2+w2=1.

[exer:26] Find the extreme values of f(x,y,z,w)=(x+z)(y+w) subject to x2+z2=1\;and \;\;y2+w2=1.

[exer:27] Find the distance between the circle x2+y2=1 the hyperbola xy=1.

[exer:28] Minimize f(x,y,x)=x2α2+y2β2+z2γ2 subject to ax+by+cz=d and x, y, z>0.

[exer:29] Find the distance from (c1,c2,,cn) to the plane a1x1+a2x2++anxn=d.

[exer:30] Find the maximum value of f(X)=ni=1aix2i subject to ni=1bix4i=1, where p, q>0 and ai, bi xi>0, 1in.

[exer:31] Find the extreme value of f(X)=ni=1aixpi subject to ni=1bixqi=1, where p, q>0 and ai, bi, xi>0, 1in.

[exer:32] Find the minimum value of f(x,y,z,w)=x2+2y2+z2+w2 subject to x+y+2z+3w=1x+y+2z+3w=2.

[exer:33] Find the minimum value of f(x,y,z)=x2a2+y2b2+z2c2 subject to p1x+p2y+p3z=d, assuming that at least one of p1, p2, p3 is nonzero.

[exer:34] Find the extreme values of f(x,y,z)=p1x+p2y+p3z subject to x2a2+y2b2+z2c2=1, assuming that at least one of p1, p2, p3 is nonzero.

[exer:35] Find the distance from (1,2,3) to the intersection of the planes
x+2y3z=4 and 2xy+2z=5.

[exer:36] Find the extreme values of f(x,y,z)=2x+y+2z subject to x2+y2=4 and x+z=2.

[exer:37] Find the distance between the parabola y=1+x2 and the line x+y=1.

[exer:38] Find the distance between the ellipsoid 3x2+9y2+6z2=10 and the plane 3x+3y+6z=70.

[exer:39] Show that the extreme values of f(x,y,z)=xy+yz+zx subject to x2a2+y2b2+z2c2=1 are the largest and smallest eigenvalues of the matrix [0a2a2b20b2c2c20].

[exer:40] Show that the extreme values of f(x,y,z)=xy+2yz+2zx subject to x2a2+y2b2+z2c2=1 are the largest and smallest eigenvalues of the matrix [0a2/2a2b2/20b2c2c20].

[exer:41] Find the extreme values of x(y+z) subject to x2a2+y2b2+z2c2=1.

[exer:42] Let a, b, c, p, q, r, α, β, and γ be positive constants. Find the maximum value of f(x,y,z)=xαyβzγ subject to axp+byq+czr=1\; and\;\;x,y,z>0.

[exer:43] Find the extreme values of f(x,y,z,w)=xwyz\quad subject to\quadx2+2y2=4\quad and\quad2z2+w2=9.

[exer:44] Let a, b, c,and d be positive. Find the extreme values of f(x,y,z,w)=xwyz subject to ax2+by2=1,cz2+dw2=1, if (a) adbc; (b) ad=bc.

[exer:45] Minimize f(x,y,z)=αx2+βy2+γz2 subject to a1x+a2y+a3z=c\; and\;\;b1x+b2y+b3z=d. Assume that α,β,γ>0,a21+a22+a230,\; and\;\;b21+b22+b230. Formulate and apply a required additional assumption.

[exer:46] Minimize f(X,Y)=ni=1(xiαi)2 subject to ni=1aixi=c\; and\;\;ni=1bixi=d, where ni=1a2i=ni=1b2i=1\; and\;\;ni=1aibi=0.

[exer:47] Find (x10,x20,,xn0) to minimize Q(X)=ni=1x2i subject to ni=1xi=1\quad and\quadni=1ixi=0. Prove explicitly that if nj=1yi=1,ni=1iyi=0 and yixi0 for some i{1,2,,n}, then ni=1y2i>ni=1x2i0.

[exer:48] Let p1, p2, …, pn and s be positive numbers. Maximize f(X)=(sx1)p1(sx2)p2(sxn)pn subject to x1+x2++xn=s.

[exer:49] Maximize f(X)=xp11xp22xpnn subject to xi>0, 1in, and ni=1xiσi=S, where p1, p2,…, pn, σ1, σ2, …, σn, and V are given positive numbers.

[exer:50] Maximize f(X)=ni=1xiσi subject to xi>0, 1in, and xp11xp22xpnn=V, where p1, p2,…, pn, σ1, σ2, …, σn, and S are given positive numbers.

[exer:51] Suppose that α1, α2, …αn are positive and at least one of a1, a2, …, an is nonzero. Let (c1,c2,,cn) be given. Minimize Q(X)=ni=1(xici)2αi subject to a1x1+a2x2++anxn=d.

[exer:52] Schwarz’s inequality says that (a1,a2,,an) and (x1,x2,,xn) are arbitrary n-tuples of real numbers, then |a1x1+a2x2++anxn|(a21+a22++a2n)1/2(x21+x22++x2n)1/2. Prove this by finding the extreme values of f(X)=ni=1aixi subject to ni=1x2i = σ2.

[exer:53] Let x1, x2, …, xm, r1, r2, …, rm be positive and r1+r2++rm=r. Show that (xr11xr22xrmm)1/rr1x1+r2x2+rmxmr, and give necessary and sufficient conditions for equality. (Hint: Maximize xr11xr22xrmm subject to mj=1rjxj=σ>0, x1>0, x2>0, …, xm>0.)

[exer:54] Let A=[aij] be an m×n matrix. Suppose that p1, p2, …, pm>0 and mj=11pj=1, and define σi=nj=1|aij|pi,1im. Use Exercise [exer:53] to show that |nj=1aija2jamj|σ1/p11σ1/p22σ1/pmm. (With m=2 this is Hölder’s inequality, which reduces to Schwarz’s inequality if p1=p2=2.)

[exer:55] Let c0, c1, …, cm be given constants and nm+1. Show that the minimum value of Q(X)=nr=0x2r subject to nr=0xrrs=cs,0sm, is attained when xr=ms=0λsrs,0rn, where m=0σs+λ=cs\; and\;\;σs=nr=0rs,0sm. Show that if {xr}nr=0 satisfies the constraints and xrxr0 for some r, then nr=0x2r>nr=0x2r0.

[exer:56] Suppose that n>2k. Show that the minimum value of f(W)=ni=nw2i, subject to the constraint ni=nwiP(ri)=P(r) whenever r is an integer and P is a polynomial of degree 2k, is attained with wi0=2kr=0λrir,1in, where 2kr=0λrσr+s={1if s=0,0if 1s2k,\; and\;\;σs=nj=njs. Show that if {wi}ni=n satisfies the constraint and wiwi0 for some i, then ni=nw2i>ni=nw2i0.

[exer:57] Suppose that nk. Show that the minimum value of fni=0w2i, subject to the constraint ni=0wiP(ri)=P(r+1) whenever r is an integer and P is a polynomial of degree k, is attained with wi0=kr=0λrir,0in, where kr=0σr+sλr=(1)s,0sk,\quad and\quad σ=ni=0i,02k. Show that if ni=0uiP(ri)=P(r+1) whenever r is an integer and P is a polynomial of degree k, and uiwi0 for some i, then ni=0u2i>ni=0w2i0.

[exer:58] Minimize f(X)=ni=1(xici)2αi subject to ni=1airxi=dr,1rm Assume that m>1, α1, α2, …αm>0, and ni=1αiairais={1 if r=s,0 if rs.

Answers to selected exercises

[exer:1]. (15727,257) ±5 1/ab, 1/ab

[exer:4]. (8,16) is closest, (8,16) is farthest. ±53/6 1/4ab p2/4

4A A3/2/66 A3/2/63 3(2V)2/3 abc/27

ab 8abc/33

[exer:18]. (1μ)2 and (1+μ)2, where μ=(nj=1c2j)1/2 1, 2 2, 4

2/3, 2 α±|β|/4|ab| 5, 73/16 ±1 ±2

±2 21 d2(aα)2+(bβ2)+(cγ)2

|da1c1a2c2ancn)ai|a21+a22+a2n (ni=1a2ibi)1/2

[exer:31]. (ni=1aq/(qp)ibp/(pq)i)1p/q is a constrained maximum if p<q, a constrained minimum if p>q

689/845 d2p21a2+p22b2+p23c2 ±(p21a2+p22b2+p23c2)1/2

[exer:35]. 693/45 [exer:36]. 2, 6 7/42 106/3 ±|c|a2+b2/2

αβγpqr(αp+βq+γr)3 [exer:43]. ±3 ±1/bc (b) ±1/ad=±1/bc

[exer:46]. (cni=1aiαi)2+(dni=1biαi)2 xi0=(4n+26i)/n(n1)

[exer:48]. [(n1)sP]Ppp11pp22ppnn

[exer:49]. (Sp1+p2++pn)p1+p2++pn(p1σ1)p1(p2σ2)p2(pnσn)pn

[exer:50]. (p1+p2++pn)(V(σ1p1)p1(σ2p2)p2(σnpn)pn)1p1+p2++pn

[exer:51]. (dni=1aici))2/(ni=1a2iαi) ±(ni=1a2i)1/2(ni=1x2i0)1/2

mr=1(drni=1airci)2

INSTRUCT0R’S SolutionS MANUAL

SolutionS OF EXERCISES

L=(x1)2+(y+2)2+(z3)22λ(2x+3y+z) Lx=x12λ,Ly=y+23λ,Lz=z3λ x0=1+2λ,y0=2+3λ,z0=3+λ 2(1+2λ)+3(2+3λ)+(3+λ)=7,λ=47 x0=157,y0=27,z0=257 The distance from (x01,y01,z01) to the plane is (x01)2+(y0+2)2+(z03)2=4λ2+9λ2+λ2=427.

L=2x+yλ2(x2+y2), Lx=2λx, Ly=1λy

x0=2y0,5y20=5,(x0,y0)=±(2,1) Constrained minimum =5, constrained maximum =5.

L=βx+αyλ2(ax2+by2)

Lx=βλax,Ly=αλby,x0=βλa,y0=αλb 1=ax20+by20=1λ2(β2a+α2b)=1abλ2(aα2+bβ2)=1abλ2. 1λ=±ab; (x0,y0)=±(βba,αab). Choosing “+” yields the constrained maximum f(x0,y0)=β2ba+α2ab=bβ2ab+aα2ab=1ab. Choosing “” yields the constrained minimum 1ab.

L=(x2)2+(y4)2λ(x2+y2)2

Lx(x,y)=(x2)λx,Ly(x,y)=(y4)λy x02x0=y04y0=λ,\; so\;\;y0=2x0. Therefore, x20+y20=5x20=320, (x0,y0)=±(8,16) so the constrained critical points are (8,16) and (8,16); (8,16) is closest to (2,4) and (8,16) is farthest.

L=2x+3y+zλ2(x2+2y2+3z2)

Lx=2λx,Ly=32λy,Lz=13λz x0=2λy0=32λ,z0=13λ,x20+2y20+3z20=536λ2=1,λ=±53/6. Since f(2/λ,3/2λ,1/3λ)=536λ=±λ, the constrained extreme values are ±53/6.

L=xyλ(ax+by), Lx(x,y)=yλa, Ly=xλb

x0=λb,y0=λa,ax0+by0=2λab=1,λ=12ab x0=12a,y0=12b,x0y0=14ab=constrained maximum\;\;

p=2x+2y, A=xy, L=xyλ(x+y), Lx=yλ, Ly=xλ, y0=x0, x0=p/4, Amax=p2/4.

Let x and y denote lengths of sides. We must mimimize x+y subject to xy=A. L=x+yλxy,Lx=1λy,Ly=1λx,x0=y0,x0y0=A,x0=A. The minimum perimeter is 4A.

Denote the vertices of the box by (0,0,0), (x,0,0), (0,y,0), and (0,0,z). V=xyz,A=2xz+2yz+2xy,L=xyzλ(xz+yz+xy) Lx=yzλ(z+y),Ly=xzλ(z+x),Lz=xyλ(x+y) y0z0=λ(z0+y0),x0z0=λ(z0+x0),x0y0=λ(x0+y0) x0z0+x0y0=z0y0+x0y0=x0z0+y0z0,x0=y0=z0 A=6z20,z=A6,Vmax=z30=A3/266.

Denote the vertices of the box by (0,0,0), (x,0,0), (0,y,0), and (0,0,z). V=xyz,A=2xz+2yz+xy,L=xyzλ(2xz+2yz+xy) Lx=yzλ(2z+y),Ly=xzλ(2z+x),Lz=xyλ(2x+2y) y0z0=λ(2z0+y0),x0z0=λ(2z0+x0),x0y0=λ(2x0+2y0) x0y0z0=λx0(2z0+y0),x0y0z0=λy0(2z0+x0),x0y0z0=λz0(2x0+2y0) 2x0z0+x0y0=2y0z0+x0y0=2x0z0+2y0z0 x0=y0=2z0,A=12z20,z0=A12,Vmax=z30=A3/263.

Denote the vertices of the box by (0,0,0), (x,0,0), (0,y,0), and (0,0,z). V=xyz,A=2xz+2yz+xy,L=2xz+2yz+xyλxyz, Lx=2z+yλyz,Ly=2z+xλxz,Lz=2x+2yλxy 2z0+y0=λy0z0,2z0+x0=λx0z0,2x0+2y0λx0y0 2x0z0+x0y0=2y0z0+x0y0=2x0z0+2y0z0 x0=y0=2z0,V=4z30,z0=(2V)1/32,x0=y0=(2V)1/3,Amin=3(2V)2/3

L=xyzλ(xa+yb+zc), Lx=yzλa, Ly=xzλb, Lz=xyλc y0z0=λa,x0z0=λb,x0y0=λc,x0a=y0b=z0c=13,Vmax=abc27.

We may assume without loss of generality that y>0, so A=ay. L=ayλ2(x2a2+y2b2),Lx=λxa2,x0=0,y0=b,Amax=ab.

We must maximize A2=s(sx)(sy)(sz) subject to x+y+z=s. L=s(sx)(sy)(sz)λ(x+y+z) Lx=s(sy)(sz)λ,Ly=s(sx)(sz)λ,Lz=s(sx)(sy)λ s(sy0)(sz0)=s(sx0)(sz0)=s(sx0)(sy0)=λ,x0=y0=z0=s3.

We must maximize V=8xyz subject to x2a2+y2b2+z2c2=1. L=xyzλ2(x2a2+y2b2+z2c2) Lx=yzλxa2,Ly=xzλyb2,Lz=xyλzc2 y0z0=λx0a2,x0z0=λy0b2,x0y0=λzc2 x20a2=y20b2=z20c2=λx0y0z0 To satisfy the constraint, x0=a3, y0=b3, z0=c3, so Vmax=8abc33.

Let (x0,y0,z0) be the point on the plane closest to (x1,y1,z1), so ax0+by0+cz0=σ. L=(xx1)2+(yy1)2+(zz1)22λ(ax+by+cz) Lx=(xx1)λa,Ly=(yy1)λb,Lz=(zz1)λc x0=x1+λa,y0=y1+λb,\quad and\quadz0=z1+λc, d2=λ2(a2+b2+c2) (A) and (B) imply that ax1+by1+cz1+λ(a2+b2+c2)=σ, so λ=σax1by1cz1a2+b2+c2, and (C) implies that d=|σax1by1cz1|a2+b2+c2.

L=12ni=1[(xxi)2+(yyi)2+(zzi)2]λ(ax+by+cz) Lx=nxλani=1xi,Ly=nyλbni=1yi,Lz=nzλbni=1zi. x0=1n[λa+ni=1xi],y0=1n[λb+ni=1yi],z0=1n[λc+ni=1zi] ax0+by0+cz0=1n[λ(a2+b2+c2)+ni=1(axi+byi+czi)] Since ax0+by0+cz0=σ, λ=(a2+b2+c2)1ni=1(σaxibyiczi).

L=12(ni=1(xici)2λni=1x2i),  Lxi=xiciλxi,  xi0=(1λ)1ci

ni=1x2i0=(1λ)2nj=1c2j=1, so λ=1±μ where μ=(nj=1c2j)1/2 Since xi0=ci+λxi0 and ni=1x2i0=1, ni=1(xi0ci)2=λ2. Since xi0=(1λ)1ci, the constrained maximum is (1+μ)2, attained with xi0=ci/μ, 1in, and the constrained minimum is (1μ)2, attained with xi0=ci/μ, 1in.

[exer:19].

L=xy+xz+yzλ2(x2+y2+z2)

Lx=y+zλx,Ly=x+zλy,Lz=x+yλz

[011101110][x0y0z0]=λ[x0y0z0]. The eigenvalues of the matrix are 2 and 1, which are therefore the extremes of Q subject to the constraint.

L=3x2+2y2+3z2+2xz2λ2(x2+y2+z2)

Lx=3x+zλx,Ly=2yλy,Lz=3z+xλz

[301020103][x0y0z0]=λ[x0y0z0] The largest and smallest eigenvalues of the matrix are 4 and 2, which are therefore the extremes of Q subject to the constraint.

L=x2+8xy+4y2λ(x2+2xy+4y2)2 Lx=(x+4y)λ(x+y)=(1λ)x+(4λ)yLy=(4x+4y)λ(x+4y)=(4λ)x+4(1λy) [1λ4λ4λ4(1λ)][x0y0]=[00], so 4(λ1)2(λ4)2=3(λ2)(λ+2)=0. If λ=2, then x0=2y0. To satisfy the constraint, (x0,y0)=±(13,123) and f(x0,y0)=2. If λ=2, then x0=2y0. To satisfy the constraint, (x0,y0)=±(13,123) and f(x0,y0)=23.

L=α+βxyλ2(ax+by)2,  Lx=βyλa(ax+by),  Ly=βxλb(ax+by)

x0=λb(ax0+by0)β, y0=λa(ax0+by0)β, (x0,y0)=±(λbβ,λaβ)

ax0+by0=2λabβ=±1, λ=±β2ab, (x_{0},y_{0})=\displaystyle{\pm\left(\frac{1}{2a},\frac{1}{2b}\right)}

(\alpha+\beta x_{0}y_{0})_\text{max}=\displaystyle{\alpha+\frac{|\beta|}{4|ab|}}, (\alpha+\beta x_{0}y_{0})_\text{min}=\alpha-\displaystyle{\frac{|\beta|}{4|ab|}}

L=x+y^{2}+2z-\displaystyle{\frac{\lambda}{2}(4x^{2}+9y^{2}-36z^{2})}

L_{x}=1-4\lambda x,\; L_{y}=2y-9\lambda y, \; L_{z}=2+36\lambda z \nonumber x_{0}=\displaystyle{\frac{1}{4\lambda}},\; z_{0}=-\displaystyle{\frac{1}{18\lambda}}=-\frac{2}{9}x_{0}, \nonumber and either y_{0}=0 or \lambda=\displaystyle{\frac{2}{9}}. If y_{0}=0, then 36=4x_{0}^{2}-36z_{0}^{2}=\left(4-36\left(\frac{2}{9}\right)^{2}\right)x_{0}^{2} =\frac{20}{9}x_{0}^{2},\text{\quad so\quad} (x_{0},z_{0})=\pm \left(\frac{9}{\sqrt{5}},-\frac{2}{\sqrt{5}}\right) \nonumber and f(x_{0},0,z_{0})=x_{0}+2z_{0}=\pm\sqrt{5}. If \lambda=\displaystyle{\frac{2}{9}}, then x_{0}=\displaystyle{\frac{9}{8}} and z_{0}=-\displaystyle{\frac{1}{4}}, so 9y_{0}^{2}=36(1+z_{0}^{2})-4x_{0}^{2}=36\left(1+\frac{1}{16}\right)-4\left(\frac{81}{64}\right) =\frac{531}{16}, \text{\; so\;\;}y_{0}=\pm\displaystyle{\frac{\sqrt{59}}{4}}. \nonumber Therefore, the constrained maximum is f\left(\frac{9}{8},\frac{\sqrt{59}}{4},-\frac{1}{4}\right)= f\left(\frac{9}{8},-\frac{\sqrt{59}}{4},-\frac{1}{4}\right)=\frac{73}{16} and the constrained minimum is f\left(-\frac{9}{\sqrt{5}},0,\frac{2}{\sqrt{5}}\right)=-\sqrt{5}.

L=(x+z)(y+w)-\displaystyle{\frac{\lambda}{2}(x^{2}+y^{2}+z^{2}+w^{2})}

L_{x}=y+w-\lambda x,\, L_{y}=x+z-\lambda y,\, L_{z}=y+w -\lambda z, \, L_{w}=x+z-\lambda w \nonumber x_{0}+z_{0}=\lambda y_{0}=\lambda w_{0}, \quad y_{0}+w_{0}=\lambda x_{0}=\lambda z_{0} \nonumber

If \lambda=0, then all (x_{0},y_{0},-x_{0},w_{0}) with 2x_{0}^{2}+y_{0}^{2}+w_{0}^{2}=1 and all (x_{0},y_{0},z_{0},-y_{0}) with x_{0}^{2}+2y_{0}^{2}+z_{0}^{2}=1 are constrained critical points, with f(x_{0},y_{0},-x_{0},w_{0})=0 and f(x_{0},y_{0},z_{0},-y_{0}).

If \lambda \ne0, then y_{0}=w_{0} and x_{0}=z_{0}, so 2x_{0}=\lambda y_{0},\quad 2y_{0}=\lambda x_{0},\quad 2z_{0}=\lambda w_{0},\quad 2w_{0} =\lambda z_{0}, \nonumber and 2x_{0}=\lambda y_{0} =\frac{\lambda}{2}(2y_{0})=\frac{\lambda^{2}}{2}x_{0} \text{\; and \;\;}2z_{0}=\lambda w_{0}=\frac{\lambda}{2}(2w_{0})= \frac{\lambda^{2}}{2}z_{0}. \nonumber If \lambda\ne2, then x_{0}=y_{0}=z_{0}=w_{0}, which does not satisfy the constraint. If \lambda=2, then x_{0}=y_{0}=z_{0}=w_{0}=\pm\frac{1}{2}\text{\; and\;\;} (x_{0}+z_{0})(y_{0}+w_{0})=1. \nonumber If \lambda=-2, then x_{0}=-y_{0}=z_{0}=-w_{0}=\pm\frac{1}{2} \text{\; and\;\;} (x_{0}+z_{0})(y_{0}+w_{0})=-1. \nonumber Therefore, the constrained maximum is 1, attained at \pm\left(\frac{1}{2},\frac{1}{2},\frac{1}{2},\frac{1}{2}\right) the constrained minimum is -1, attained at \pm\left(\frac{1}{2},-\frac{1}{2},\frac{1}{2},-\frac{1}{2}\right).

L=(x+z)(y+w)-\displaystyle{\frac{\lambda}{2}(x^{2}+y^{2})} -\displaystyle{\frac{\mu}{2}(z^{2}+w^{2})}

L_{x}=y+w-\lambda x,\, L_{y}=x+z-\lambda y,\, L_{z}=y+w -\mu z, \, L_{w}=x+z-\mu w \nonumber \tag{A} x_{0}+z_{0}=\lambda y_{0}=\mu w_{0}, \quad y_{0}+w_{0}=\lambda x_{0}=\mu z_{0}

If \lambda=\mu=0, then z_{0}=-x_{0} and w_{0}=-y_{0}, (x_{0},y_{0},-x_{0},-y_{0}) satisfies the constraints and f(x_{0},y_{0},-x_{0},-y_{0})=0 for all (x_{0},y_{0}) such that x_{0}^{2}+y_{0}^{2}=1.

If \lambda=0 and \mu\ne0, then z_{0}=w_{0}=0, which does not satisfy the constraint z^{2}+y^{2}=1. If \mu=0 and \lambda\ne0, then x_{0}=y_{0}=0, which does not satisfy the constraint x^{2}+y^{2}=1.

Now assume that \lambda, \mu\ne0. From (A), \lambda(x_{0}^{2}+y_{0}^{2})=\mu^{2}(z_{0}^{2}+w_{0}^{2}), so \lambda=\pm\mu. If \lambda=-\mu, (A) implies that y_{0}=-w_{0} and x_{0}=-z_{0}, so again (x_{0},y_{0},-x_{0},-y_{0}) satisfies the constraints and f(x_{0},y_{0},-x_{0},-y_{0})=0 for all (x_{0},y_{0}) such that x_{0}^{2}+y_{0}^{2}=1.

If \lambda=\mu, (A) becomes x_{0}+z_{0}=\lambda y_{0}= \lambda w_{0},\quad y_{0}+w_{0}=\lambda x_{0}=\lambda z_{0}, \nonumber so y_{0}=w_{0}, x_{0}=z_{0}, 2x_{0}=\lambda y_{0}, and 2y_{0}=\lambda x_{0}, 4x_{0}=2\lambda y_{0}=\lambda^{2}x_{0}, so \lambda=\pm2.

If \lambda=2, x_{0}=y_{0}=z_{0}=w_{0}. To satisfy the constraints,

(x_{0},y_{0},z_{0},w_{0})=\pm\left( \frac{1}{\sqrt2}, \frac{1}{\sqrt2}, \frac{1}{\sqrt2}, \frac{1}{\sqrt2} \right), \text{\; so\;\;} \nonumber and the constrained maximum is f(x_{0},y_{0},z_{0},w_{0})=2.

If \lambda=-2, x_{0}=-y_{0}=z_{0}=-w_{0}. To satisfy the constraints, (x_{0},y_{0},z_{0},w_{0})=\pm\left( \frac{1}{\sqrt2}, - \frac{1}{\sqrt2}, \frac{1}{\sqrt2}, -\frac{1}{\sqrt2} \right), \text{\; so\;\;} \nonumber and the constrained minimum is f(x_{0},y_{0},z_{0},w_{0})=-2.

L=(x+z)(y+w)-\displaystyle{\frac{\lambda}{2}}(x^{2}+z^{2}) -\displaystyle{\frac{\mu}{2}}(y^{2}+w^{2})

L_{x}=y+w-\lambda x,\; L_{y}=x+z-\mu y,\; L_{w}=x+z-\mu w,\; L_{z}=y+w-\lambda z \nonumber

y_{0}+w_{0}=\lambda x_{0}, x_{0}+z_{0}=\mu y_{0}, x_{0}+z_{0}=\mu w_{0}, y_{0}+w_{0}=\lambda z_{0}

If \mu=0, then x_{0}=-z_{0}, so the constrained critical points are \pm\left(\frac{1}{\sqrt2},y_{0},-\frac{1}{\sqrt2},w_{0}\right) for all (y_{0},w_{0}) such that y_{0}^{2}+w_{0}^{2}=1; f=0 at all such points.

If \lambda=0, then y_{0}=-w_{0}, so the constrained critical points are \pm\left(x_{0},\frac{1}{\sqrt2},z_{0},-\frac{1}{\sqrt2}\right) for all (x_{0},z_{0}) such that x_{0}^{2}+z_{0}^{2}=1; f=0 at all such points.

Now suppose that \lambda\mu\ne0. Since \lambda x_{0}=\lambda z_{0} and \mu y_{0}=\mu w_{0}, x_{0}=z_{0} and y_{0}=w_{0}. Therefore, (x_{0},z_{0})=\pm\left(\frac{1}{\sqrt2},\frac{1}{\sqrt2}\right) and (y_{0},w_{0})=\pm\left(\frac{1}{\sqrt2},\frac{1}{\sqrt2}\right), so the constrained maximum is 2, attained at \pm(\frac{1}{\sqrt2},\frac{1}{\sqrt2},\frac{1}{\sqrt2},\frac{1}{\sqrt2}), and constrained minimum is -2, attained \pm\left(\frac{1}{\sqrt2},-\frac{1}{\sqrt2},\frac{1}{\sqrt2},-\frac{1}{\sqrt2}\right),

L=\displaystyle{\frac{(x_{1}-x_{2})^{2}+(y_{1}-y_{2})^{2}}{2}}- \displaystyle{\frac{\lambda}{2}}(x_{1}^{2}+y_{1}^{2})-\mu x_{2}y_{2}

L_{x_{1}}=x_{1}-x_{2}-\lambda x_{1},\; L_{x_{2}}=x_{2}-x_{1}-\mu y_{2},\; L_{y_{1}}=y_{1}-y_{2}-\lambda y_{1},\; L_{y_{2}}=y_{2}-y_{1}-\mu x_{2} \nonumber

(i) x_{10}-x_{20}=\lambda x_{10},(ii) y_{10}-y_{20}=\lambda y_{10}

(iii) x_{20}-x_{10}=\mu y_{20}, (iv) y_{20}-y_{10}=\mu x_{20}

Since 0<x_{10}<x_{20} and 0<y_{10}<y_{20}, \lambda<0 and \mu>0 Since x_{20}\ne0, \lambda \ne 1, (i) and (ii) imply that (v) x_{10}y_{20}=y_{10}x_{20}. From (i) and (iii), (vi) \lambda x_{10}=-\mu y_{20}; from (ii) and (iv), (vii) \lambda y_{10}=-\mu x_{20}. Since x_{20}y_{20}=1, (vi) and (vii) imply that x_{10}x_{20}=y_{10}y_{20}. This and (v) imply that \frac{x_{10}}{y_{10}}=\frac{x_{20}}{y_{20}}=\frac{y_{20}}{x_{20}}. \nonumber Therefore, x_{20}=y_{20}=1 and x_{10}=y_{10}=\frac{1}{\sqrt2}, so (x_{10}-x_{20})^{2}+(y_{10}-y_{20})^{2}= 2\left(1-\frac{1}{\sqrt 2}\right)^{2} \nonumber and the distance between the curves is \sqrt2-1.

L=\displaystyle{\frac{1}{2}}\left(\displaystyle{\frac{x^{2}}{\alpha^{2}}+\frac{y^{2}}{\beta^{2}}} +\frac{z^{2}}{\gamma^{2}}\right) -\lambda (ax+by+cz)

L_{x}=\frac{x}{\alpha^{2}}-\lambda a,\quad L_{y}=\frac{y}{\beta^{2}}-\lambda b,\quad L_{z}=\frac{z}{\gamma^{2}}-\lambda c \nonumber x_{0}=\lambda a \alpha^{2},\quad y_{0}=\lambda b \beta^{2},\quad z_{0}=\lambda c \gamma^{2} \nonumber ax_{0}+by_{0}+cz_{0}= \lambda[(a \alpha)^{2}+(b\beta)^{2}+(c\gamma^{2})]=d, \quad \lambda=\frac{d}{(a\alpha)^{2}+(b\beta^{2})+(c\gamma)^{2}} \nonumber \frac{x_{0}^{2}}{\alpha^{2}}+\frac{y_{0}^{2}}{\beta^{2}} +\frac{z_{0}^{2}}{\gamma^{2}}= \lambda^{2}[(a\alpha)^{2}+(b\beta)^{2}+(c\gamma)^{2}] = \frac{d^{2}}{(a\alpha)^{2}+(b\beta^{2})+(c\gamma)^{2}}. \nonumber

\displaystyle{L(x_{1},x_{2},\dots,x_{n})=\frac{(x_{1}-c_{1})^{2}+(x_{2}-c_{2})^2+ \cdots+(x_{n}-c_{n})^2}{2}} -\lambda(a_{1}x_{1}+a_{2}x_{2}+\cdots+a_{n}x_{n}) \nonumber L_{x_{i}}=x_{i}-c_{i}-\lambda a_{i}, 1\le i\le n. We must choose \lambda so that if x_{i0}=c_{i}+\lambda a_{i}, 1\le i\le n, then \begin{aligned} a_{1}x_{10}+a_{2}x_{20}+\cdots+a_{n}x_{n0}&=&a_{1}c_{1}+a_{2}c_{2}+\dots + a_{n}c_{n}\\ &+& \lambda (a_{1}^{2}+a_{2}^{2}+\cdots+ a_{n}^{2})=d,\end{aligned} \nonumber which holds if and only if \lambda=\frac{d-a_{1}c_{1}-a_{2}c_{2}-\cdots-a_{n}c_{n}} {a_{1}^{2}+a_{2}^{2}+\cdots +a_{n}^{2}}. \nonumber Therefore, x_{i0}=c_{i}+ \frac{(d-a_{1}c_{1}-a_{2}c_{2}-\cdots-a_{n}c_{n})a_{i}} {a_{1}^{2}+a_{2}^{2}+\cdots a_{n}^{2}},\quad 1\le i\le n, \nonumber and the distance from (x_{10},x_{10},\dots,x_{n0}) to (c_{1},c_{2},\dots,c_{n}) is \frac{|(d-a_{1}c_{1}-a_{2}c_{2}-\cdots-a_{n}c_{n})a_{i}|} {\sqrt{a_{1}^{2}+a_{2}^{2}+\cdots a_{n}^{2}}}. \nonumber

L=\displaystyle{\frac{1}{2}\sum_{i=1}^{n}a_{i}x_{i}^{2}- \frac{\lambda}{4}\sum_{i=1}^{n}b_{i}x_{i}^{4}}, L_{x_{i}}=a_{i}x_{i}-\lambda b_{i}x_{i}^{3}, a_{i}x_{i0}^{2}=\lambda b_{i}x_{i0}^{4}

\displaystyle{\sum_{i=1}^{n}a_{i}x_{i0}^{2}=\lambda \sum_{i=1}^{n} b_{i}x_{i0}^{4}=\lambda}, x_{i0}^{2}=\displaystyle{\frac{a_{i}}{\lambda b_{i}}}, \lambda=\displaystyle{\sum_{i=1}^{n}a_{i}x_{i0}^{2}= \frac{1}{\lambda}\sum_{i=1}^{n}\frac{a_{i}^{2}}{b_{i}}}, \lambda=\displaystyle{\left(\sum_{i=1}^{n}\frac{a_{i}^{2}}{b_{i}}\right)^{1/2}}

[exer:31].

L=\displaystyle{\frac{1}{p}\sum_{i=1}^{n}a_{i}x_{i}^{p}- \frac{\lambda}{q}\sum_{i=1}^{n}b_{i}x_{i}^{q}}, L_{x_{i}}=a_{i}x_{i}^{p}-\lambda b_{i}x_{i}^{q}, a_{i}x_{i0}^{p}=\lambda b_{i}x_{i0}^{q}

\displaystyle{\sum_{i=1}^{n}a_{i}x_{i0}^{p}=\lambda \sum_{i=1}^{n} b_{i}x_{i0}^{q}=\lambda}, x_{i0}^{q-p}=\displaystyle{\frac{a_{i}}{\lambda b_{i}}}, x_{i0}=\displaystyle{\left(\frac{a_{i}}{\lambda b_{i}}\right)^{1/(q-p)}}, x_{i0}^{p}=\displaystyle{\left(\frac{a_{i}}{\lambda b_{i}}\right)^{p/(q-p)}}

\lambda=\sum_{i=1}^{n}a_{i}x_{i0}^{p}=\lambda^{p/(p-q)} \sum_{i=1}^{n}a_{i}^{q/(q-p)} b_{i}^{p/(p-q)},\quad \nonumber \lambda^{q/(q-p)}= \sum_{i=1}^{n}a_{i}^{q/(q-p)} b_{i}^{p/(p-q)},\quad \lambda= \left(\sum_{i=1}^{n}a_{i}^{q/(q-p)} b_{i}^{p/(p-q)}\right)^{1-p/q}= \sum_{i=1}^{n}a_{i}x_{i0}^{p} \nonumber \lambda is the constrained maximum if p<q, the constrained minimum if p>q, undefined if p=q.

[exer:32]. L=\displaystyle{\frac{x^{2}+2y^{2}+z^{2}+w^{2}}{2}}-\lambda(x+y+z+3w)-\mu(x+y+2z+w) L_{x}=x-\lambda-\mu, \quad L_{y}=2y-\lambda-\mu, \quad L_{z}=z-\lambda-2\mu, \quad L_{w}=w-3\lambda-\mu \nonumber x_{0}=\lambda+\mu, \quad y_{0}=\frac{\lambda+\mu}{2}, \quad z_{0}=\lambda+2\mu, \quad w_{0}=3\lambda+\mu \nonumber x_{0}+y_{0}+z_{0}+3w_{0}=\frac{23}{2}\lambda+\frac{13}{2}\mu=1, \quad x_{0}+y_{0}+2z_{0}+w_{0}=\frac{13}{2}\lambda+\frac{13}{2}\mu=2 \nonumber \lambda=-\frac{1}{5},\, \mu=\frac{33}{65},\, x_{0}=\frac{4}{13},\, y_{0}=\frac{2}{13},\, z_{0}=\frac{53}{65},\, w_{0}=-\frac{6}{65},\,\ \min=\frac{689}{845} \nonumber

\displaystyle{L=\frac{1}{2}\left(\frac{x^{2}}{a^{2}}+\frac{y^{2}}{b^{2}}+\frac{z^{2}}{c^{2}}\right) -\lambda(p_{1}x+p_{2}y+p_{3}z)}

L_{x}=\displaystyle{\frac{x}{a^{2}}}-\lambda p_{1}, L_{y}=\displaystyle{\frac{y}{b^{2}}}-\lambda p_{2}, L_{z}=\displaystyle{\frac{z}{c^{2}}}-\lambda p_{3}

x_{0}=\lambda p_{1}a^{2}, y_{0}=\lambda p_{2}b^{2}, z_{0}=\lambda p_{3}c^{2}

p_{1}x_{0}+p_{2}y_{0}+p_{3}z_{0}= \lambda(p_{1}^{2}a^{2}+p_{2}^{2}b^{2}+p_{3}^{2}c^{2})=d

\lambda=\displaystyle{\frac{d}{p_{1}^{2}a^{2}+p_{2}^{2}b^{2}+p_{3}^{2}c^{2}}}, \displaystyle{\frac{x_{0}}{a}=\lambda p_{1}a}, \displaystyle{\frac{y_{0}}{b}=\lambda p_{2}b}, \displaystyle{\frac{z_{0}}{b}=\lambda p_{3}c}

\frac{x_{0}^{2}}{a^{2}}+\frac{y_{0}^{2}}{b^{2}}+\frac{z_{0}^{2}}{c^{2}} =\lambda^{2}(p_{1}^{2}a^{2}+p_{2}^{2}b^{2}+p_{3}^{2}c^{2}) =\frac{d^{2}}{p_{1}^{2}a^{2}+p_{2}^{2}b^{2}+p_{3}^{2}c^{2}} \nonumber

L=p_{1}x+p_{2}y+p_{3}z- \displaystyle{\frac{\lambda}{2}\left(\frac{x^{2}}{a^{2}}+\frac{y^{2}}{b^{2}}+ \frac{z^{2}}{c^{2}}\right)}

L_{x}=p_{1}-\lambda\displaystyle{\frac{x}{a^{2}}}, L_{y}=p_{2}-\lambda\displaystyle{\frac{y}{b^{2}}}, L_{z}=p_{3}-\lambda\displaystyle{\frac{z}{c^{2}}}

x_{0}=\displaystyle{\frac{p_{1}a^{2}}{\lambda}}, y_{0}=\displaystyle{\frac{p_{2}b^{2}}{\lambda}}, z_{0}=\displaystyle{\frac{p_{3}c^{2}}{\lambda}}

\frac{x_{0}^{2}}{a^{2}}+\frac{y_{0}^{2}}{b^{2}}+\frac{z_{0}^{2}}{c^{2}} =\frac{p_{1}^{2}a^{2}+p_{2}^{2}b^{2}+p_{3}^{2}c^{2}}{\lambda^{2}}=1 \nonumber \lambda=\pm(p_{1}^{2}a^{2}+p_{2}^{2}b^{2}+p_{3}^{2}c^{2})^{1/2} \nonumber p_{1}x_{0}+p_{2}y_{0}+p_{3}z_{0}= \frac{p_{1}^{2}a^{2}+p_{2}^{2}b^{2}+p_{3}^{2}c^{2}}{\lambda} =\pm (p_{1}^{2}a^{2}+p_{2}^{2}b^{2}+p_{3}^{2}c^{2})^{1/2} \nonumber

L=\displaystyle{\frac{(x+1)^{2}+(y-2)^{2}+(z-3)^{2}}{2}}-\lambda(x+2y-3z)-\mu(2x-y+2z)

L_{x}=x+1-\lambda-2\mu,\quad L_{y}=y-2-2\lambda +\mu,\quad L_{z}=z-3+3\lambda-2\mu \nonumber x_{0}=-1+\lambda+2\mu,\quad y_{0}=2+2\lambda-\mu, \quad z_{0}=3-3\lambda+2\mu \nonumber x_{0}+2y_{0}-3z_{0}-4=-10+14\lambda-6\mu,\quad 2x_{0}-y_{0}+2z_{0}-5=-3-6\lambda+9\mu \nonumber 7\lambda-3\mu=5, \quad -2\lambda+3\mu=1,\quad \lambda=\frac{18}{15}, \quad \mu=\frac{17}{15} \nonumber (x_{0},y_{0},z_{0})=\left(\frac{37}{15}, \frac{49}{15},\frac{25}{15}\right),\quad \nonumber \sqrt{(x_{0}+1)^{2}+(y_{0}-2)^{2}+(z_{0}-3)^{2}} =\left[\left(\frac{52}{15}\right)+\left(\frac{19}{15}\right)^{2}+ \left(\frac{20}{15}\right)^{2}\right]^{1/2}=\sqrt{\frac{693}{45}} \nonumber

L=2x+y+2z-\displaystyle{\frac{\lambda}{2}}(x^{2}+y^{2})-\mu(x+z)

L_{x}=2-\lambda x-\mu,\quad L_{y}=1-\lambda y,\quad L_{z}=2-\mu \nonumber \mu=2, so \lambda x_{0}=0. Since \lambda y_{0}=1, \lambda\ne0; hence, x_{0}=0. Since x_{0}^{2}+y_{0}^{2}=4, y_{0}=\pm2. Therefore, (0,2,2) and (0,-2,2), are constrained extreme points, and the constrained extreme values are f(0,2,2)=6 and f(0,-2,2)=2.

Let (x_{1},y_{1}) be on the parabola, (x_{2},y_{2}) on the line. L=\frac{(x_{1}-x_{2})^{2}+(y_{1}-y_{2})^{2}}{2} -\lambda(y_{1}-x_{1}^{2})-\mu(x_{2}+y_{2}). \nonumber L_{x_{1}}=x_{1}-x_{2}+2\lambda x_{1},\, L_{x_{2}}=x_{2}-x_{1}-\mu,\, \nonumber L_{y_{1}}=y_{1}-y_{2}-\lambda,\, L_{y_{2}}=y_{2}-y_{1}-\mu \nonumber \begin{aligned} x_{10}-x_{20}&=&-2\lambda x_{10}\\ x_{20}-x_{10}&=&\mu\\ y_{10}-y_{20}&=&\lambda\text{\quad (i)}\\ y_{20}-y_{10}&=&\mu\text{\quad (ii)}\end{aligned} \nonumber From (i) and (ii), \lambda=-\mu, so \begin{aligned} x_{10}-x_{20}&=& 2\mu x_{10}\text{\quad (i)}\\ x_{20}-x_{10}&=&\mu\text{\quad\quad \;\, (ii)}\\ y_{20}-y_{10}&=&\mu\text{\quad\quad \;\, (iii)}\end{aligned} \nonumber From (i) and (ii), x_{10}=-1/2, so y_{10}=1+x_{10}^{2}=5/4 and 2\mu=x_{20}+y_{20}-x_{10}-y_{10}=-1+\frac{1}{2}-\frac{5}{4}=-\frac{7}{4}, \nonumber since x_{20}+y_{20}=-1 (constraint). Therefore, \mu=-7/8 so (ii) and (iii) imply that x_{20}=x_{10}=\mu=-\frac{1}{2}-\frac{7}{8}=-\frac{11}{8} \text{\; and\;\;} y_{20}=y_{10}-\frac{7}{8}=\frac{5}{4}-\frac{7}{8}=\frac{3}{8}. \nonumber The distance between the line and the parabola is \sqrt{(x_{10}-x_{20})^{2}+(y_{10}-y_{20})^{2}}=\frac{7}{4\sqrt{2}}. \nonumber

Let (x_{1},y_{1},z_{1}) be on the ellipsoid and (x_{2},y_{2},z_{2}) be on the plane. L= \frac{(x_{1}-x_{2})^{2}+(y_{1}-y_{2})^{2}+(z_{1}-z_{2})^{2}}{2} -\frac{\lambda}{2}(3x_{1}^{2}+9y_{1}^{2}+6z_{1}^{2}) -\mu(x_{2}+y_{2}+2z_{2}). \nonumber L_{x_{1}}=x_{1}-x_{2}-3\lambda x_{1}=0,\quad L_{y_{1}}=y_{1}-y_{2}-9\lambda y_{1}=0,\quad L_{z_{1}}=z_{1}-z_{2}-6\lambda z_{1} \nonumber L_{x_{2}}=x_{2}-x_{1}-\mu,\quad Ly_{2}=y_{2}-y_{1}-\mu,\quad L_{z_{2}}=z_{2}-z_{1}-2\mu \nonumber \begin{aligned} x_{10}-x_{20}&=& 3\lambda x_{10}\\ y_{10}-y_{20}&=& 9\lambda y_{10}\\ z_{10}-z_{20}&=& 6\lambda z_{10}\\ x_{20}-x_{10}&=& \mu\\ y_{20}-y_{10}&=& \mu \\ z_{20}-z_{10}&=& 2\mu\end{aligned} \nonumber Therefore, 3\lambda x_{10}=-\mu, 9\lambda y_{10}=-\mu, and 3\lambda z_{10}=-\mu, so y_{10}=x_{1}/3 and z_{10}=x_{10}. Since (x_{10},x_{10}/3,x_{10}) is on the ellipsoid if and only if x_{10}=\pm1, either \text{\; (a)\;\;}(x_{10},y_{10},z_{10})=\left(1,\frac{1}{3},1\right) \text{\; or \quad (b)\;\;} (x_{10},y_{10},z_{10})=\left(-1,-\frac{1}{3},-1\right). \nonumber Since \tag{A} x_{2}=x_{1}+\mu,\quad y_{2}=y_{1}+\mu,\quad z_{2}=z_{1}+2\mu, \tag{B} (x_{10}-x_{20})^{2}+(y_{10}-y_{20})^{2}+(z_{10}-z_{20})=6\mu^{2}, \text{\; so\;\;} d=\mu.\sqrt{6}. Since 3x_{20}+3y_{20}+6z_{20}=70, (A) implies that \mu=\frac{70-3x_{10}-3y_{10}-6z_{10}}{18}, \nonumber

In Case (a) \mu=\frac{10}{3} so (A) implies that d=\frac{10\sqrt{6}}{3} In case (b) \mu=\frac{40}{9}>\frac{10}{3}, so the distance between the plane and the ellipsoid is \frac{10\sqrt{6}}{3}.

L=xy+yz+zx-\displaystyle{\frac{\lambda}{2} \left(\frac{x^{2}}{a^{2}}+\frac{y^{2}}{b^{2}}+\frac{z^{2}}{c^{2}}\right)} L_{x}=y+z-\lambda\frac{x}{a^{2}},\quad L_{y}=z+x-\lambda\frac{y}{b^{2}},\quad L_{z}=x+y-\lambda\frac{z}{c^{2}} \nonumber y_{0}+z_{0}=\lambda\frac{x_{0}}{a^{2}},\quad z_{0}+x_{0}=\lambda\frac{y_{0}}{b^{2}},\quad x_{0}+y_{0}-\lambda\frac{z_{0}}{c^{2}} \nonumber \left[\begin{array}{ccccccc} 0&a^{2}&a^{2}\\ b^{2}&0&b^{2}\\c^{2}&c^{2}&0 \end{array}\right] \left[\begin{array}{ccccccc} x_{0}\\y_{0}\\z_{0} \end{array}\right]=\lambda \left[\begin{array}{ccccccc} x_{0}\\y_{0}\\z_{0} \end{array}\right] \nonumber x_{0}(y_{0}+z_{0})=\lambda\frac{x_{0}^{2}}{a^{2}},\quad y_{0}(z_{0}+x_{0})=\lambda\frac{y_{0}^{2}}{b^{2}},\quad z_{0}(x_{0}+y_{0})=\lambda\frac{z_{0}^{2}}{c^{2}}, \nonumber

x_{0}(y_{0}+z_{0})+ y_{0}(z_{0}+x_{0})+ z_{0}(x_{0}+y_{0})= \lambda\left(\frac{x_{0}^{2}}{a^{2}}+\frac{y_{0}^{2}}{b^{2}}+\frac{z_{0}^{2}}{c^{2}}\right) =\lambda \nonumber

L=xy+2yz+2zx-\lambda \displaystyle{\left(\frac{x^{2}}{a^{2}}+\frac{y^{2}}{b^{2}}+\frac{z^{2}}{c^{2}}\right)} L_{x}=y+2z-2\lambda\frac{x}{a^{2}},\quad L_{y}=x+2z-2\lambda\frac{y}{b^{2}},\quad L_{z}=2x+2y-2\lambda\frac{z}{c^{2}} \nonumber y_{0}+2z_{0}=2\lambda\frac{x_{0}}{a^{2}},\quad x_{0}+2z_{0}=2\lambda\frac{y_{0}}{b^{2}},\quad 2x_{0}+2y_{0}-2\lambda\frac{z_{0}}{c^{2}} \nonumber

\left[\begin{array}{ccccccc} 0&a^{2}/2&a^{2}\\ b^{2}/2&0&b^{2}\\c^{2}&c^{2}&0 \end{array}\right] \left[\begin{array}{ccccccc} x_{0}\\y_{0}\\z_{0} \end{array}\right]=\lambda \left[\begin{array}{ccccccc} x_{0}\\y_{0}\\z_{0} \end{array}\right]. \nonumber

x_{0}(y_{0}+2z_{0})=2\lambda\frac{x_{0}^{2}}{a^{2}},\quad y_{0}(x_{0}+2z_{0})=2\lambda\frac{y_{0}^{2}}{b^{2}};\quad z_{0}(2x_{0}+2y_{0})=2\lambda\frac{z_{0}^{2}}{c^{2}}, \nonumber \frac{x_{0}(y_{0}+2z_{0})+ y_{0}(x_{0}+2z_{0})+ z_{0}(2x_{0}+2y_{0})}{2}= \lambda\left(\frac{x_{0}^{2}}{a^{2}}+\frac{y_{0}^{2}}{b^{2}}+\frac{z_{0}^{2}}{c^{2}}\right) =\lambda, \nonumber

L=xz+yz-\displaystyle{\frac{\lambda}{2} \left(\frac{x^{2}}{a^{2}}+\frac{y^{2}}{b^{2}}+\frac{z^{2}}{c^{2}}\right)} L_{x}=z-\lambda\frac{x}{a^{2}},\quad L_{y}=z-\lambda\frac{y}{b^{2}},\quad L_{z}=x+y-\lambda\frac{z}{c^{2}} \nonumber z_{0}=\lambda\frac{x_{0}}{a^{2}},\quad z_{0}=\lambda\frac{y_{0}}{b^{2}},\quad x_{0}+y_{0}=\lambda\frac{z_{0}}{c^{2}},\text{\; so\;\;} \frac{a^{2}}{\lambda}+\frac{b^{2}}{\lambda}=\frac{\lambda}{c^{2}}. \nonumber Therefore, \lambda=\pm |c|\sqrt{a^{2}+b^{2}}. To determine z_{0}, note that x_{0}=\displaystyle{\frac{a^{2}z_{0}}{\lambda}} and y_{0}=\displaystyle{\frac{b^{2}z_{0}}{\lambda}}. Therefore, 1=\frac{x_{0}^{2}}{a^{2}} +\frac{y_{0}^{2}}{b^{2}}+\frac{z_{0}^{2}}{c^{2}} = \left(\frac{a^{2}+b^{2}}{\lambda^{2}}+\frac{1}{c^{2}}\right)z_{0}^{2}= \frac{2z_{0}^{2}}{c^{2}}, \nonumber so z_{0}=\pm\frac{|c|}{\sqrt2}\text{\; and\;\;} (x_{0},y_{0},z_{0})=\pm \left(\frac{a^{2}}{\sqrt{2(a^{2}+b^{2})}}, \frac{b^{2}}{\sqrt{2(a^{2}+b^{2})}}, \displaystyle{\frac{|c|}{\sqrt{2}}} \right) \nonumber (x_{0}+y_{0})z_{0}=\displaystyle{\frac{\lambda z_{0}^{2}}{c^{2}}}=\pm\frac{\lambda}{2}=\pm \frac{|c|\sqrt{a^{2}+b^{2}}}{2}. \nonumber

L=x^{\alpha}y^{\beta}z^{\gamma}-\lambda(ax^{p}+by^{q}+cz^{r})

L_{x}=\alpha x^{\alpha-1}y^{\beta}z^{\gamma}-\lambda pax^{p-1},\quad L_{y}=\beta x^{\alpha}y^{\beta-1}z^{\gamma}-\lambda qby^{q-1} \nonumber L_{z}=\gamma x^{\alpha}y^{\beta}z^{\gamma-1}-\lambda rcz^{r-1} \nonumber \displaystyle{\frac{p}{\alpha}ax_{0}^{p}=\frac{q}{\beta}by_{0}^{q}=\frac{r}{\gamma}cz_{0}^{q}=C} \nonumber where C is to be determined as follows: \displaystyle{ax_{0}^{p}=\frac{C\alpha}{p},\quad by_{0}^{q}=\frac{C\beta}{q},\quad cz_{0}^{q}=\frac{C\gamma}{r}} \nonumber From the constraint, ax_{0}^p+by_{0}^{p}+cz_{0}^{r}=1, \nonumber so C=\displaystyle{\left(\frac{\alpha}{p}+\frac{\beta}{q}+\frac{\gamma}{r}\right)^{-1}} \text{\; and\;\;} \displaystyle{x_{0}^{p}y_{0}^{q}z_{0}^{r}=\frac{\alpha\beta\gamma}{pqr} \left(\frac{\alpha}{p}+\frac{\beta}{q}+\frac{\gamma}{r}\right)^{-3}}. \nonumber

L=xw-yz-\displaystyle{\frac{\lambda (x^{2}+2y^{2})}{2}-\frac{\mu(2z^{2}+w^{2})}{2}}

L_{x}=w-\lambda x,\quad L_{y}=-z-2\lambda y,\quad L_{z}=-y-2\mu z,\quad L_{w}=x-\mu w \nonumber w_{0}=\lambda x_{0},\quad z_{0}=-2\lambda y_{0},\quad y_{0}=-2\mu z_{0},\quad x_{0}=\mu w_{0} \nonumber The first and last equality imply that w_{0}=\lambda\mu w_{0} and z_{0}=4\lambda\mu z_{0}. Since
2z_{0}^{2}+w_{0}^{2}=9, w_{0} and z_{0} cannot both be zero, so either \lambda\mu=1 or 4\lambda\mu=1.

If \lambda\mu=1, z_{0}=y_{0}=0, x_{0}^{2}=4, and w_{0}^{2}=9, so the constrained critical values are f(2,0,0,3)=f(-2,0,0,-3)=6 \text{\; and\;\;} f(-2,0,0,3)=f(2,0,0,-3)=-6. \nonumber

If 4\lambda\mu=1, then x_{0}=w_{0}=0, y_{0}^{2}=2 and z_{0}^{2}=9/2, so the constrained critical values are f\left(0,\sqrt{2},\frac{3}{\sqrt{2}},0\right)= f\left(0,-\sqrt{2},-\frac{3}{\sqrt{2}},0\right)=3 \nonumber and f\left(0,\sqrt{2},-\frac{3}{\sqrt{2}},0\right)= f\left(0,-\sqrt{2},\frac{3}{\sqrt{2}},0\right)= -3. \nonumber Hence the constrained maximum and minimum values are 3 and -3.

L=xw-yz-\displaystyle{ \frac{\lambda}{2}(ax^{2}+by^{2})-\frac{\mu}{2}(cz^{2}+dw^{2})}

L_{x}=w-a\lambda x,\quad L_{y}=-z-b\lambda y, \nonumber L_{z}=-y-c\mu z=0,\quad L_{w}=x-d\mu w=0 \nonumber x_{0}=\mu dw_{0},\quad y_{0}=-c\mu z_{0},\quad z_{0}=-b\lambda y_{0}, \text{\; and\;\;} w_{0}=\lambda a x_{0}. \nonumber This implies that x_{0}w_{0}-y_{0}z_{0}=\lambda (ax_{0}^{2}+by_{0}^{2})=\lambda \text{\; and\;\;} x_{0}w_{0}-y_{0}z_{0}=\mu(cz_{0}^{2}+dw_{0}^{2}) =\mu, \nonumber so \lambda =\mu. Therefore, x_{0}=\lambda dw_{0},\quad y_{0}=-c\lambda z_{0},\quad z_{0}=-b\lambda y_{0}, \text{\; and\;\;} w_{0}=\lambda a x_{0}, \nonumber so z_{0}=bc\lambda^{2} z_{0} and w_{0}=ad\lambda^{2}w_{0}. Since cz_{0}^{2}+dw_{0}^{2}=1, w_{0} and z_{0} cannot both be zero; hence, either ad\lambda^{2}=1 or bc\lambda^{2}=1.

Suppose that ad\ne bc. If \lambda^{2} ad=1, then \lambda^{2} bc\ne1, so z_{0}=y_{0}=0, and the constraints imply that x_{0}^{2}=1/a, and w_{0}^{2}=1/d. Therefore, the constrained maximum is \displaystyle{\frac{1}{\sqrt{ad}}},\text{\; attained at\;\;} \pm \displaystyle{\left(\frac{1}{\sqrt{a}},0,0,\frac{1}{\sqrt{d}}\right)} \nonumber and the constrained minimum is -\displaystyle{\frac{1}{\sqrt{ad}}},\text{\; attained at\;\;} \pm \displaystyle{\left(-\frac{1}{\sqrt{a}},0,0,\frac{1}{\sqrt{d}}\right)}. \nonumber If \lambda^{2} bc=1, then \lambda^{2} ad\ne1, so x_{0}=w_{0}=0 and the constraints imply that y_{0}^{2}=1/b and z_{0}^{2}=1/c. Therefore, the constrained maximum is \displaystyle{\frac{1}{\sqrt{bc}}}, \text{\; attained at\;\;} \pm \displaystyle{\left(0,\frac{1}{\sqrt{b}},-\frac{1}{\sqrt{c}},0\right)}, \nonumber and the constrained minimum is -\displaystyle{\frac{1}{\sqrt{bc}}}, \text{\; attained at\;\;} \pm \displaystyle{\left(0,\frac{1}{\sqrt{b}},\frac{1}{\sqrt{c}},0\right)}. \nonumber

Suppose that ad=bc. Since x_{0}=\lambda dw_{0} and y_{0}=-c\lambda z_{0}, 1=ax_{0}^{2}+by_{0}^{2}=\lambda^{2}[(ad)dw_{0}^2+(bc)cz_{0}^{2}]= \lambda^{2}ad(cz_{0}^{2}+d(w_{0})^{2}=\lambda^{2}ad, \nonumber so \lambda=\pm \displaystyle{\frac{1}{\sqrt {ad}}}=\pm\frac{1}{\sqrt{bc}}. Therefore, the constrained maximum value of f is \displaystyle{\frac{1}{\sqrt {ad}}}=\frac{1}{\sqrt{bc}}, is attained at all points of the form \displaystyle{\left(w_{0}\sqrt{\frac{d}{a}},-z_{0}\sqrt{\frac{c}{b}},z_{0},w_{0}\right)} and the constrained minimum value of f is -\displaystyle{\frac{1}{\sqrt {ad}}}=-\frac{1}{\sqrt{bc}}, attained at all points of the form \displaystyle{\left(-w_{0}\sqrt{\frac{d}{a}},z_{0}\sqrt{\frac{c}{b}},z_{0},w_{0}\right)} where, in both cases, cz_{0}^2+dw_{0}^{2}=1. Alternatively, all the constrained maximum points are of the form \displaystyle{\left(x_{0},y_{0},-y_{0}\sqrt{\frac{b}{c}},x_{0}\sqrt{\frac{a}{d}}\right)} and all the constrained minimum points are of the form \displaystyle{\left(x_{0},y_{0},y_{0}\sqrt{\frac{b}{c}},-x_{0}\sqrt{\frac{a}{d}}\right)} where, in both cases, ax_{0}^{2}+by_{0}^{2}=1.

L=\displaystyle{\frac{\alpha x^{2}+\beta y^{2}+\gamma z^{2}}{2}} -\lambda(a_{1}x+a_{2}y+a_{3}z)-\mu(b_{1}x+b_{2}y+b_{3}z)

L_{x}=\alpha x-\lambda a_{1}-\mu b_{1},\quad L_{y}=\beta y-\lambda a_{2}-\mu b_{2}, \quad L_{z}=\gamma y-\lambda a_{3}-\mu b_{3} \nonumber

\tag{A} x_{0}=\frac{\lambda a_{1}+\mu b_{1}}{\alpha},\quad y_{0}=\frac{\lambda a_{2}+\mu b_{2}}{\beta},\quad z_{0}=\frac{\lambda a_{3}+\mu b_{3}}{\gamma}.

\tag{B} \frac{a_{1}(\lambda a_{1}+\mu b_{1})}{\alpha}+ \frac{a_{2}(\lambda a_{2}+\mu b_{2})}{\beta}+ \frac{a_{3}(\lambda a_{3}+\mu b_{3})}{\gamma}=c.

\tag{C} \frac{b_{1}(\lambda a_{1}+\mu b_{1})}{\alpha}+ \frac{b_{2}(\lambda a_{2}+\mu b_{2})}{\beta}+ \frac{b_{3}(\lambda a_{3}+\mu b_{3})}{\gamma}=d.

Assume that {\bf u}=\frac{a_{1}}{\sqrt{\alpha}}{\bf i}+ \frac{a_{2}}{\sqrt{\beta}}{\bf j}+ \frac{a_{3}}{\sqrt{\gamma}}{\bf k} \text{\; and\;\;} {\bf v}=\frac{b_{1}}{\sqrt{\alpha}}{\bf i}+ \frac{b_{2}}{\sqrt{\beta}}{\bf j}+ \frac{b_{3}}{\sqrt{\gamma}}{\bf k} \nonumber are linearly independent. Then (B) and (C) can be written as \tag{D} |{\bf u}|^{2}\lambda+({\bf u}\cdot{\bf v})\mu=c,\quad ({\bf u}\cdot{\bf v})\lambda+|{\bf v}|^2\mu=d. Since {\bf u} and {\bf v} are linearly independent, \Delta=_\text{def}|{\bf u}|^{2}|{\bf v}|^{2}-({\bf u}\cdot{\bf v})^{2}\ne0. Therfore the solution of (D) is \lambda=\frac{c|{\bf v}|^{2}-d({\bf u}\cdot{\bf v})}{\Delta},\quad \mu=\frac{d|{\bf u}|^{2}-c({\bf u}\cdot{\bf v})}{\Delta}. \nonumber From (A), \begin{aligned} \alpha x_{0}^2+\beta y_{0}^{2}+\gamma z_{0}^{2} &=& (\lambda a_{1}+\mu b_{1})^{2}+ (\lambda a_{2}+\mu b_{2})^{2}+ (\lambda a_{3}+\mu b_{3})^{2}\\ &=& \lambda^{2} (a_{1}^{2}+a_{2}^{2}+a_{3}^{2})+ \mu^{2} (b_{1}^{2}+b_{2}^{2}+b_{3}^{2})\\ &&+ 2\lambda\mu(a_{1}b_{1}+a_{2}b_{2}+a_{3}b_{3}).\end{aligned} \nonumber

L=\displaystyle{\frac{1}{2}\sum_{i=1}^{n}(x_{i}-\alpha_{i})^{2}- \lambda\sum_{i=1}^{n}a_{i}x_{i}-\mu\sum_{i=1}^{n}b_{i}x_{i}}

L_{x_{i}}=x_{i}-\alpha_{i}-\lambda a_{i}-\mu_{i} b_{i},\quad x_{i0}=\alpha_{i}+\lambda a_{i}+\mu b_{i} \nonumber c=\sum_{i=1}^{n}a_{i}x_{i0}=\sum_{i=1}^{n}a_{i}\alpha_{i} +\lambda \sum_{i=1}^{n}a_{i}^{2}+\mu\sum_{i=1}^{n}a_{i}b_{i} = \sum_{i=1}^{n}a_{i}\alpha_{i} +\lambda \nonumber

d=\sum_{i=1}^{n}b_{i}x_{i0}=\sum_{i=1}^{n}b_{i}\alpha_{i} +\lambda \sum_{i=1}^{n}a_{i}b_{i}+\mu\sum_{i=1}^{n}b_{i}^{2} = \sum_{i=1}^{n}b_{i}\alpha_{i} +\mu \nonumber

\lambda=c-\sum_{i=1}^{n}a_{i}\alpha_{i},\quad \mu=d-\sum_{i=1}^{n}b_{i}\alpha_{i} \nonumber \begin{aligned} \sum_{i=1}^{n}(x_{i0}-\alpha_{i})^{2}&=& \sum_{i=1}^{n}(\lambda a_{i}+\mu b_{i})^{2} =\lambda^{2}\sum_{i=1}^{n}a_{i}^{2}\\&+&2\lambda \mu\sum_{i=1}^{n}a_{i}b_{i} +\mu^{2}\sum_{i=1}^{n}b_{i}^{2}=\lambda^{2}+\mu^{2}\\ &=&\left(c-\sum_{i=1}^{n}a_{i}\alpha_{i}\right)^{2} +\left(d-\sum_{i=1}^{n}b_{i}\alpha_{i}\right)^{2}\end{aligned} \nonumber

L=\displaystyle{\frac{1}{2}}\sum_{i=1}^{n}x_{i}^{2}- \lambda\sum_{i=1}^{n}x_{i}-\mu\sum_{i=1}^{n}jx_{i}; L_{x_{i}}=x_{i}-\lambda-\mu i, so x_{i0}=\lambda+\mu i. To satisfy the constraints, \displaystyle{\sum_{i=1}^{n}(\lambda+ \mu i)=1} \text{\; and\;\;} \displaystyle{\sum_{i=1}^{n}i(\lambda+ \mu i)=0}. \tag{A} Let s_{0}=n, \quad s_{1}=\sum_{j=1}^{n}i=\frac{n(n+1)}{2},\text{\; and\;\;} s_{2}=\sum_{i=1}^{n}i^{2}=\frac{n(n+1)(2n+1)}{6}. \nonumber Then (A) is equvalent to, \left[\begin{array}{ccccccc} s_{0}&s_{1}\\ s_{1}&s_{2} \end{array}\right] \left[\begin{array}{ccccccc} \lambda\\\mu \end{array}\right] = \left[\begin{array}{ccccccc} 1\\0 \end{array}\right]. \nonumber

By Cramer’s rule, \lambda=\frac{s_{2}}{s_{0}s_{2}-s_{1}^{2}}=\frac{2(2n+1)}{n(n-1)} \text{\; and\;\;} \mu=-\frac{s_{1}}{s_{0}s_{2}-s_{1}^{2}}=-\frac{6}{n(n-1)}. \nonumber Therefore, x_{i0}=\displaystyle{\frac{4n+2-6i}{n(n-1)}},\quad 1\le i\le n. \nonumber

If \sum_{i=1}^{n}y_{i}=1\text{\; and\;\;}\sum_{i=1}^{n}iy_{i}=0, \text{\; then\;\;}\sum_{i=1}^{n}(y_{i}-x_{i0})x_{i0}=0, \nonumber so \begin{aligned} \sum_{i=1}^{n}y_{i}^{2}&=&\sum_{i=1}^{n}(y_{i}-x_{i0}+x_{i0})^{2} +\sum_{i=1}^{n}(y_{i}-x_{i0})^{2}+ 2\sum_{i=1}^{n}(y_{i}-x_{i0})x_{i0} +\sum_{i=1}^{n}x_{i0}^{2}\\ &=& \sum_{i=1}^{n}(y_{i}-x_{i0})^{2}+ \sum_{i=1}^{n}x_{i0}^{2}>\sum_{i=1}^{n}x_{i0}^{2}\end{aligned} \nonumber if y_{i}\ne x_{i0} for some i\in\{1,2,\dots,n\}.

L=f({\bf X})- \lambda (x_{1}+x_{2}+\cdots+x_{n})

L_{x_{i}}=-\frac{p_{i}f({\bf X})}{s-x_{i}}- \lambda,\text{\; so\;\;} \frac{s-x_{10}}{p_{1}}= \frac{s-x_{20}}{p_{2}}=\cdots= \frac{s-x_{n0}}{p_{n}}=_\text{ def}C. \nonumber x_{i0}=s-Cp_{i}, 1\le i\le n. Denote P=p_{1}+p_{2}+\cdots +p_{n}.

x_{1}+x_{2}+\cdots+x_{n}=ns-C(p_{1}+p_{2}+\cdots+p_{n})=ns-CP=s. \nonumber \displaystyle{C=\frac{(n-1)s}{P}};\quad x_{i0}=\displaystyle{\frac{[P-(n-1)]sp_{i}}{P}}. \nonumber f_\text{max}=C^{P}p_{1}^{p_{1}}p_{2}^{p_{2}}\cdots p_{n}^{p_{n}}= \left[\frac{(n-1)s}{P}\right]^{P}p_{1}^{p_{1}}p_{2}^{p_{2}}\cdots p_{n}^{p_{n}} \nonumber

[exer:49]. L({\bf X})=\displaystyle{f({\bf X})-\lambda \sum_{i=1}^{n}\frac{x_{i}}{\sigma_{i}}}, L_{x_{i}}=\displaystyle{\frac{p_{i}f({\bf X})}{x_{i}}-\frac{\lambda}{\sigma_{i}}}, so \displaystyle{\frac{x_{i0}}{\sigma_{i}}}=Cp_{i}. To satisfy the constraint, C=(p_{1}+p_{2}\cdots+p_{n})^{-1}, so x_{i0}=\displaystyle{\frac{p_{i}\sigma_{i}S}{p_{1}+p_{2}+\cdots+p_{n}}}. \nonumber and x_{10}^{p_{1}}x_{20}^{p_{2}}\cdots x_{n0}^{p_{n}}= \left(\frac{S}{p_{1}+p_{2}+\cdots+ p_{n}}\right)^{p_{1}+p_{2}+\cdots+p_{n}} (p_{1}\sigma_{1})^{p_{1}} (p_{2}\sigma_{2})^{p_{2}} \cdots (p_{n}\sigma_{n})^{p_{n}} \nonumber

\displaystyle{L=\sum_{i=1}^{n}\frac{x_{i}}{\sigma_{i}}- \lambda x_{1}^{p_{1}}x_{2}^{p_{2}}\cdots x_{n}^{p_{n}}}, L_{x_{i}}=\displaystyle{\frac{1}{\sigma_{i}}-\lambda\frac{p_{i}V}{x_{i}}}, \displaystyle{\frac{x_{i0}}{\sigma_{i}}}=Cp_{i}, where C must be chosen to satisfy the constraints.

x_{i0}=C\sigma_{i}p_{i}, x_{i0}^{p_{i}}=(C\sigma_{i}p_{i})^{p_{i}}, V=(C\sigma_{1}p_{1})^{p_{1}} (C\sigma_{2}p_{2})^{p_{2}}\cdots (C\sigma_{n})^{p_{n}} C^{p_{1}+p_{2}+\cdots+p_{n}}=\frac{V}{(\sigma_{1}p_{1})^{p_{1}}(\sigma_{2}p_{2})^{p_{2}} \cdots (\sigma_{ n}p_{n})^{p_{n}}} \nonumber

C=\left(\frac{V}{(\sigma_{1}p_{1})^{p_{1}}(\sigma_{2}p_{2})^{p_{2}} \cdots (\sigma_{ n}p_{n})^{p_{n}}}\right)^{\frac{1}{p_{1}+p_{2}+\cdots+p_{n}}} \nonumber \frac{x_{i0}}{\sigma_{i}}=p_{i} \left(\frac{V}{(\sigma_{1}p_{1})^{p_{1}}(\sigma_{2}p_{2})^{p_{2}} \cdots (\sigma_{ n}p_{n})^{p_{n}}}\right)^{\frac{1}{p_{1}+p_{2}+\cdots+p_{n}}} \nonumber

\sum_{i=1}^{n}\frac{x_{i0}}{\sigma_{i}}=(p_{1}+p_{2}+\cdots+p_{n}) \left(\frac{V}{(\sigma_{1}p_{1})^{p_{1}}(\sigma_{2}p_{2})^{p_{2}} \cdots (\sigma_{ n}p_{n})^{p_{n}}}\right)^{\frac{1}{p_{1}+p_{2}+\cdots+p_{n}}}. \nonumber

L=\displaystyle{\frac{1}{2}\sum_{i=1}^{n}\frac{(x_{i}-c_{i})^{2}}{\alpha_{i}}} -\lambda (a_{1}x_{1}+a_{2}x_{2}+\cdots+a_{n}x_{n})

L_{x_{i}}=\displaystyle{\frac{x_{i}-c_{i}}{\alpha_{i}}}-\lambda a_{i},\quad x_{i0}=c_{i}+\lambda a_{i}\alpha_{i} \nonumber \sum_{i=1}^{n}a_{i}x_{i0}=\sum_{i=1}^{n}a_{i}c_{i}+ \lambda\sum_{i=1}^{n}a_{i}^{2}\alpha_{i}=d,\quad \lambda=\frac{d-\sum_{i=1}^{n}a_{i}c_{i}}{\sum_{i=1}^{n}a_{i}^{2}\alpha_{i}} \nonumber \sum_{i=1}^{n}\frac{(x_{i0}-c_{i})^{2}}{\alpha_{i}}=\lambda^{2} \sum_{i=1}^{n}a_{i}^{2}\alpha_{i}= \frac{(d-\sum_{i=1}^{n}a_{i}c_{i})^{2}}{\sum_{i=1}^{n}a_{i}^{2}\alpha_{i}} \nonumber

It suffices to extremize \displaystyle{\sum_{i=1}^{n}a_{i}x_{i}} subject to \sum_{i=1}^{n}x_{i}^{2}=\sigma^{2} for arbitrary \sigma>0. L=\displaystyle{\sum_{i=1}^{n}a_{i}x_{i}-\frac{\lambda}{2}\sum_{i=1}^{n}x_{i}^{2}}, \quad L_{y_{i}}=a_{i}-\lambda x_{i},\quad a_{i}=\lambda x_{i0}, \nonumber \sum_{i=1}^{n}a_{i}^{2}=\lambda^{2}\sum_{i=1}^{n}x_{i0}^{2}=\lambda^{2}\sigma^{2} \nonumber \sum_{i=1}^{n}a_{i}x_{i0}=\lambda \sum_{i=1}^{n}x_{i0}^{2}=\lambda\sigma^{2}=(\lambda\sigma)\sigma = \pm\left(\sum_{i=1}^{n}a_{i}^{2}\right)^{1/2} \left(\sum_{i=1}^{n}x_{i0}^{2}\right)^{1/2} \nonumber

For every \sigma>0, f({\bf X})= x_{m})=x_{1}^{r_{1}}x_{2}^{r_{2}}\cdots x_{m}^{r_{m}} assumes a maximum value on the closed set S_{\sigma}=\left\{(x_{1},x_{2}, \dots, x_{m})\, \big|\, x_{i}>0, \,1 \le i \le m,\, r_{1}x_{1}+r_{2}x_{2}+\cdots+ r_{m}x_{m}=\sigma\right\}. \nonumber L=x_{1}^{r_{1}}x_{2}^{r_{2}}\cdots x_{m}^{r_{m}} -\lambda\sum_{i=1}^{m}r_{i}x_{i},\quad L_{x_{i}}=r_{i}\left(\frac{x_{1}^{r_{1}}x_{2}^{r_{2}}\cdots x_{m}^{r_{m}}}{x_{i}}-\lambda\right), \quad 1 \le i \le m. \nonumber Therefore, the constrained extremum is attained at x_{1}=x_{2}=\cdots =x_{m}=\sigma/r, and the value of the constrained extremum is (\sigma/r)^{r}, so \left(x_{1}^{r_{1}}x_{2}^{r_{2}}\cdots x_{m}^{r_{m}}\right)^{1/r} \le \frac{\sigma}{r}=\frac{r_{1}{x_{1}+r_{2}x_{2}+\cdots+r_{k}x_{k}}}{r} \nonumber with equality if and only if x_{1}=x_{2}=\cdots= x_{m}=\sigma/r.

The statement is trivial if \sigma_{i}=0 for some i. If \sigma_{i}\ne0, 1 \le i \le m, then Exercise [exer:53] with r_{i}=\displaystyle{\frac{1}{p_{i}}} and x_{i}=\displaystyle{\frac{|a_{ij}|^{p_{i}}}{\sigma_{i}}} implies that \frac{|a_{1j}||a_{2j}|\cdots|a_{mj}|} {\sigma_{1}^{1/p_{1}}\sigma_{2}^{1/p_{2}}\cdots\sigma_{m}^{1/p_{m}}} \le \sum_{i=1}^{m} \frac{|a_{ij}|^{p_{i}}}{p_{i}\sigma_{i}}. \nonumber Summing both sides from j=1 to n yields the stated conclusion.

\displaystyle{L =\frac{1}{2}\sum_{r=0}^{n}x_{r}^{2}-\sum_{s=0}^{m} \lambda_{s}\sum_{r=0}^{n}x_{r}r^{s}}, L_{x_{r}}=x_{r}-\displaystyle{\sum_{s=0}^{m}\lambda_{s}r^{s}} x_{r0}=\sum_{s=0}^{m}\lambda_{s}r^{s},\quad 0\le r\le n. \nonumber \sum_{r=0}^{n}x_{r0}r^{s}=\sum_{r=0}^{n}\sum_{\ell=0}^{m}\lambda_{\ell}r^{\ell+s} =\sum_{\ell=0}^{m}\lambda_{\ell}\sum_{r=0}^{n}r^{\ell+s}= \sum_{\ell=0}^{m}\sigma_{s+\ell}\lambda_{\ell}=c_{s}, \quad 0\le s \le m, \nonumber so (x_{10},x_{20},\dots,x_{n0}) is a critical point of L. To see that it is constrained minimum point of Q, suppose that (y_{0},y_{1},\dots,y_{n}) also satisfies the constraints; thus, \sum_{r=0}^{n}y_{r}r^{s}=c_{s},\quad 0\le s \le m. \nonumber Then \sum_{r=0}^{n}(y_{r}-x_{r0})x_{r0}=\sum_{r=0}^{n}(y_{r}-x_{r0}) \sum_{s=0}^{m}\lambda_{s}r^{s}=\sum_{s=0}^{m}\lambda_{s}\sum_{r=0}^{n} (y_{r}-x_{r0})r^{s}=0, \nonumber so \begin{aligned} \sum_{r=0}^{n}y_{r}^{2}&=&\sum_{r=0}^{n}(y_{r}-x_{r0}+x_{r0})^{2} =\sum_{r=0}^{n}[(y_{r}-x_{r0})^{2}+2(y_{r}-x_{r0})x_{r0} +x_{r0}^{2}]\\ &=&\sum_{r=0}^{n}[(y_{r}-x_{r0})^{2} +\sum_{r=0}^{n}x_{r0}^{2}> \sum_{r=0}^{n}x_{r0}^{2}.\end{aligned} \nonumber

Imposing the constraint with r=0 and P(x)=x^{s}, 1\le s\le 2k, yields the necessary condition \tag{A} \sum_{i=-n}^{n}w_{i}i^{s}= \begin{cases} 1& \text{if } s=0,\\ 0&\text{if }1\le s\le 2k. \end{cases} If P is an arbitrary polynomial of degree \le 2k and r is an arbitrary integer, then
P(r-i)=P(r)+ a linear combination of i, i^{2}, …, i^{2k}, so (A) implies that \sum_{i=-n}^{n}w_{i}P(r-i)=P(r) \nonumber whenever r is an integer and P is a polynomial of degree \le 2k. Therefore, L=\frac{1}{2}\sum_{i=-n}^{n}w_{i}^{2}-\sum_{r=0}^{2k}\lambda_{r} \sum_{i=-n}^{n}w_{i}i^{r}, \nonumber L_{w_{i}}=w_{i}-\sum_{r=0}^{2k}\lambda_{r}i^{r},\quad w_{i0}=\sum_{r=0}^{2k}\lambda_{r}i^{r}, \quad -n\le i\le n, \nonumber and \sum_{i=-n}^{n}w_{i0}i^{s}= \sum_{i=-n}^{n} \left(\sum_{r=0}^{2k} \lambda_{r}i^{r}\right)i^{s} =\sum_{r=0}^{2k}\lambda_{r}\sigma_{r+s}\text{\; where\;\;} \sigma_{m}=\sum_{i=-n}^{n}i^{m}. \nonumber

If \{w_{i}\}_{i=-n}^{n} also satisfies the constraint, then \sum_{i=-n}^{n}(w_{i}-w_{i0})w_{i0}= \sum_{i=-n}^{n}(w_{i}-w_{i0})\sum_{r=0}^{2k}\lambda_{r}i^{r}=0. \nonumber Therefore, \begin{aligned} \sum_{i=-n}^{n}w_{i}^{2}&=&\sum_{i=-n}^{n}(w_{i0}+w_{i}-w_{i0})^{2}= \sum_{i=-n}^{n}\left(w_{i0}^{2}+2(w_{i}-w_{i0})w_{i0}+(w_{i}-w_{i0})^{2}\right)\\ &=&\sum_{i=-n}^{n}w_{i0}^{2}+\sum_{i=-n}^{n}(w_{i}-w_{i0})^{2} >\sum_{i=-n}^{n}w_{i0}^{2}\end{aligned} \nonumber if w_{i}\ne w_{i0} for some i.

The coefficients w_{0}, w_{1}, …, w_{k} satisfy the constraint if and only if \sum_{i=0}^{n}w_{i}(r-i)^{j}=(r+1)^{j},\quad 0\le j\le k, \nonumber for all integers r. This is equivalent to \sum_{i=0}^{n}w_{i}\sum_{s=0}^{j}(-1)^{s} \binom{j}{s}s^{j}r^{j-s} =\sum_{s=0}^{j}\binom{j}{s}r^{j-s},\quad 0\le j\le k, \nonumber which is equivalent to \tag{A} \sum_{i=0}^{n}w_{i}i^{s}=(-1)^{s},\quad 0\le s\le k. L=\frac{1}{2}\sum_{i=0}^{k}w_{i}^{2}-\sum_{r=0}^{k}\lambda_{r} \sum_{i=0}^{k}w_{i}i^{r};\quad L_{x_{i}}=w_{i}-\sum_{r=0}^{k}\lambda_{r} i^{r};\quad w_{i0}=\sum_{r=0}^{k}\lambda_{r}i^{r}. \nonumber Now must choose \lambda_{1}, \lambda_{2}, …, \lambda_{k} to satisfy (A).

\sum_{i=0}^{n}w_{i0}i^{s}\sum_{r=0}^{k}\lambda_{r}i^{r} =\sum_{r=0}^{k}\lambda_{r}\sum_{i=0}^{n}i^{r+s} = \sum_{r=0}^{k}\sigma_{r+s}\lambda_{r}=(-1)^{s}, \quad 0\le s\le k. \nonumber

If \{w_{i}\}_{i=0}^{n} also satisfies the constraint, then \sum_{i=0}^{n}(w_{i}-w_{i0})w_{i0}= \sum_{i=n}^{n}(w_{i}-w_{i0})\sum_{r=0}^{2k}\lambda_{r}i^{r}=0. \nonumber Therefore, \begin{aligned} \sum_{i=0}^{n}w_{i}^{2}&=&\sum_{i=0}^{n}(w_{i0}+w_{i}-w_{i0})^{2}= \sum_{i=0}^{n}\left(w_{i0}^{2}+2(w_{i}-w_{i0})w_{i0}+(w_{i}-w_{i0})^{2}\right)\\ &=&\sum_{i=0}^{n}w_{i0}^{2}+\sum_{i=-n}^{n}(w_{i}-w_{i0})^{2} >\sum_{i=0}^{n}w_{i0}^{2}\end{aligned} \nonumber if w_{i}\ne w_{i0} for some i.

L=\displaystyle{\frac{1}{2}\sum_{i=1}^{n}\frac{(x_{i}-c_{i})^{2}}{\alpha_{i}} -\sum_{s=1}^{m}\lambda_{s}\sum_{i=1}^{n}a_{is}x_{i}}

L_{x_{i}}=\frac{x_{i}-c_{i}}{\alpha_{i}}, \quad x_{i0}=c_{i}+\alpha_{i}\displaystyle{\sum_{s=1}^{m}\lambda_{s}a_{is}} \nonumber

\displaystyle{\sum_{i=1}^{n}a_{ir}x_{i0}}=\displaystyle{\sum_{i=1}^{n}a_{ir}c_{i}+ \sum_{s=1}^{m}\lambda_{s}\sum_{i=1}^{n}\alpha_{i}a_{ir}a_{is} = \sum_{i=1}^{n}a_{ir}c_{i}+\lambda_{r} =d_{r}} \nonumber

\lambda_{r}=d_{r}-\displaystyle{\sum_{i=1}^{n}a_{ir} c_{i}},\quad \displaystyle{\frac{(x_{i}-c_{i})^{2}}{\alpha_{i}}=\alpha_{i}\sum_{r,s=1}^{m} \lambda_{r}\lambda_{s}a_{ir}a_{is}} \nonumber

\sum_{i=1}^{n}\frac{(x_{i}-c_{i})^{2}}{\alpha_{i}}=\sum_{r,s=1}^{m} \lambda_{r}\lambda_{s}\sum_{i=1}^{n}\alpha_{i}a_{ir}a_{is} =\sum_{r=1}^{m}\lambda_{r}^{2} =\sum_{r=1}^{m} \left(d_{r}-\sum_{i=1}^{n}a_{ir}c_{i}\right)^{2} \nonumber


This page titled 6: Exercises is shared under a CC BY-NC-SA 3.0 license and was authored, remixed, and/or curated by William F. Trench.

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