Su sistema
$$\left\{ \begin{array}{c} \frac{1}{300}a-\frac{1}{200}b=5 \\ -\frac{1}{300}a+\left( -\frac{1}{300}+\frac{1}{200}\right) b-\frac{1}{200} c=-e^{b} \\ -\frac{1}{200}b+\frac{1}{200}c=-e^{c}\tag{1} \end{array} \right. $$
equivale a
$$\left\{ \begin{array}{c} 2a-3b=3000 \\ -2a+b-3c=-600e^{b} \\ -b+c=-200e^{c}\tag{2} \end{array} \right. $$
y a
$$\left\{ \begin{array}{c} a=\frac{3}{2}\left( c+200e^{c}\right) +1500 \\ -5c-400e^{c}-3000+600\text{ exp}(c+200e^{c})=0 \\ \tag{3} b=c+200e^{c}. \end{array} \right. $$
La segunda ecuación tiene dos soluciones ( cálculo en WolframAlpha ): $c\approx -600.000$ y $c\approx -3.64058$ .
El método de Newton aplicado a $$f(c)=-5c-400e^{c}-3000+600\text{ exp}(c+200e^{c})\tag{4}$$
consiste en las siguientes iteraciones
$$c_{k+1}=c_{k}-\frac{f(c_{k})}{f^{\prime }(c_{k})},\qquad k=1,2,\dots\tag{5}$$
con
$$f'(c)=-5-400e^{c}+600\left( 1+200e^{c}\right) \text{ exp}(c+200e^{c})\tag{6}$$
Empezando por, por ejemplo $c_{1}=-500$ obtenemos $$ \begin{eqnarray*} f(c_{1}) &=&-5c_{1}-400e^{c_{1}}-3000+600\text{ exp}(c_{1}+200e^{c_{1}}) \\ f(-500) &=&5\times 500-400e^{-500}-3000+600\text{ exp}(-500+200e^{-500}) \\ &\approx &-500.0 \end{eqnarray*}$$
y $$ \begin{eqnarray*} f^{\prime }(c_{1}) &=&-5-400e^{c_{1}}+600\left( 1+200e^{c_{1}}\right) \text{ exp}(c_{1}+200e^{c_{1}}) \\ f^{\prime }(-500) &=&-5-400e^{-500}+600\left( 1+200e^{-500}\right) \text{ exp}(-500+200e^{-500}) \\ &\approx &-5.0. \end{eqnarray*}$$
Y así, $$ c_{2}=c_{1}-\frac{f(c_{1})}{f^{\prime }(c_{1})}\approx -500-\frac{-500.0}{ -5.0}\approx -600.0, $$
que ya es una buena aproximación.
Para $c_{1}=-3.6$ obtenemos sucesivamente $$\begin{eqnarray*} c_{2} &\approx &-3.6-\frac{879.64}{25019.0}\approx -3.6352 \\ c_{3} &\approx &-3.6352-\frac{71.578}{19406.}\approx -3.6389 \\ c_{4} &\approx &-3.6389-\frac{1.\,417\,3}{18902.}\approx -3.6390 \\ c_{5} &\approx &-3.6390-\frac{29.\,615}{18889.}\approx -3.6406 \\ c_{6} &\approx &-3.6406-\frac{-0.435\,93}{18676}\approx -3.6406. \end{eqnarray*}$$
Desde $(3)$ para $c\approx -3.6406$ obtenemos la solución $(a,b,c)\approx (1502.4,1.6067,-3.6406)$ y para $c\approx -600.0$ la solución $(a,b,c)\approx (600.0,-600.0,-600.0)$ .
Parcela de $f(c)$ para $c=-700$ a $c=-3.62$
Parcela de $f(c)$ para $c=-3.7$ a $c=-3.6$
Añadido : Quizás tengas en mente el método general para resolver un sistema no lineal sistema no lineal, aplicado al caso que nos ocupa. Denotemos $x_{1}=a,x_{2}=b,x_{3}=c$ . El sistema
$$ \begin{pmatrix} f_{1}(x_{1},x_{2},x_{3}) \\ f_{2}(x_{1},x_{2},x_{3}) \\ f_{3}(x_{1},x_{2},x_{3}) \end{pmatrix} = \begin{pmatrix} 0 \\ 0 \\ 0 \end{pmatrix},\tag{7}$$
donde
$$ \begin{pmatrix} f_{1}(x_{1},x_{2},x_{3}) \\ f_{2}(x_{1},x_{2},x_{3}) \\ f_{3}(x_{1},x_{2},x_{3}) \end{pmatrix} = \begin{pmatrix} \frac{1}{300}x_{1}-\frac{1}{200}x_{2}-5 \\ -\frac{1}{300}x_{1}+\left( -\frac{1}{300}+\frac{1}{200}\right) x_{2}-\frac{1 }{200}x_{3}+e^{x_{2}} \\ -\frac{1}{200}x_{2}+\frac{1}{200}x_{3}+e^{x_{3}} \end{pmatrix},\tag{8}$$
tiene la matriz jacobiana
$$\begin{eqnarray*} J\left( x\right) &=& \begin{pmatrix} \frac{\partial f_{1}(x_{1},x_{2},x_{3})}{\partial x_{1}} & \frac{\partial f_{1}(x_{1},x_{2},x_{3})}{\partial x_{2}} & \frac{\partial f_{1}(x_{1},x_{2},x_{3})}{\partial x_{3}} \\ \frac{\partial f_{2}(x_{1},x_{2},x_{3})}{\partial x_{1}} & \frac{\partial f_{2}(x_{1},x_{2},x_{3})}{\partial x_{2}} & \frac{\partial f_{2}(x_{1},x_{2},x_{3})}{\partial x_{3}} \\ \frac{\partial f_{3}(x_{1},x_{2},x_{3})}{\partial x_{1}} & \frac{\partial f_{3}(x_{1},x_{2},x_{3})}{\partial x_{2}} & \frac{\partial f_{3}(x_{1},x_{2},x_{3})}{\partial x_{3}} \end{pmatrix} \\ &=& \begin{pmatrix} \frac{1}{300} & -\frac{1}{200} & 0 \\ -\frac{1}{300} & \frac{1}{600}+e^{x_{2}} & -\frac{1}{200} \\ 0 & -\frac{1}{200} & \frac{1}{200}+e^{x_{3}} \end{pmatrix} . \end{eqnarray*}\tag{9} $$
El método de Newton consiste en partir de una aproximación $x^{(1)}$ y encuentran sucesivamente
$$x^{(k+1)}=x^{(k)}+\Delta x^{(k)},\qquad k=1,2,\dots\tag{10}$$
donde $\Delta x^{(k)}$ es una solución de
$$J\left( x^{(k)}\right) \Delta x^{(k)}=-f\left( x^{(k)}\right) ,\tag{11}$$
que se puede encontrar por eliminación gaussiana.
Notación : $x^{(k)}$ es el vector $\left( x_{1}^{(k)},x_{2}^{(k)},x_{3}^{(k)}\right) ^{T}$ , $x^{(k+1)}$ es el vector $% \left( x_{1}^{(k+1)},x_{2}^{(k+1)},x_{3}^{(k+1)}\right) ^{T}$ , $J\left( x^{(k)}\right) $ es la matriz jacobiana evaluada en $\left( x_{1}^{(k)},x_{2}^{(k)},x_{3}^{(k)}\right) $ y $f\left( x^{(k)}\right)$ es la columna del vector $(8)$ de $f$ evaluado en $\left( x_{1}^{(k)},x_{2}^{(k)},x_{3}^{(k)}\right) $ .