"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Una cadena de Markov es un proceso estocástico que experimenta transiciones de un estado a otro en un espacio de estados. Tiene la propiedad de que el estado futuro sólo depende del estado actual y no de la secuencia de acontecimientos que lo precedieron (propiedad de no memoria). La simulación de Montecarlo es un método que utiliza el muestreo aleatorio para aproximar la distribución de probabilidad de una cantidad desconocida. En el contexto de las cadenas de Markov, podemos utilizar simulaciones de Montecarlo para estimar el comportamiento a largo plazo de la cadena.\n",
"\n",
"En este tutorial se desarrollarán dos maneras diferentes de obtener medidas de interés de un sistema. La primera consiste en calcular valores esperados a partir de las probabilidades obtenidas de una Cadena de Markov, y la segunda consiste en realizar una simulación de Montecarlo para generar diferentes escenarios que permitan estimar los valores esperados.\n",
"\n",
"Una simulación de Montecarlo es una técnica que permite calcular medidas de desempeño de un sistema que no es determinístico. Esto se hace mediante la creación de diferentes escenarios (o réplicas) a partir de un muestreo de los componentes aleatorios del sistema. Para realizar este muestreo, utilizamos las distribuciones de probabilidad de los componentes aleatorios. Una vez generados los diferentes escenarios se pueden, por ejemplo, utilizar los resultados de cada escenario para estimar la distribución de alguna medida de desempeño o promediar los resultados para estimar el valor esperado de una medida de desempeño.\n",
"\n",
"La validez de los métodos de Montecarlo se basa en la Ley de los Grandes Números y en el Teorema del Límite Central. La ley de los grandes números establece que, a medida que aumenta el número de muestras, la media muestral converge hacia la media real de la población. El teorema del límite central afirma que la distribución de la media muestral se aproxima a una distribución normal a medida que aumenta el tamaño de la muestra, independientemente de la distribución de la población. Estos teoremas garantizan que las estimaciones de Montecarlo sean más precisas a medida que aumenta el número de muestras. Sin embargo, es importante tener en cuenta que la convergencia puede ser lenta para algunos problemas, requiriendo un gran número de muestras para alcanzar el nivel de precisión deseado.\n",
"\n",
"Tomemos por ejemplo el siguiente proceso estocástico modelado como una CMTD:\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"$$\n",
"X_n = \\text{Calidad del aire al finalizar el n-ésimo día}\n",
"$$\n",
"\n",
"$$\n",
"S_X = \\text{\\{1 (Mala), 2 (Regular), 3 (Buena)\\}}\n",
"$$\n",
"\n",
"$$\n",
"\\begin{bmatrix}\n",
"0.5 & 0.3 & 0.2 \\\\\n",
"0.3 & 0.4 & 0.3 \\\\\n",
"0.2 & 0.3 & 0.5\n",
"\\end{bmatrix}\n",
"$$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Para crear la matriz en Python usamos el siguiente código:"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
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"execution_count": 1,
"metadata": {},
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],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"\n",
"# Definir la matriz con probabilidades de transición a un paso (P)\n",
"estados = [1, 2, 3]\n",
"\n",
"P = np.array([[0.5, 0.3, 0.2],\n",
" [0.3, 0.4, 0.3],\n",
" [0.2, 0.3, 0.5]])\n",
"\n",
"# Crear un DataFrame para asignar nombres a las filas y columnas\n",
"P = pd.DataFrame(P, index=estados, columns=estados)\n",
"\n",
"P\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Hasta este momento del curso, si se desea calcular el valor esperado de la calidad del aire o el valor esperado de algún costo asociado, se ha hecho uso de las probabilidades a un paso, varios pasos o en estado estable de la cadena de Markov. Sin embargo, también es posible realizar simulaciones de este proceso estocástico para estimar estas medidas. Asumamos que al final del día de hoy la calidad de aire es Mala (1). Siendo así, se sabe que las probabilidades de transición de la calidad del aire para el día siguiente son:\n",
"$$\n",
"P[X_{n+1}|X_{n}=1]= \\begin{bmatrix}\n",
"0.5 & 0.3 & 0.2 \\\\\n",
"\\end{bmatrix}\n",
"$$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Para hacer esto en Python, accedemos a la fila de la matriz $P$ que hace referencia al estado inicial (1)."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1 0.5\n",
"2 0.3\n",
"3 0.2\n",
"Name: 1, dtype: float64"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Estado actual\n",
"estado = 1\n",
"# Definir la distribución de probabilidad de la calidad de aire para el día siguiente, dado el estado actual\n",
"P.loc[estado,]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Si deseamos simular la calidad del aire para el día de mañana, podemos generar una muestra aleatoria del estado futuro con estas probabilidades, de modo que, dado que actualmente estamos en el estado 1, con probabilidad de 0.5 se pase al estado 1, con probabilidad de 0.3 se pase al estado 2 y con probabilidad de 0.2 se pase al estado 3. Para esto, utilizamos la función `np,random.choice()`."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.random.choice(estados, p=P[estado])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Esta función genera una muestra aleatoria del vector `estados` a partir de las probabilidades dadas por el parámetro `p`. Debido a que esta función realiza un muestreo aleatorio, cada vez que se ejecute esta función podemos obtener un resultado diferente.\n",
"\n",
"Habiendo entendido cómo podemos muestrear el estado futuro a partir de las probabilidades de transición, ahora realizaremos varios muestreos para simular varios días de evolución de la calidad del aire. Debido a que la evolución depende de los muestreos aleatorios, utilizaremos una semilla para que la generación de números aleatorios sea igual cada vez que se ejecuta el código y los resultados sean reproducibles."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"# Días de evolución\n",
"dias = 10\n",
"\n",
"# Fijar la semilla para números aleatorios\n",
"np.random.seed(0)\n",
"\n",
"# Definir el estado inicial\n",
"estado = 1\n",
"\n",
"# Inicializar lista que contiene la calidad del aire en cada día\n",
"lista_estados = []\n",
"\n",
"# Simular 10 días de evolución de la calidad del aire\n",
"for i in range(1, dias+1):\n",
" # Guardar estado actual en la lista de estados\n",
" lista_estados.append(estado)\n",
" \n",
" # Obtener estado futuro\n",
" estado = np.random.choice(estados, p=P[estado])\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Podemos utilizar los diferentes estados por los que pasó la cadena (almacenados en `lista_estados`) para graficar la evolución de la calidad del aire durante los 10 días."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0, 0.5, 'Calidad del aire')"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"\n",
"plt.plot(lista_estados,'o')\n",
"plt.title(\"Evolución de la calidad del aire\")\n",
"plt.xlabel(\"Día\")\n",
"plt.ylabel(\"Calidad del aire\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"En la gráfica de arriba podemos observar un posible escenario de la evolución de la calidad del aire. Sin embargo, si nos interesa calcular medidas sobre este sistema, necesitaremos de una muestra más grande. Ahora haremos la simulación con 8 escenarios, u 8 evoluciones diferentes de la CMTD. Los resultados de cada escenario los iremos guardando en una matriz para graficarlos más adelante."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"# Días de evolución\n",
"dias = 10\n",
"\n",
"# Cantidad de escenarios\n",
"escenarios = 8\n",
"\n",
"# Fijar semilla para números aleatorios\n",
"np.random.seed(0)\n",
"\n",
"# Inicializar matriz para almacenar la simulación de la calidad del aire para cada escenario\n",
"matriz_calidad = np.zeros((dias, escenarios), dtype=float)\n",
"\n",
"for j in range(1, escenarios+1):\n",
" # Definir el estado inicial\n",
" estado = 1\n",
" \n",
" # Simular 10 días de evolución de la calidad del aire\n",
" for i in range(1, dias+1):\n",
" # Guardar estado actual en la lista de estados\n",
" matriz_calidad[i-1, j-1] = estado\n",
" \n",
" # Obtener estado futuro\n",
" estado = np.random.choice(estados, p=P[estado])\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Ahora, graficaremos la evolución de la calidad del aire para cada escenario."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\cante\\AppData\\Local\\Temp\\ipykernel_21044\\1316832013.py:11: UserWarning: No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n",
" plt.legend()\n"
]
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Graficar cada serie (columna de la matriz)\n",
"for i in range(matriz_calidad.shape[1]): # Iterar sobre las columnas\n",
" plt.plot(matriz_calidad[:, i]) # Graficar la i-ésima columna\n",
"\n",
"# Agregar títulos y etiquetas\n",
"plt.title(\"Evolución de la calidad del aire para varios escenarios\")\n",
"plt.xlabel(\"Día\")\n",
"plt.ylabel(\"Calidad del aire\")\n",
"\n",
"# Agregar leyenda\n",
"plt.legend()\n",
"\n",
"# Mostrar el gráfico\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Con esto en mente, ahora se resolverá el problema del archivo “Complementaria 11 (Q).pdf” que se encuentra en Bloque Neón."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"
Literal A: Modelación\n",
"
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"En primer lugar, se modelará la situación como una cadena de Markov de tiempo discreto. Se define la variable de estado:\n",
"\n",
"$$\n",
"X_{n} = \\text{Inventario de cajas de medicamento al finalizar la n-ésima semana}\\\\\n",
"S_{X} = \\{0,1,...,100\\}\n",
"$$\n",
"\n",
"Sabemos que la demanda semanal sigue un proceso de Poisson con tasa $\\lambda = 15 \\text{ semanas}^{-1}$\n",
"\n",
"$$\n",
"P[D=x] = \\frac{e^{-\\lambda} \\cdot \\lambda^{x}}{x!}\\\\\n",
"$$\n",
"\n",
"$$\n",
"P[D \\geq x]=\\sum_{i=x}^{\\infty}{\\frac{e^{-\\lambda}\\cdot \\lambda^{i}}{i!}}\n",
"$$\n",
"\n",
"Las probabilidades de transición de un paso entre estados de esta CMTD son las siguientes:\n",
"\n",
"$$\n",
"\\mathbb{P}_{i \\rightarrow j} = \\begin{cases}\n",
"P[D=30+i-j] & \\text{si } j > 0, i \\leq 70 \\\\\n",
"P[D \\geq 30+i-j] & \\text{si } j = 0, i \\leq 70 \\\\\n",
"P[D = i-j] & \\text{si } j > 0, i > 70 \\\\\n",
"P[D \\geq i-j] & \\text{si } j = 0, i > 70 \\\\\n",
"0 & \\text{d.l.c}\n",
"\\end{cases}\n",
"$$\n",
"\n",
"Se implementa en Python la formulación general y se crea la cadena de Markov."
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"from scipy.stats import poisson\n",
"from jmarkov.dtmc import dtmc\n",
"\n",
"#Tasa de la demanda\n",
"tasa_demanda = 15\n",
"\n",
"#Modelación del manejo de inventarios de Wattenspharma con cadenas de Markov\n",
"#Crear los estados\n",
"estados = range(0,101)\n",
"\n",
"#*****Crear y llenar la matriz P de la política*****\n",
"matrizP = np.zeros((len(estados), len(estados)), dtype=float)\n",
"\n",
"#Para la Politica -> si i<=70 solicita 30 cajas\n",
"for i in estados:\n",
" for j in estados:\n",
" if i<=70 and j>0:\n",
" matrizP[i,j] = poisson.pmf(30+i-j, tasa_demanda)\n",
" elif i<=70 and j==0:\n",
" matrizP[i,j] = 1 - poisson.cdf(30+i-j-1, tasa_demanda)\n",
" elif i>70 and j>0:\n",
" matrizP[i,j] = poisson.pmf(i-j, tasa_demanda)\n",
" elif i>70 and j==0:\n",
" matrizP[i,j] = 1 - poisson.cdf(i-j-1, tasa_demanda)\n",
"\n",
"# Crear la cadena usando el paquete jmarkov\n",
"cmtd = dtmc(matrizP)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"
Literal B: Cálculo del valor esperado de inventario para cada semana y el costo total de ordenar.\n",
"
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"En el literal b, se pide calcular el valor esperado de inventario para cada semana y el costo total de ordenar. El valor esperado del inventario para cada semana se calcula utilizando las probabilidades en el transitorio para cada una de las siguientes 30 semanas.\n",
"\n",
"$$\n",
"E[\\text{Inventario}]_{n} = \\sum_{i\\in S_{X}}{[\\alpha \\mathbb{P}^{n}]_{i}\\cdot i} ~~~ \\forall n \\in 1,2,...,30\n",
"$$\n",
"\n",
"Implementando esta solución en Python:"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Text(0, 0.5, 'Valor esperado de inventario')"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Vector para guardar el valor esperado del inventario en cada semana\n",
"vEsperadoInv = []\n",
"\n",
"#Creamos el vector de estados iniciales\n",
"alpha = np.zeros(101)\n",
"alpha[0] = 1\n",
"\n",
"# Recorrer las semanas\n",
"for n in range(1,31):\n",
" # Calcular la matriz de probabilidades en el transitorio\n",
" probs = cmtd.transient_probabilities(n, alpha)\n",
" # Calcular valor esperado y agregar al vector\n",
" vEsperadoInv.append(np.dot(probs, estados))\n",
"\n",
"plt.plot(vEsperadoInv)\n",
"plt.title(\"Inventario al final de la semana\")\n",
"plt.xlabel(\"Semana\")\n",
"plt.ylabel(\"Valor esperado de inventario\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Se puede observar que el valor esperado del inventario parece estabilizarse alrededor de 70 desde la semana 5.\n",
"\n",
"Ahora calculamos el valor esperado del costo de ordenar total para las siguientes 30 semanas. Para este caso, se calcula el valor esperado del costo de ordenar para cada semana como la multiplicación entre el costo de ordenar y la probabilidad de ordenar, que consiste en la probabilidad de que el inventario esté entre 0 y 70:\n",
"\n",
"$$\n",
"E[\\text{Costo Ordenar}] = \\sum_{n=1}^{30}{5000} \\cdot \\sum_{i=0}^{70}{[\\alpha \\mathbb{P}^{n}]_{i}}\n",
"$$\n",
"\n",
"Implementamos esta solución de la siguiente forma:"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"84249.96608375743"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Creamos el vector de estados iniciales\n",
"alpha = np.zeros(101)\n",
"alpha[0] = 1\n",
"\n",
"# Calcula el valor esperado del costo de ordenar de las siguientes 30 semanas\n",
"cOrdenar = 5000\n",
"vEsperadoOrd = 0\n",
"\n",
"for n in range(1,31):\n",
" # Calcular probabilidades en el transitorio dado el estado inicial\n",
" probs = cmtd.transient_probabilities(n, alpha)\n",
" \n",
" # Calcular el valor esperado de ordenar y sumarlo al costo hasta el momento\n",
" vEsperadoOrd = vEsperadoOrd + np.sum(probs[0:71])*cOrdenar\n",
"\n",
"vEsperadoOrd"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"
Literal C: Inventario mediante simulación de Montecarlo.\n",
"
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"En este literal, empezaremos por realizar una simulación de Montecarlo para visualizar el nivel de inventario durante las próximas 30 semanas con 8 escenarios. Para esto, utilizaremos la matriz de probabilidades que creamos en el literal a. Para cada escenario, iremos guardando el inventario que se tiene en cada semana para después visualizar los resultados."
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
"escenarios = 8\n",
"semanas = 30\n",
"\n",
"# Inicializar matriz para almacenar la simulación del inventario para cada escenario\n",
"inventario = np.zeros((semanas, escenarios), dtype=float)\n",
"\n",
"# Simular la cadena de Markov\n",
"np.random.seed(0)\n",
"\n",
"for j in range(1, escenarios+1):\n",
" \n",
" # Definir el estado inicial (inventario inicial)\n",
" estado = 0\n",
" \n",
" # Simular las transiciones por 30 semanas\n",
" for i in range(1, semanas+1):\n",
" \n",
" # Guardar el inventario actual\n",
" inventario[i-1,j-1] = estado\n",
" \n",
" # Obtener estado futuro\n",
" estado = np.random.choice(estados, p=matrizP[estado])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Ahora graficaremos la evolución del nivel de inventario para cada escenario."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\cante\\AppData\\Local\\Temp\\ipykernel_21044\\79001961.py:11: UserWarning: No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n",
" plt.legend()\n"
]
},
{
"data": {
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Graficar cada serie (columna de la matriz)\n",
"for i in range(inventario.shape[1]): # Iterar sobre las columnas\n",
" plt.plot(inventario[:, i]) # Graficar la i-ésima columna\n",
"\n",
"# Agregar títulos y etiquetas\n",
"plt.title(\"Evolución de inventario\")\n",
"plt.xlabel(\"Semana\")\n",
"plt.ylabel(\"Inventario\")\n",
"\n",
"# Agregar leyenda\n",
"plt.legend()\n",
"\n",
"# Mostrar el gráfico\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Podemos observar que el inventario parece estabilizarse y oscila alrededor de las 70 cajas de medicamento, consistente con lo encontrado en el literal b."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"
Literal D: Inventario al final de la semana 30 mediante simulación de Montecarlo.\n",
"
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Ahora vamos a repetir la simulación pero utilizando 1000 escenarios."
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"escenarios = 1000\n",
"semanas = 30\n",
"\n",
"# Inicializar matriz para almacenar la simulación del inventario para cada escenario\n",
"inventario = np.zeros((semanas, escenarios), dtype=float)\n",
"\n",
"# Simular la cadena de Markov\n",
"np.random.seed(0)\n",
"\n",
"for j in range(1, escenarios+1):\n",
" \n",
" # Definir el estado inicial (inventario inicial)\n",
" estado = 0\n",
" \n",
" # Simular las transiciones por 30 semanas\n",
" for i in range(1, semanas+1):\n",
" \n",
" # Guardar el inventario actual\n",
" inventario[i-1,j-1] = estado\n",
" \n",
" # Obtener estado futuro\n",
" estado = np.random.choice(estados, p=matrizP[estado])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Con los resultados de esta simulación, vamos a graficar un histograma que permita visualizar la distribución del inventario al final de la semana 30. Para esto, elegimos unicamente la fila 30 de nuestra matriz inventario para solo incluir el inventario en la semana 30."
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.hist(inventario[-1, :], edgecolor='black') # [-1, :] selecciona la última fila\n",
"plt.title(\"Distribución de inventario en la semana 30\")\n",
"plt.xlabel(\"Inventario\")\n",
"plt.ylabel(\"Frecuencia\")\n",
"\n",
"# Mostrar el gráfico\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Ahora, vamos a estimar el valor esperado del inventario al final de la semana 30 utilizando el inventario promedio de nuestros escenarios en la semana 30."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Inventario promedio utilizando simulación de Montecarlo: 70.382\n"
]
}
],
"source": [
"# Calcular inventario promedio\n",
"inventario_promedio = np.mean(inventario[-1, :])\n",
"\n",
"print(\"Inventario promedio utilizando simulación de Montecarlo: \", inventario_promedio)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Valor esperado del inventario (literal b): 70.499\n"
]
}
],
"source": [
"print(\"Valor esperado del inventario (literal b): \", round(vEsperadoInv[29],3))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Nótese que el resultado obtenido con la simulación de Montecarlo es muy cercano al obtenido en el literal b. Entre más escenarios se tengan en la simulación, más cercano estará este valor al valor esperado obtenido en el literal b."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"
Literal E: Costo total de ordenar con simulación de Montecarlo.\n",
"
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Para este literal, modificaremos el código desarrollado en el literal D para incluir el costo de ordenar bajo cada escenario. Como se mencionó anteriormente, Wattenspharma ordena cajas de medicamento cuando se tienen 70 o menos unidades en inventario. Por lo tanto, para cada escenario, se evaluará si hay 70 o menos unidades en inventario, y en caso de que sí, se sumaran los $5,000 que cuesta ordenar al costo total."
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [],
"source": [
"escenarios = 1000\n",
"semanas = 30\n",
"\n",
"# Inicializar vector para guardar los costos de ordenar de cada escenario\n",
"vector_costos = []\n",
"\n",
"# Simular la cadena de Markov\n",
"np.random.seed(0)\n",
"\n",
"for j in range(1, escenarios+1):\n",
" \n",
" # Definir el estado inicial (inventario inicial)\n",
" estado = 0\n",
" # Inicializar costo de ordenar\n",
" costo = 0\n",
" \n",
" # Simular las transiciones por 30 semanas\n",
" for i in range(1, semanas+1):\n",
" \n",
" estado = np.random.choice(estados, p=matrizP[estado])\n",
"\n",
" # Si el inventario es menor a 70, sumar costo de ordenar\n",
" if estado<=70:\n",
" costo = costo + cOrdenar\n",
" \n",
" \n",
" # Guardar el costo de ordenar\n",
" vector_costos.append(costo)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Ahora calculamos el costo total de ordenar promedio de los 1000 escenarios generados."
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Costo total de ordenar promedio utilizando simulación de Montecarlo: $ 84390.0\n"
]
}
],
"source": [
"# Calcular inventario promedio\n",
"costo_promedio = np.mean(vector_costos)\n",
"\n",
"print(\"Costo total de ordenar promedio utilizando simulación de Montecarlo: $\", costo_promedio)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Valor esperado del costo total de ordenar: $ 84249.966\n"
]
}
],
"source": [
"print(\"Valor esperado del costo total de ordenar: $\", round(vEsperadoOrd,3))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Al igual que con el inventario promedio, el costo promedio obtenido con la simulación de Montecarlo aproxima el valor esperado obtenido en el literal b."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Universidad de los Andes | Vigilada Mineducación. Reconocimiento como Universidad: Decreto 1297 del 30 de mayo de 1964. Reconocimiento personería jurídica: Resolución 28 del 23 de febrero de 1949 Minjusticia. Departamento de Ingeniería Industrial Carrera 1 Este No. 19 A 40 Bogotá, Colombia Tel. (57.1) 3324320 | (57.1) 3394949 Ext. 2880 /2881 http://industrial.uniandes.edu.co"
]
}
],
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