{ "cells": [ { "cell_type": "code", "id": "e19ec4ae5347c678", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:17.258978Z", "start_time": "2024-09-08T08:14:16.937551Z" } }, "source": [ "import numpy as np\n", "import pandas as pd\n", "\n", "pd.options.display.max_columns = 100" ], "outputs": [], "execution_count": 1 }, { "cell_type": "code", "id": "initial_id", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:17.666091Z", "start_time": "2024-09-08T08:14:17.259867Z" } }, "source": [ "\n", "df_crop_details = pd.read_excel('./data/2.xlsx', sheet_name=1)" ], "outputs": [], "execution_count": 2 }, { "cell_type": "code", "id": "1d2a51b3414be94", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:17.681548Z", "start_time": "2024-09-08T08:14:17.668092Z" } }, "source": [ "# 去除空格\n", "df_crop_details['cropName'] = df_crop_details['cropName'].apply(lambda x: x.strip())\n" ], "outputs": [], "execution_count": 3 }, { "cell_type": "code", "id": "514cd9136d9ca341", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:17.712692Z", "start_time": "2024-09-08T08:14:17.682481Z" } }, "source": [ "df_crop_planting = pd.read_excel('./data/2.xlsx', sheet_name=0)\n", "# 照例去除一下空格\n", "df_crop_planting['cropName'] = df_crop_planting['cropName'].apply(lambda x: x.strip())\n", "# ffill\n", "df_crop_planting['landName'] = df_crop_planting['landName'].ffill()" ], "outputs": [], "execution_count": 4 }, { "cell_type": "code", "id": "1503f8b642c842db", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:17.743562Z", "start_time": "2024-09-08T08:14:17.714837Z" } }, "source": [ "df_land = pd.read_excel('./data/1.xlsx', sheet_name=0)\n", "# 去除landType和landName的空格\n", "df_land['landType'] = df_land['landType'].apply(lambda x: x.strip())\n", "df_land['landName'] = df_land['landName'].apply(lambda x: x.strip())" ], "outputs": [], "execution_count": 5 }, { "cell_type": "code", "id": "3cdf51a9a9d4d30f", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:17.759420Z", "start_time": "2024-09-08T08:14:17.744880Z" } }, "source": [ "# 计算利润\n", "unit_profit_lsc = []\n", "for line in df_crop_details.values:\n", " s = str(line[7]).split('-')\n", " unit_profit_lsc.append((float(s[0]) + float(s[1])) / 2 * line[5] - line[6])\n", "df_crop_details['unitProfit'] = unit_profit_lsc" ], "outputs": [], "execution_count": 6 }, { "cell_type": "code", "id": "569016a9b90f841b", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:17.790551Z", "start_time": "2024-09-08T08:14:17.760229Z" } }, "source": [ "df_crop_type_land = pd.read_excel('./data/1.xlsx', sheet_name=1)\n", "# 老规矩，去掉cropName和cropType的空格\n", "df_crop_type_land['cropType'] = df_crop_type_land['cropType'].apply(lambda x: x.strip())\n", "df_crop_type_land['cropName'] = df_crop_type_land['cropName'].apply(lambda x: x.strip())" ], "outputs": [], "execution_count": 7 }, { "cell_type": "code", "id": "a7661d84217b578c", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:17.806633Z", "start_time": "2024-09-08T08:14:17.791553Z" } }, "source": [ "# 搞一下季节和年份的集合\n", "SeasonType = [\"单季\", \"第一季\", \"第二季\"]\n", "SeasonDict = {\"单季\": 1, \"第一季\": 1, \"第二季\": 2}\n", "SeasonNum = [1, 2]\n", "years = [2024, 2025, 2026, 2027, 2028, 2029, 2030]" ], "outputs": [], "execution_count": 8 }, { "cell_type": "code", "id": "4a4e06a1f2d4d8ab", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:17.822646Z", "start_time": "2024-09-08T08:14:17.807607Z" } }, "source": [ "# 枚举地块类型\n", "LandType = {\"A\": \"平旱地\", \"B\": \"梯田\", \"C\": \"山坡地\", \"D\": \"水浇地\", \"E\": \"普通大棚\", \"F\": \"智慧大棚\"}" ], "outputs": [], "execution_count": 9 }, { "cell_type": "code", "id": "cc938565a63a8129", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:17.838210Z", "start_time": "2024-09-08T08:14:17.823659Z" } }, "source": [ "# 枚举地块\n", "LandName = df_crop_planting['landName'].unique()" ], "outputs": [], "execution_count": 10 }, { "cell_type": "code", "id": "dae53a6215cea525", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:17.853788Z", "start_time": "2024-09-08T08:14:17.839182Z" } }, "source": [ "# 枚举地块面积，取df_land的landName为key，landArea为value\n", "LandArea = {x: df_land[df_land['landName'] == x]['landArea'].values[0] for x in LandName}" ], "outputs": [], "execution_count": 11 }, { "cell_type": "code", "id": "7a0e6cc209d93b56", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:17.869293Z", "start_time": "2024-09-08T08:14:17.854772Z" } }, "source": [ "# 读入作物名称\n", "CropName = df_crop_details['cropName'].unique()" ], "outputs": [], "execution_count": 12 }, { "cell_type": "code", "id": "8a280f918bb3139a", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:17.900877Z", "start_time": "2024-09-08T08:14:17.870289Z" } }, "source": [ "# 作物分类\n", "CropType = {x: df_crop_type_land[df_crop_type_land['cropType'] == x]['cropName'].values for x in\n", " df_crop_type_land['cropType'].values}\n", "CropType['粮食（除了水稻）'] = CropType['粮食'][:-1] # 这样不太好，但能用\n", "CropType['豆类'] = np.array(list(CropType['粮食（豆类）']) + list(CropType['蔬菜（豆类）']), dtype=object)\n", "CropType['全粮食'] = np.array(list(CropType['粮食']) + list(CropType['粮食（豆类）']), dtype=object)\n", "CropType['全粮食（除了水稻）'] = np.array(list(CropType['粮食'][:-1]) + list(CropType['粮食（豆类）']), dtype=object)\n", "CropType['全蔬菜'] = np.array(list(CropType['蔬菜']) + list(CropType['蔬菜（豆类）']), dtype=object)\n", "CropType['特殊蔬菜'] = np.array([\"大白菜\", \"白萝卜\", \"红萝卜\"], dtype=object)\n", "CropType[\"普通蔬菜\"] = np.array([c for c in CropType['全蔬菜'] if c not in CropType['特殊蔬菜']], dtype=object)\n", "CropType" ], "outputs": [ { "data": { "text/plain": [ "{'粮食（豆类）': array(['黄豆', '黑豆', '红豆', '绿豆', '爬豆'], dtype=object),\n", " '粮食': array(['小麦', '玉米', '谷子', '高粱', '黍子', '荞麦', '南瓜', '红薯', '莜麦', '大麦', '水稻'],\n", " dtype=object),\n", " '蔬菜（豆类）': array(['豇豆', '刀豆', '芸豆'], dtype=object),\n", " '蔬菜': array(['土豆', '西红柿', '茄子', '菠菜', '青椒', '菜花', '包菜', '油麦菜', '小青菜', '黄瓜',\n", " '生菜', '辣椒', '空心菜', '黄心菜', '芹菜', '大白菜', '白萝卜', '红萝卜'], dtype=object),\n", " '食用菌': array(['榆黄菇', '香菇', '白灵菇', '羊肚菌'], dtype=object),\n", " '粮食（除了水稻）': array(['小麦', '玉米', '谷子', '高粱', '黍子', '荞麦', '南瓜', '红薯', '莜麦', '大麦'],\n", " dtype=object),\n", " '豆类': array(['黄豆', '黑豆', '红豆', '绿豆', '爬豆', '豇豆', '刀豆', '芸豆'], dtype=object),\n", " '全粮食': array(['小麦', '玉米', '谷子', '高粱', '黍子', '荞麦', '南瓜', '红薯', '莜麦', '大麦', '水稻',\n", " '黄豆', '黑豆', '红豆', '绿豆', '爬豆'], dtype=object),\n", " '全粮食（除了水稻）': array(['小麦', '玉米', '谷子', '高粱', '黍子', '荞麦', '南瓜', '红薯', '莜麦', '大麦', '黄豆',\n", " '黑豆', '红豆', '绿豆', '爬豆'], dtype=object),\n", " '全蔬菜': array(['土豆', '西红柿', '茄子', '菠菜', '青椒', '菜花', '包菜', '油麦菜', '小青菜', '黄瓜',\n", " '生菜', '辣椒', '空心菜', '黄心菜', '芹菜', '大白菜', '白萝卜', '红萝卜', '豇豆', '刀豆',\n", " '芸豆'], dtype=object),\n", " '特殊蔬菜': array(['大白菜', '白萝卜', '红萝卜'], dtype=object),\n", " '普通蔬菜': array(['土豆', '西红柿', '茄子', '菠菜', '青椒', '菜花', '包菜', '油麦菜', '小青菜', '黄瓜',\n", " '生菜', '辣椒', '空心菜', '黄心菜', '芹菜', '豇豆', '刀豆', '芸豆'], dtype=object)}" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "execution_count": 13 }, { "cell_type": "code", "id": "22f9730e3d9c1016", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:18.089134Z", "start_time": "2024-09-08T08:14:17.903431Z" } }, "source": [ "# 亩产量\n", "unit_yield_lsc = {\n", " l: {\n", " 1: {\n", " c: df_crop_details[\n", " (df_crop_details['cropName'] == c) &\n", " (df_crop_details['cropLandType'] == l) &\n", " ((df_crop_details['season'] == \"单季\") |\n", " (df_crop_details['season'] == \"第一季\"))\n", " ]['unitYield'].values[0] if df_crop_details[\n", " (df_crop_details['cropName'] == c) &\n", " (df_crop_details['cropLandType'] == l) &\n", " ((df_crop_details['season'] == \"单季\") |\n", " (df_crop_details['season'] == \"第一季\"))\n", " ]['unitYield'].values.size > 0 else 0\n", " for c in CropName\n", " },\n", " 2: {\n", " c: df_crop_details[\n", " (df_crop_details['cropName'] == c) &\n", " (df_crop_details['cropLandType'] == l) &\n", " (df_crop_details['season'] == \"第二季\")\n", " ]['unitYield'].values[0] if df_crop_details[\n", " (df_crop_details['cropName'] == c) &\n", " (df_crop_details['cropLandType'] == l) &\n", " (df_crop_details['season'] == \"第二季\")][\n", " 'unitYield'].values.size > 0 else 0\n", " for c in CropName\n", " }\n", " }\n", " for l in LandType.values()\n", "}\n" ], "outputs": [], "execution_count": 14 }, { "cell_type": "code", "id": "99dbe4ca6c54db0b", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:18.292866Z", "start_time": "2024-09-08T08:14:18.089960Z" } }, "source": [ "# 亩利润\n", "unit_profit_lsc = {\n", " l: {\n", " 1: {\n", " c: df_crop_details[\n", " (df_crop_details['cropName'] == c) &\n", " (df_crop_details['cropLandType'] == l) &\n", " ((df_crop_details['season'] == \"单季\") |\n", " (df_crop_details['season'] == \"第一季\"))\n", " ]['unitProfit'].values[0] if df_crop_details[\n", " (df_crop_details['cropName'] == c) &\n", " (df_crop_details['cropLandType'] == l) &\n", " ((df_crop_details['season'] == \"单季\") |\n", " (df_crop_details['season'] == \"第一季\"))\n", " ]['unitProfit'].values.size > 0 else 0\n", " for c in CropName\n", " },\n", " 2: {\n", " c: df_crop_details[\n", " (df_crop_details['cropName'] == c) &\n", " (df_crop_details['cropLandType'] == l) &\n", " (df_crop_details['season'] == \"第二季\")\n", " ]['unitProfit'].values[0] if df_crop_details[\n", " (df_crop_details['cropName'] == c) &\n", " (df_crop_details['cropLandType'] == l) &\n", " (df_crop_details['season'] == \"第二季\")\n", " ]['unitProfit'].values.size > 0 else 0\n", " for c in CropName\n", " }\n", " }\n", " for l in LandType.values()\n", "}\n" ], "outputs": [], "execution_count": 15 }, { "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:18.462863Z", "start_time": "2024-09-08T08:14:18.293865Z" } }, "cell_type": "code", "source": [ "# 亩成本\n", "unit_cost_lsc = {\n", " l: {\n", " 1: {\n", " c: df_crop_details[\n", " (df_crop_details['cropName'] == c) &\n", " (df_crop_details['cropLandType'] == l) &\n", " ((df_crop_details['season'] == \"单季\") |\n", " (df_crop_details['season'] == \"第一季\"))\n", " ]['cost'].values[0] if df_crop_details[\n", " (df_crop_details['cropName'] == c) &\n", " (df_crop_details['cropLandType'] == l) &\n", " ((df_crop_details['season'] == \"单季\") |\n", " (df_crop_details['season'] == \"第一季\"))\n", " ]['cost'].values.size > 0 else 0\n", " for c in CropName\n", " },\n", " 2: {\n", " c: df_crop_details[\n", " (df_crop_details['cropName'] == c) &\n", " (df_crop_details['cropLandType'] == l) &\n", " (df_crop_details['season'] == \"第二季\")\n", " ]['cost'].values[0] if df_crop_details[\n", " (df_crop_details['cropName'] == c) &\n", " (df_crop_details['cropLandType'] == l) &\n", " (df_crop_details['season'] == \"第二季\")\n", " ]['cost'].values.size > 0 else 0\n", " for c in CropName\n", " }\n", " }\n", " for l in LandType.values()\n", "}\n" ], "id": "1c8ad73eaea8be7a", "outputs": [], "execution_count": 16 }, { "cell_type": "code", "id": "13f2ccc7aa215d4c", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:18.478343Z", "start_time": "2024-09-08T08:14:18.463669Z" } }, "source": [ "# 每种作物的总需求\n", "crop_demand = {\n", " c: 0\n", " for c in CropName\n", "}\n", "\n", "# 这里需要另一张表\n", "# 代码独立出来移到上面去了\n", "\n", "for line in df_crop_planting.values:\n", " # 面积*该土地类型的亩产量 面积 地块类型字典 地块类型 季节 作物名称\n", " crop_demand[line[2]] += line[4] * unit_yield_lsc[LandType[line[0][0]]][SeasonDict[line[5]]][line[2]]\n" ], "outputs": [], "execution_count": 17 }, { "cell_type": "code", "id": "5d09872708d40da4", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:18.525244Z", "start_time": "2024-09-08T08:14:18.480029Z" } }, "source": [ "# 准备开搞\n", "from pulp import LpMaximize, LpProblem, LpVariable, lpSum, value, PULP_CBC_CMD, LpContinuous, LpBinary\n", "import pulp" ], "outputs": [], "execution_count": 18 }, { "cell_type": "code", "id": "b6eff87c7a762769", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:18.541546Z", "start_time": "2024-09-08T08:14:18.527235Z" } }, "source": [ "model = LpProblem(\"Crop_Planting_Optimization_with_Specific_Rules\", LpMaximize)" ], "outputs": [], "execution_count": 19 }, { "cell_type": "code", "id": "4cb129e20385a7ee", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:18.587814Z", "start_time": "2024-09-08T08:14:18.542556Z" } }, "source": [ "\n", "t = []\n", "for y in years:\n", " for l in LandName:\n", " for s in SeasonNum:\n", " if l[0] in [\"A\", \"B\", \"C\"] and s == 1:\n", " for c in CropType[\"全粮食（除了水稻）\"]:\n", " t.append((c, l, y, s))\n", " if l[0] == \"D\":\n", " if s == 1:\n", " for c in list(CropType[\"普通蔬菜\"]) + [\"水稻\"]:\n", " t.append((c, l, y, s))\n", " if s == 2:\n", " for c in CropType[\"特殊蔬菜\"]:\n", " t.append((c, l, y, s))\n", " if l[0] == \"E\":\n", " if s == 1:\n", " for c in list(CropType[\"普通蔬菜\"]):\n", " t.append((c, l, y, s))\n", " if s == 2:\n", " for c in CropType[\"食用菌\"]:\n", " t.append((c, l, y, s))\n", " if l[0] == \"F\":\n", " for s in SeasonNum:\n", " for c in CropType[\"普通蔬菜\"]:\n", " t.append((c, l, y, s))\n", "\n", "\n", "# X" ], "outputs": [], "execution_count": 20 }, { "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:18.618675Z", "start_time": "2024-09-08T08:14:18.589714Z" } }, "cell_type": "code", "source": [ "# 地块l在y年的s季的种植c的量\n", "X = LpVariable.dicts(\"X\", t,\n", " lowBound=0,\n", " cat=LpContinuous\n", " )" ], "id": "ca23e006a68f2993", "outputs": [], "execution_count": 21 }, { "cell_type": "code", "id": "9dab983ca7b3b607", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:18.649531Z", "start_time": "2024-09-08T08:14:18.619566Z" } }, "source": [ "# 地块l在y年的s季是否种植了c\n", "Y = LpVariable.dicts(\"Y\", t, cat=LpBinary)" ], "outputs": [], "execution_count": 22 }, { "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:18.664701Z", "start_time": "2024-09-08T08:14:18.650399Z" } }, "cell_type": "code", "source": [ "tt = set(t)\n", "\n", "\n", "def is_feasible(c, l, y, s):\n", " return (c, l, y, s) in tt" ], "id": "bf16c7f3ea10152f", "outputs": [], "execution_count": 23 }, { "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:19.068077Z", "start_time": "2024-09-08T08:14:18.665729Z" } }, "cell_type": "code", "source": [ "# 确保与X进行01约束\n", "for c in CropName:\n", " for l in LandName:\n", " for y in years:\n", " for s in SeasonNum:\n", " # if 1:\n", " if is_feasible(c, l, y, s):\n", " # 如果种植了作物，则种植面积大于0\n", " model += X[c, l, y, s] <= 100 * Y[c, l, y, s], f\"PlantingConstraint1_{c}_{l}_{y}_{s}\"\n", " # 如果未种植作物，则种植面积为0\n", " model += X[c, l, y, s] >= 0.001 * Y[c, l, y, s], f\"PlantingConstraint2_{c}_{l}_{y}_{s}\"\n", "\n", "min_area = 0.2\n", "for c in CropName:\n", " for l in LandName:\n", " for y in years:\n", " for s in SeasonNum:\n", " if is_feasible(c, l, y, s): # 最小面积约束和加强版01约束\n", " model += X[c, l, y, s] <= LandArea[l] * Y[c, l, y, s], f\"LandAreaConstraint_{c}_{l}_{y}_{s}\"\n", " model += X[c, l, y, s] >= min_area * (\n", " 1 if Y[c, l, y, s] else 0), f\"MinAreaConstraint_{c}_{l}_{y}_{s}\"" ], "id": "603175d36624172f", "outputs": [], "execution_count": 24 }, { "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:19.177480Z", "start_time": "2024-09-08T08:14:19.069076Z" } }, "cell_type": "code", "source": [ "# 初始化总目标函数的表达式\n", "total_profit = lpSum([]) # 空的lpSum用于初始化\n", "\n", "# 累积每个作物、每个年份的利润和惩罚\n", "for c in CropName:\n", " for y in years:\n", " # 计算利润部分\n", " profit_term = lpSum(\n", " X[c, l, y, s] * unit_profit_lsc[LandType[l[0]]][s][c]\n", " for l in LandName for s in SeasonNum if is_feasible(c, l, y, s)\n", " )\n", "\n", " # 惩罚超过需求的部分：将每个地块、每个季节的单位成本与种植量相乘\n", " penalty_term = lpSum(\n", " X[c, l, y, s] * unit_cost_lsc[LandType[l[0]]][s][c]\n", " for l in LandName for s in SeasonNum if is_feasible(c, l, y, s)\n", " ) - crop_demand[c] * lpSum(\n", " unit_cost_lsc[LandType[l[0]]][s][c]\n", " for l in LandName for s in SeasonNum if is_feasible(c, l, y, s)\n", " )\n", "\n", " # 累积到总目标函数中\n", " total_profit += profit_term - penalty_term\n", "\n", "# 一次性将目标函数添加到模型中\n", "model += total_profit, \"total_profit\"\n" ], "id": "4505b0f2fe6bf93d", "outputs": [], "execution_count": 25 }, { "cell_type": "code", "id": "7e13de7700d38f19", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:19.225057Z", "start_time": "2024-09-08T08:14:19.195511Z" } }, "source": [ "# 条件2： 每年每季每块地的种植面积不能超过该地块的总面积\n", "for l in LandName:\n", " for y in years:\n", " for s in SeasonNum:\n", " model += lpSum(X[c, l, y, s] for c in CropName if is_feasible(c, l, y, s)) <= LandArea[\n", " l], f\"LandAreaConstraint_{l}_{y}_{s}\"" ], "outputs": [], "execution_count": 27 }, { "cell_type": "code", "id": "1f6ac4323825f28b", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:19.240711Z", "start_time": "2024-09-08T08:14:19.226182Z" } }, "source": [ "# 条件3： 平旱地、梯田和山坡地每年适宜单季种植[粮食类作物（水稻除外）]。因为除了[粮食类作物（水稻除外）]以外的作物似乎已经被上面给约束了，所以大概不需要做限制了吧\n", "for l in LandName:\n", " if l[0] in [\"A\", \"B\", \"C\"]: # [\"平旱地\", \"梯田\", \"山坡地\"]\n", " for y in years:\n", " model += lpSum(\n", " Y[c, l, y, 2] for c in CropName if is_feasible(c, l, y, 2)) == 0, f\"SingleSeasonConstraint1_{y}_{l}\"\n", "\n" ], "outputs": [], "execution_count": 28 }, { "cell_type": "code", "id": "c0e9b6b37092f0e7", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:19.256292Z", "start_time": "2024-09-08T08:14:19.241709Z" } }, "source": [ "# 条件4： 水浇地每年可以单季种植水稻或两季种植蔬菜作物。\n", "for l in LandName:\n", " if l[0] == \"D\":\n", " for y in years:\n", " for c in CropType[\"全蔬菜\"]:\n", " if is_feasible(c, l, y, 2):\n", " model += Y[\"水稻\", l, y, 1] + Y[c, l, y, 2] <= 1, f\"IrrigatedConstraint0_{l}_{y}_{c}\"\n" ], "outputs": [], "execution_count": 29 }, { "cell_type": "code", "id": "e8fb2dea1326a05b", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:19.287009Z", "start_time": "2024-09-08T08:14:19.257188Z" } }, "source": [ "# 条件10： 别种得太碎了，啥意思？ 每种作物不超过4块地吧。\n", "for c in CropName:\n", " for y in years:\n", " for s in SeasonNum:\n", " model += lpSum(\n", " Y[c, l, y, s] for l in LandName if is_feasible(c, l, y, s)) <= 3, f\"MaxCropTypeConstraint_{c}_{y}_{s}\"" ], "outputs": [], "execution_count": 30 }, { "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:19.333885Z", "start_time": "2024-09-08T08:14:19.288072Z" } }, "cell_type": "code", "source": [ "# 条件11： 每块地最大种植作物种类数3\n", "for l in LandName:\n", " for y in years:\n", " for s in SeasonNum:\n", " model += lpSum(\n", " Y[c, l, y, s] for c in CropName if is_feasible(c, l, y, s)) <= 3, f\"MaxLandConstraint_{l}_{y}_{s}\"" ], "id": "b8d9ae82090818ec", "outputs": [], "execution_count": 31 }, { "cell_type": "code", "id": "49f1490823c6af3c", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:19.411639Z", "start_time": "2024-09-08T08:14:19.335783Z" } }, "source": [ "# 条件12： 最小种植面积：0.2吧\n", "for l in LandName:\n", " for y in years:\n", " for s in SeasonNum:\n", " for c in CropName:\n", " if is_feasible(c, l, y, s):\n", " model += X[c, l, y, s] >= 0.2 * (\n", " 1 if X[c, l, y, s] else 0), f\"MinCropAreaConstraint_{c}_{l}_{y}_{s}\"" ], "outputs": [], "execution_count": 32 }, { "cell_type": "code", "id": "bdf1048b83723f91", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:19.473674Z", "start_time": "2024-09-08T08:14:19.412530Z" } }, "source": [ "# 条件13 ： 最重要的，不能重复种植同一块地同一年同一季的同一作物\n", "# 每种作物在同一地块（含大棚）都不能连续重茬种植\n", "\n", "for l in LandName:\n", " for c in CropName:\n", " for y in years[1:]: # 单季不能连年种植 同一年不能连续种植 跨年也不能连续种植\n", " if is_feasible(c, l, y - 1, 1) and is_feasible(c, l, y - 1, 2):\n", " model += Y[c, l, y - 1, 1] + Y[c, l, y - 1, 2] <= 1, f\"RepeatPlantingConstraint_{c}_{l}_{y}\"\n", " model += Y[c, l, y - 1, 2] + Y[c, l, y, 1] <= 1, f\"RepeatPlantingConstraint1_{c}_{l}_{y}\"\n", " if is_feasible(c, l, y - 1, 1) and is_feasible(c, l, y, 1):\n", " if l[0] in [\"A\", \"B\", \"C\"]: # and c in CropType[\"全粮食\"]:\n", " model += Y[c, l, y - 1, 1] + Y[c, l, y, 1] <= 1, f\"RepeatPlantingConstraint2_{c}_{l}_{y}\"\n", " elif l[0] == \"D\" and c == \"水稻\":\n", " model += Y[c, l, y - 1, 1] + Y[c, l, y, 1] <= 1, f\"RepeatPlantingConstraint3_{c}_{l}_{y}\"\n" ], "outputs": [], "execution_count": 33 }, { "cell_type": "code", "id": "50da0aff9c68ae24", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:19.488304Z", "start_time": "2024-09-08T08:14:19.474674Z" } }, "source": [ "# 条件14：从 2023 年开始，要求每个地块（含大棚） 在三年内至少种满一次豆类作物\n", "for l in LandName:\n", " for y in years[2:]: # 只需循环到倒数第三年，因为要考虑三年周期\n", " # 在 y-2 到 y+2 之间的三年内，至少种满一次豆类作物\n", " model += lpSum(X[c, l, y_r, s]\n", " for c in CropType['豆类']\n", " for y_r in range(y - 2, y + 1)\n", " for s in SeasonNum if is_feasible(c, l, y_r, s)) >= LandArea[l], f\"BeanConstraint_{l}_{y}\"\n" ], "outputs": [], "execution_count": 34 }, { "cell_type": "code", "id": "d4792a1210afca3b", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:33.144757Z", "start_time": "2024-09-08T08:14:19.489518Z" } }, "source": [ "%%time\n", "model.solve(\n", " pulp.GUROBI_CMD(msg=True,\n", " timeLimit=7200,\n", " threads=20,\n", " options=[(\"Method\", 2), (\"MIPGap\", 0.0001)]))\n" ], "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: total: 78.1 ms\n", "Wall time: 13.6 s\n" ] }, { "data": { "text/plain": [ "1" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "execution_count": 35 }, { "cell_type": "code", "id": "cb3f4e95111e3292", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:33.570095Z", "start_time": "2024-09-08T08:14:33.146145Z" } }, "source": [ "# 输出文件名，包含起始年份和结束年份\n", "output_filename = f\"planting_plan_1_1_{years[0]}-{years[-1]}.xlsx\"\n", "\n", "with pd.ExcelWriter(output_filename) as writer:\n", " for y in years:\n", "\n", " # 用于存储需要交换的DataFrame\n", " sheets_to_swap = {}\n", "\n", " for s in SeasonNum:\n", " # 创建一个空的 DataFrame，横轴为作物名称，纵轴为地块名称\n", " result_table = pd.DataFrame(columns=CropName, index=LandName)\n", "\n", " # 填充表格数据\n", " for l in LandName:\n", " for c in CropName:\n", " # 获取变量 X[c, l, y, s] 的值\n", " if is_feasible(c, l, y, s):\n", " crop_value = value(X[c, l, y, s])\n", " if crop_value is not None and crop_value > 0:\n", " result_table.at[l, c] = crop_value # 填入结果\n", "\n", " # 用 0 填充空值\n", " result_table.fillna(0, inplace=True)\n", " sheet_name = f\"{y}_Season_第{s}季\"\n", " result_table.to_excel(writer, sheet_name=sheet_name)\n", "\n", "print(f\"结果已保存到文件：{output_filename}\")\n" ], "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "结果已保存到文件：planting_plan_1_1_2024-2030.xlsx\n" ] } ], "execution_count": 36 }, { "cell_type": "code", "id": "ebbf10d3", "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:33.943958Z", "start_time": "2024-09-08T08:14:33.571680Z" } }, "source": [ "# 四舍五入版\n", "output_filename = f\"planting_plan_1_1_{years[0]}-{years[-1]}-四舍五入版.xlsx\"\n", "\n", "with pd.ExcelWriter(output_filename) as writer:\n", " for y in years:\n", " # 用于存储需要交换的DataFrame\n", " sheets_to_swap = {}\n", "\n", " for s in SeasonNum:\n", " # 创建一个空的 DataFrame，横轴为作物名称，纵轴为地块名称\n", " result_table = pd.DataFrame(columns=CropName, index=LandName)\n", "\n", " # 填充表格数据\n", " for l in LandName:\n", " for c in CropName:\n", " # 获取变量 X[c, l, y, s] 的值\n", " if is_feasible(c, l, y, s):\n", " crop_value = value(X[c, l, y, s])\n", " if crop_value is not None and crop_value > 0:\n", " result_table.at[l, c] = crop_value # 填入结果\n", "\n", " # 用 0 填充空值\n", " result_table.fillna(0, inplace=True)\n", "\n", " # 对DataFrame中的所有数值进行四舍五入，保留两位小数\n", " result_table = result_table.round(2)\n", "\n", " sheet_name = f\"{y}_Season_第{s}季\"\n", " result_table.to_excel(writer, sheet_name=sheet_name)\n" ], "outputs": [], "execution_count": 37 }, { "metadata": { "ExecuteTime": { "end_time": "2024-09-08T08:14:33.959313Z", "start_time": "2024-09-08T08:14:33.944640Z" } }, "cell_type": "code", "source": "", "id": "ab1fd16df70c4293", "outputs": [], "execution_count": 37 } ], 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