281 lines
11 KiB
Python
281 lines
11 KiB
Python
import gurobipy as gp
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from gurobipy import GRB, Model, quicksum
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HYPEREDGES = {
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4: (['Butadien', 'Butadien'], []),
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5: (['Butadien', 'Butadien'], ['Butadien', 'Butadien']),
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7: (['Butadien', 'Butadien'], []),
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9: (['p_{0,0}', 'p_{0,0}'], []),
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10: (['p_{0,0}', 'p_{0,1}'], ['Butadien', 'Butadien']),
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11: (['p_{0,0}', 'p_{0,1}'], []),
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13: (['p_{0,0}', 'p_{0,2}'], []),
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14: (['p_{0,0}', 'p_{0,2}'], []),
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15: (['Butadien', 'p_{0,0}'], ['Butadien']),
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16: (['p_{0,1}', 'p_{0,1}'], []),
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18: (['p_{0,1}', 'p_{0,1}'], ['Butadien']),
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20: (['p_{0,1}', 'p_{0,2}'], ['Butadien']),
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21: (['Butadien', 'p_{0,1}'], ['Butadien']),
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22: (['p_{0,1}', 'p_{0,2}'], []),
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23: (['Butadien', 'p_{0,1}'], []),
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24: (['p_{0,2}', 'p_{0,2}'], []),
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25: (['Butadien', 'p_{0,2}'], ['Butadien']),
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26: (['Butadien', 'p_{0,2}'], []),
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28: (['p_{0,0}', 'p_{0,1}'], []),
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30: (['Butadien', 'p_{0,0}'], []),
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32: (['Butadien', 'p_{0,1}'], []),
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33: (['Butadien', 'p_{0,1}'], []),
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35: (['Butadien', 'p_{0,1}'], []),
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37: (['Butadien', 'p_{0,1}'], []),
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38: (['p_{0,3}'], []),
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42: (['p_{0,4}'], []),
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50: (['p_{0,3}', 'p_{0,3}'], []),
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51: (['p_{0,3}', 'p_{0,4}'], []),
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52: (['p_{0,3}', 'p_{0,5}'], []),
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53: (['p_{0,3}', 'p_{0,6}'], []),
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54: (['p_{0,3}', 'p_{0,8}'], []),
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55: (['p_{0,3}', 'p_{0,9}'], []),
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56: (['p_{0,3}', 'p_{0,10}'], []),
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57: (['p_{0,2}', 'p_{0,3}'], []),
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58: (['p_{0,0}', 'p_{0,3}'], []),
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59: (['Butadien', 'p_{0,3}'], ['Butadien']),
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60: (['p_{0,1}', 'p_{0,3}'], []),
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61: (['p_{0,4}', 'p_{0,4}'], []),
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62: (['p_{0,4}', 'p_{0,5}'], []),
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64: (['p_{0,4}', 'p_{0,6}'], []),
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65: (['p_{0,2}', 'p_{0,4}'], []),
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66: (['p_{0,0}', 'p_{0,4}'], ['Butadien']),
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67: (['Butadien', 'p_{0,4}'], []),
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68: (['Butadien', 'p_{0,4}'], ['Butadien']),
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69: (['p_{0,1}', 'p_{0,4}'], []),
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70: (['p_{0,4}', 'p_{0,6}'], []),
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71: (['p_{0,4}', 'p_{0,8}'], []),
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72: (['p_{0,4}', 'p_{0,9}'], []),
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73: (['p_{0,4}', 'p_{0,10}'], []),
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74: (['p_{0,2}', 'p_{0,4}'], []),
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75: (['p_{0,0}', 'p_{0,4}'], []),
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76: (['p_{0,5}', 'p_{0,5}'], []),
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77: (['p_{0,5}', 'p_{0,6}'], []),
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78: (['p_{0,2}', 'p_{0,5}'], []),
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79: (['p_{0,0}', 'p_{0,5}'], ['Butadien']),
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80: (['Butadien', 'p_{0,5}'], []),
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81: (['Butadien', 'p_{0,5}'], ['Butadien']),
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82: (['p_{0,1}', 'p_{0,5}'], []),
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83: (['p_{0,1}', 'p_{0,5}'], []),
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84: (['p_{0,5}', 'p_{0,6}'], []),
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85: (['p_{0,5}', 'p_{0,8}'], []),
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86: (['p_{0,5}', 'p_{0,9}'], []),
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87: (['p_{0,5}', 'p_{0,10}'], []),
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88: (['p_{0,0}', 'p_{0,5}'], []),
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89: (['p_{0,6}', 'p_{0,6}'], []),
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90: (['p_{0,6}', 'p_{0,8}'], []),
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91: (['p_{0,6}', 'p_{0,9}'], []),
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92: (['p_{0,6}', 'p_{0,10}'], []),
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93: (['p_{0,2}', 'p_{0,6}'], []),
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94: (['p_{0,0}', 'p_{0,6}'], []),
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95: (['Butadien', 'p_{0,6}'], ['Butadien']),
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96: (['Butadien', 'p_{0,6}'], []),
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97: (['p_{0,1}', 'p_{0,6}'], ['Butadien']),
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98: (['p_{0,1}', 'p_{0,6}'], []),
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100: (['p_{0,0}', 'p_{0,6}'], []),
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102: (['p_{0,0}', 'p_{0,7}'], []),
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103: (['p_{0,8}', 'p_{0,8}'], []),
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104: (['p_{0,8}', 'p_{0,9}'], []),
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105: (['p_{0,8}', 'p_{0,10}'], []),
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106: (['p_{0,2}', 'p_{0,8}'], []),
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107: (['p_{0,0}', 'p_{0,8}'], []),
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108: (['Butadien', 'p_{0,8}'], ['Butadien']),
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109: (['p_{0,1}', 'p_{0,8}'], []),
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110: (['p_{0,9}', 'p_{0,9}'], []),
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111: (['p_{0,9}', 'p_{0,10}'], []),
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112: (['p_{0,2}', 'p_{0,9}'], []),
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113: (['p_{0,0}', 'p_{0,9}'], []),
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114: (['Butadien', 'p_{0,9}'], ['Butadien']),
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115: (['p_{0,1}', 'p_{0,9}'], []),
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116: (['p_{0,10}', 'p_{0,10}'], []),
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117: (['p_{0,2}', 'p_{0,10}'], []),
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118: (['p_{0,0}', 'p_{0,10}'], []),
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119: (['Butadien', 'p_{0,10}'], ['Butadien']),
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120: (['p_{0,1}', 'p_{0,10}'], []),
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121: (['p_{0,0}', 'p_{0,4}'], []),
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123: (['p_{0,0}', 'p_{0,4}'], []),
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125: (['Butadien', 'p_{0,7}'], []),
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130: (['p_{0,14}'], []),
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132: (['p_{0,15}'], []),
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135: (['p_{0,0}', 'p_{0,11}'], []),
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136: (['p_{0,12}', 'p_{0,12}'], []),
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137: (['p_{0,12}', 'p_{0,13}'], []),
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138: (['p_{0,12}', 'p_{0,14}'], []),
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139: (['p_{0,12}', 'p_{0,15}'], []),
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140: (['p_{0,12}', 'p_{0,16}'], []),
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141: (['p_{0,8}', 'p_{0,12}'], []),
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142: (['p_{0,9}', 'p_{0,12}'], []),
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143: (['Butadien', 'p_{0,12}'], ['Butadien']),
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144: (['p_{0,10}', 'p_{0,12}'], []),
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145: (['p_{0,0}', 'p_{0,12}'], []),
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146: (['p_{0,1}', 'p_{0,12}'], []),
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147: (['p_{0,2}', 'p_{0,12}'], []),
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148: (['p_{0,3}', 'p_{0,12}'], []),
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149: (['p_{0,4}', 'p_{0,12}'], []),
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150: (['p_{0,5}', 'p_{0,12}'], []),
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151: (['p_{0,6}', 'p_{0,12}'], []),
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152: (['p_{0,13}', 'p_{0,13}'], []),
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153: (['Butadien', 'p_{0,13}'], []),
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154: (['Butadien', 'p_{0,13}'], ['Butadien']),
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155: (['p_{0,0}', 'p_{0,13}'], ['Butadien']),
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156: (['p_{0,1}', 'p_{0,13}'], []),
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157: (['p_{0,1}', 'p_{0,13}'], []),
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158: (['p_{0,2}', 'p_{0,13}'], []),
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159: (['p_{0,4}', 'p_{0,13}'], []),
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160: (['p_{0,5}', 'p_{0,13}'], []),
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161: (['p_{0,6}', 'p_{0,13}'], []),
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162: (['p_{0,13}', 'p_{0,14}'], []),
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163: (['p_{0,13}', 'p_{0,15}'], []),
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164: (['p_{0,13}', 'p_{0,16}'], []),
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165: (['p_{0,8}', 'p_{0,13}'], []),
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166: (['p_{0,9}', 'p_{0,13}'], []),
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167: (['p_{0,10}', 'p_{0,13}'], []),
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168: (['p_{0,0}', 'p_{0,13}'], []),
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169: (['p_{0,2}', 'p_{0,13}'], []),
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170: (['p_{0,3}', 'p_{0,13}'], []),
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171: (['p_{0,14}', 'p_{0,14}'], []),
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172: (['p_{0,14}', 'p_{0,15}'], []),
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173: (['p_{0,14}', 'p_{0,16}'], []),
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174: (['p_{0,8}', 'p_{0,14}'], []),
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175: (['p_{0,9}', 'p_{0,14}'], []),
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176: (['Butadien', 'p_{0,14}'], ['Butadien']),
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177: (['p_{0,10}', 'p_{0,14}'], []),
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178: (['p_{0,0}', 'p_{0,14}'], []),
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179: (['p_{0,1}', 'p_{0,14}'], []),
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180: (['p_{0,2}', 'p_{0,14}'], []),
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181: (['p_{0,3}', 'p_{0,14}'], []),
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182: (['p_{0,4}', 'p_{0,14}'], []),
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183: (['p_{0,5}', 'p_{0,14}'], []),
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184: (['p_{0,6}', 'p_{0,14}'], []),
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185: (['p_{0,15}', 'p_{0,15}'], []),
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186: (['p_{0,15}', 'p_{0,16}'], []),
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187: (['p_{0,8}', 'p_{0,15}'], []),
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188: (['p_{0,9}', 'p_{0,15}'], []),
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189: (['Butadien', 'p_{0,15}'], ['Butadien']),
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190: (['p_{0,10}', 'p_{0,15}'], []),
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191: (['p_{0,0}', 'p_{0,15}'], []),
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192: (['p_{0,1}', 'p_{0,15}'], []),
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193: (['p_{0,2}', 'p_{0,15}'], []),
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194: (['p_{0,3}', 'p_{0,15}'], []),
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195: (['p_{0,4}', 'p_{0,15}'], []),
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196: (['p_{0,5}', 'p_{0,15}'], []),
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197: (['p_{0,6}', 'p_{0,15}'], []),
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198: (['p_{0,16}', 'p_{0,16}'], []),
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199: (['p_{0,8}', 'p_{0,16}'], []),
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200: (['p_{0,9}', 'p_{0,16}'], []),
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201: (['Butadien', 'p_{0,16}'], ['Butadien']),
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202: (['p_{0,10}', 'p_{0,16}'], []),
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203: (['p_{0,0}', 'p_{0,16}'], []),
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204: (['p_{0,1}', 'p_{0,16}'], []),
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205: (['p_{0,2}', 'p_{0,16}'], []),
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206: (['p_{0,3}', 'p_{0,16}'], []),
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207: (['p_{0,4}', 'p_{0,16}'], []),
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208: (['p_{0,5}', 'p_{0,16}'], []),
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209: (['p_{0,6}', 'p_{0,16}'], []),
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211: (['Butadien', 'p_{0,11}'], []),
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}
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VERTICES = ['Butadien', 'p_{0,0}', 'p_{0,1}', 'p_{0,2}', 'p_{0,3}', 'p_{0,4}', 'p_{0,5}', 'p_{0,6}', 'p_{0,7}', 'p_{0,8}', 'p_{0,9}', 'p_{0,10}', 'p_{0,11}', 'p_{0,12}', 'p_{0,13}', 'p_{0,14}', 'p_{0,15}', 'p_{0,16}', 'p_{0,17}', 'p_{0,18}']
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VERTICESSMILES = ['C=CC=C', 'C=C', 'C=CC=CC=C', 'C1CCC(C=C)CC=1', 'C(CCC(C=C)CC=C)=C', 'C=CC=CC=CC=C', 'C1CCC(C=CC=C)CC=1', 'C=CC1C=CCCC1', 'C1CCCCC=1', 'C=CC1CC=CCC1C=C', 'C1CCC(C=C)C(C=C)C=1', 'C(C1CC(C=C)C=CC1)=C', 'C1C=CC=CC=1', 'C(CCC1C=CC=CC1)=C', 'C1C(C=CC=C)CCCC=1', 'C=CC(C=C)CCCC=C', 'C=CCCCCC=C', 'C=CC1C=CC(C=C)CC1', 'C1CC2CCCCC2CC=1', 'C1CC2C=CC=CC2CC=1']
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FIXED_FLOWS = {
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#1: 1,
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}
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def build_model(name, hyperedges, vertices, nmrlikelihoods, excluded_support=None):
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model = Model(name)
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x = {e_id: model.addVar(vtype=GRB.INTEGER, lb = 0, name = f"x_{e_id}") for e_id in hyperedges}
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b = {e_id: model.addVar(vtype=GRB.BINARY, name = f"b_{e_id}") for e_id in hyperedges}
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n = model.addVars(vertices, vtype=GRB.CONTINUOUS, lb = 0.0, ub = 1.0, name = "nmr")
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for v, nmr in zip(vertices, nmrlikelihoods):
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n[v] = nmr
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vertices = set(v for tails, heads in hyperedges.values() for v in tails + heads)
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for v in vertices:
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inflow = quicksum(x[e_id] for e_id, (_, heads) in hyperedges.items() if v in heads)
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outflow = quicksum(x[e_id] for e_id, (tails, _) in hyperedges.items() if v in tails)
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model.addConstr(inflow == outflow, name = f"flow_conservation_{v}")
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for e_id, value in FIXED_FLOWS.items():
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model.addConstr(x[e_id] == value, name = f"fixed_flow_{e_id}")
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for e_id in hyperedges:
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model.addGenConstrIndicator(b[e_id], 0, x[e_id] == 0, name = f"unused_implies_zero_{e_id}")
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model.addConstr(x[e_id] >= b[e_id], name = f"used_implies_positive_flow_{e_id}")
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reaction_path = {}
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if excluded_support:
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model.addConstr(quicksum(b[e_id] for e_id in excluded_support) <= len(excluded_support) - 1, name = "different_hyperedges",)
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#Multiplizier den node Wert mit infow + outflow
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model.ModelSense = GRB.MAXIMIZE
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#Multiply node value with infow or outflow
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model.setObjectiveN(
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quicksum(n[t_id[0]] * x[e_id] for e_id, (_, t_id) in hyperedges.items() if t_id != []),
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index = 0,
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priority = 2,
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name = "maximize_nmr_similarity",
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)
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model.setObjectiveN(
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quicksum(-1 * x[e_id] for e_id in hyperedges),
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index=1,
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priority=1,
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name="minimize_used_hyperedges",
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)
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return model, x, b
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def positive_entries(variable_dict, threshold = 0.5):
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return {e_id: var.X for e_id, var in variable_dict.items() if var.X > threshold}
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def print_solution(title, flow_solution, binary_solution, hyperedges):
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print(f"\n{title}:")
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for e_id in sorted(flow_solution):
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flow = flow_solution[e_id]
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tails, heads = hyperedges[e_id]
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print(f"Hyperedge {e_id}: Flow = {flow}, Tails = {tails}, Heads = {heads}")
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print("\nBinary Variables:")
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for e_id in sorted(binary_solution):
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print(f"Binary Variable b_{e_id} = {binary_solution[e_id]}")
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print(f"\nTotal flow: {sum(flow_solution.values())}")
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print(f"Number of used hyperedges: {len(binary_solution)}")
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def main():
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model, x, b = build_model("HypergraphFlow", HYPEREDGES, VERTICES, NMRLIKELYHOODS)
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model.optimize()
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if model.status != GRB.Status.OPTIMAL:
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print("No optimal solution found for the first model.")
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return
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optimal_solution = positive_entries(x)
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optimal_binary_solution = positive_entries(b)
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print_solution("Optimal Solution", optimal_solution, optimal_binary_solution, HYPEREDGES)
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""" excluded_support = list(optimal_binary_solution.keys())
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second_model, x2, b2 = build_model("SecondBestHypergraphFlow", HYPEREDGES, excluded_support=excluded_support,)
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second_model.optimize()
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if second_model.status == GRB.Status.OPTIMAL:
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second_solution = positive_entries(x2)
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second_binary_solution = positive_entries(b2)
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print_solution("Second Best Solution", second_solution, second_binary_solution, HYPEREDGES, VERTICES)
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else:
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print("No optimal solution found for the second best model.")
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"""
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if __name__ == "__main__":
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main() |