proffapt / mip_optimisation

MIP optimisation using GUROBIPY, OR LAB Project

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MIP Optimisation

This is the code repository for the final project submitted for OR LAB, Industrial & Systems Engineering, IIT KGP.
Here we have presented a POC method to optimise the menu of our mess using the Mixed Integer Programming model.
It also gives multiple solutions based on the deviation specified from the Optimal Solution.
Following example of Input and it's corresponding Output demonstrates what it is supposed to do.

Input

parameter value
age 25
gender M
budget_up 250
budget_low 100

The final model for this example is store in demo_model.lp.

Output

>> Using python 3
Enter your age: 25
Enter your gender (M/F): M
Enter your budget's upper limit: 250
Enter your budget's lower limit: 100
Set parameter Username
Academic license - for non-commercial use only - expires 2023-12-31

Optimal Solution
Food_Item_12: 2.10 servings
Food_Item_29: 0.73 servings
Food_Item_46: 7.90 servings
Food_Item_53: 3.00 servings
Food_Item_60: 0.36 servings
Food_Item_87: 4.00 servings
Food_Item_95: 0.82 servings
Total Cost: $228.16


Other Solution #2
Food_Item_36: 4.91 servings
Food_Item_39: 0.53 servings
Food_Item_46: 19.61 servings
Food_Item_59: 3.06 servings
Food_Item_68: 0.31 servings
Total Cost: $250.00


Other Solution #3
Food_Item_8: 1.00 servings
Food_Item_36: 5.44 servings
Food_Item_46: 21.20 servings
Food_Item_59: 2.48 servings
Total Cost: $238.36


Other Solution #4
Food_Item_36: 2.05 servings
Food_Item_39: 3.52 servings
Food_Item_46: 5.74 servings
Food_Item_59: 2.01 servings
Food_Item_69: 1.00 servings
Total Cost: $246.03


Other Solution #5
Food_Item_8: 1.00 servings
Food_Item_14: 1.00 servings
Food_Item_36: 5.53 servings
Food_Item_46: 14.81 servings
Food_Item_59: 1.94 servings
Total Cost: $198.68


Other Solution #6
Food_Item_36: 5.44 servings
Food_Item_46: 21.03 servings
Food_Item_59: 3.04 servings
Food_Item_68: 0.12 servings
Food_Item_82: 1.00 servings
Total Cost: $249.92


Other Solution #7
Food_Item_4: 1.00 servings
Food_Item_8: 1.00 servings
Food_Item_14: 1.00 servings
Food_Item_36: 4.39 servings
Food_Item_46: 10.26 servings
Food_Item_59: 1.41 servings
Total Cost: $155.14


Other Solution #8
Food_Item_11: 4.00 servings
Food_Item_12: 0.44 servings
Food_Item_14: 1.00 servings
Food_Item_39: 2.88 servings
Food_Item_46: 3.50 servings
Food_Item_59: 0.20 servings
Food_Item_69: 1.00 servings
Food_Item_73: 0.16 servings
Total Cost: $250.00


Other Solution #9
Food_Item_8: 1.00 servings
Food_Item_36: 5.55 servings
Food_Item_46: 14.00 servings
Food_Item_57: 1.00 servings
Food_Item_59: 2.21 servings
Total Cost: $186.10


Other Solution #10
Food_Item_11: 5.00 servings
Food_Item_12: 0.34 servings
Food_Item_14: 1.00 servings
Food_Item_27: 0.14 servings
Food_Item_39: 2.60 servings
Food_Item_46: 4.34 servings
Food_Item_59: 0.44 servings
Food_Item_69: 1.00 servings
Total Cost: $250.00

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MIP optimisation using GUROBIPY, OR LAB Project


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