Introduction to Prescriptive AI by Akshay Kulkarni & Adarsha Shivananda & Avinash Manure

Author:Akshay Kulkarni & Adarsha Shivananda & Avinash Manure
Language: eng
Format: epub
ISBN: 9781484295687
Publisher: Apress

Step 3: Adding constraints[In]: opt_model += (lpSum(x.values()) <= 45, "Manpower")

[In]: opt_model += (6 * x[1] + 4 * x[2] + 2 * x[3] <= 100, "Wood Pulp")

[In]: opt_model += (2 * x[2] + 4 * x[3] + 6 * x[4] <= 75, "Fiber")

Step 4: Setting the objective function[In]: opt_model += (10 * x[1] + 11 * x[2] + 8 * x[3] + 12.5 * x[4], "Objective Function")

Step 5: Utilizing the default solver method for solving the given optimization problem[In]: status = opt_model.solve()

Step 6: Getting the results[In]: print(f"status: {opt_model.status}, {LpStatus[opt_model.status]}")

[In]: print(f"objective: {opt_model.objective.value()}")

[In]: for var in x.values():

print(f"{var.name}: {var.value()}")

[In]: for name, constraint in opt_model.constraints.items():

print(f"{name}: {constraint.value()}")

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