A Production Mix Problem (PRODMIX)

prodmix.py

"""
## GAMSSOURCE: https://www.gams.com/latest/gamslib_ml/libhtml/gamslib_prodmix.html
## LICENSETYPE: Demo
## MODELTYPE: LP
## KEYWORDS: linear programming, production planning, manufacturing, furniture production


A Production Mix Problem (PRODMIX)

A furniture company wants to maximize its profits from the
manufacture of different types of desks.


Dantzig, G B, Chapter 3.5. In Linear Programming and Extensions.
Princeton University Press, Princeton, New Jersey, 1963.
"""

from __future__ import annotations

import os

import numpy as np

from gamspy import Container
from gamspy import Equation
from gamspy import Model
from gamspy import Parameter
from gamspy import Sense
from gamspy import Set
from gamspy import Sum
from gamspy import Variable


def main():
    m = Container(
        system_directory=os.getenv("SYSTEM_DIRECTORY", None),
        delayed_execution=int(os.getenv("DELAYED_EXECUTION", False)),
    )

    # Set
    desk = Set(m, name="desk", records=["d1", "d2", "d3", "d4"])
    shop = Set(m, name="shop", records=["carpentry", "finishing"])

    # Data
    labor = Parameter(
        m,
        name="labor",
        domain=[shop, desk],
        records=np.array([[4, 9, 7, 10], [1, 1, 3, 40]]),
        description="labor requirements (man-hours)",
    )
    caplim = Parameter(
        m,
        name="caplim",
        domain=shop,
        records=np.array([6000, 4000]),
        description="capacity (man hours)",
    )
    price = Parameter(
        m,
        name="price",
        domain=desk,
        records=np.array([12, 20, 18, 40]),
        description="per unit sold ($)",
    )

    # Variable
    mix = Variable(
        m,
        name="mix",
        domain=desk,
        type="Positive",
        description="mix of desks produced (number of desks)",
    )
    profit = Variable(
        m, name="profit", description="total profit                        ($)"
    )

    # Equation
    cap = Equation(
        m,
        name="cap",
        domain=shop,
        description="capacity constraint (man-hours)",
    )
    ap = Equation(m, name="ap", description="accounting: total profit    ($)")

    cap[shop] = Sum(desk, labor[shop, desk] * mix[desk]) <= caplim[shop]
    ap[...] = profit == Sum(desk, price[desk] * mix[desk])

    pmp = Model(
        m,
        name="pmp",
        equations=m.getEquations(),
        problem="LP",
        sense=Sense.MAX,
        objective=profit,
    )

    pmp.solve()


if __name__ == "__main__":
    main()