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silver_meal_heuristic.py

silver_meal_heuristic

dict_in = {'planningPeriod': 14, 'fixedCost': 10000, 'varCost': 1, 'roll': 4} module-attribute

demand = [0, 0, 6022, 6103, 3533, 4046, 3044, 3023, 4064, 9552, 3960, 5077, 4000, 4000, 3430, 300, 3400, 3440, 200, 3400, 9400, 4340, 3400, 300, 3040, 4000, 5000, 6500, 45454, 4443, 3244, 2334, 344, 3223, 2999, 4000, 4000, 4000, 3400, 3400, 3444, 5006, 4500, 400, 4500, 3400, 5400, 0, 0, 0, 4500, 4500, 4400, 555, 4540, 0, 0, 4555, 3000, 4555, 455, 3444, 4333, 2344, 4454, 4555, 3444] module-attribute

silver_m = SilverMeal() module-attribute

output = silver_m.run(dict_in, demand) module-attribute

SilverMeal

Source code in examples/lot_sizing/lot_optimizers/silver_meal_heuristic.py 
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class SilverMeal:
    def __init__(self):
        pass

    def run(self, dict_in, demand):
        # Füllen der Variablen aus Start_Dictionary
        dem = demand
        kf = dict_in["fixedCost"]
        kv = dict_in["varCost"]
        pp = len(dem)
        # rh = dict_in["roll"]
        # print(pp)
        orders = [0 for i in range(pp)]
        orders1 = [0 for i in range(pp)]

        c = kf
        d = kf + 1
        p = 0
        y = 1
        cost_i = 0

        # testen ob "Null-Perioden am Anfang vorliegen
        while dem[p] == 0:
            orders1[p] = 0
            p = p + 1
            if p == pp:
                p = p - 1
                break
        i = p

        while p < pp:
            c = c + kv * dem[p] * (p - i)

            bed = c / y

            if d > bed:
                orders[p] += dem[p]
                lot = sum(orders) - sum(orders1)
                cost_i = kv * dem[p] * (p - i) + cost_i
                d = bed
                y = y + 1

            else:
                orders1[i] = lot
                i = p
                p = p - 1
                c = kf
                bed = 0
                d = kf + 1
                y = 1

            p = p + 1

        lot = sum(orders) - sum(orders1)
        orders1[i] = lot

        x = orders1.count(0)
        fix = (pp - x) * kf
        # print(cost_i)
        cost_i + fix
        #  print("Total Cost: " + str(total_c))
        #        print(sum(orders1))
        return np.array(orders1)

__init__()

Source code in examples/lot_sizing/lot_optimizers/silver_meal_heuristic.py 
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def __init__(self):
    pass

run(dict_in, demand)

Source code in examples/lot_sizing/lot_optimizers/silver_meal_heuristic.py 
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def run(self, dict_in, demand):
    # Füllen der Variablen aus Start_Dictionary
    dem = demand
    kf = dict_in["fixedCost"]
    kv = dict_in["varCost"]
    pp = len(dem)
    # rh = dict_in["roll"]
    # print(pp)
    orders = [0 for i in range(pp)]
    orders1 = [0 for i in range(pp)]

    c = kf
    d = kf + 1
    p = 0
    y = 1
    cost_i = 0

    # testen ob "Null-Perioden am Anfang vorliegen
    while dem[p] == 0:
        orders1[p] = 0
        p = p + 1
        if p == pp:
            p = p - 1
            break
    i = p

    while p < pp:
        c = c + kv * dem[p] * (p - i)

        bed = c / y

        if d > bed:
            orders[p] += dem[p]
            lot = sum(orders) - sum(orders1)
            cost_i = kv * dem[p] * (p - i) + cost_i
            d = bed
            y = y + 1

        else:
            orders1[i] = lot
            i = p
            p = p - 1
            c = kf
            bed = 0
            d = kf + 1
            y = 1

        p = p + 1

    lot = sum(orders) - sum(orders1)
    orders1[i] = lot

    x = orders1.count(0)
    fix = (pp - x) * kf
    # print(cost_i)
    cost_i + fix
    #  print("Total Cost: " + str(total_c))
    #        print(sum(orders1))
    return np.array(orders1)