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least_unit_cost_method.py

least_unit_cost_method

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

leastunitcostmethod = LeastUnitCostMethod() module-attribute

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

LeastUnitCostMethod

Source code in examples/lot_sizing/lot_optimizers/least_unit_cost_method.py 
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class LeastUnitCostMethod:
    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)

        p = 0
        kpj = 0
        kppj = 0
        orders = [0 for i in range(pp)]
        total_c = 0

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

        while p < pp:
            j = p
            lg1 = 0
            lg2 = 0
            kppj = (kf + (kv * dem[j] * (j - p))) / dem[j]
            while j < pp:
                last_c = kpj * lg2
                lg1 += dem[j] * (j - p)  # Aufsummierung der Nachfrage, in Abhängigkeit der Verzinsung
                lg2 += dem[j]  # Aufsummierung der Nachfrage
                kpj = (kf + kv * lg1) / lg2
                if kpj > kppj:
                    orders[p] = lg2 - dem[j]
                    total_c += last_c
                    break
                j += 1
                kppj = kpj
            temp = p
            p = j
        total_c += kpj * lg2
        orders[temp] = lg2
        #   print("Total Cost: " + str(total_c))
        #        print(sum(orders))
        return np.array(orders)

__init__()

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

run(dict_in, demand)

Source code in examples/lot_sizing/lot_optimizers/least_unit_cost_method.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)

    p = 0
    kpj = 0
    kppj = 0
    orders = [0 for i in range(pp)]
    total_c = 0

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

    while p < pp:
        j = p
        lg1 = 0
        lg2 = 0
        kppj = (kf + (kv * dem[j] * (j - p))) / dem[j]
        while j < pp:
            last_c = kpj * lg2
            lg1 += dem[j] * (j - p)  # Aufsummierung der Nachfrage, in Abhängigkeit der Verzinsung
            lg2 += dem[j]  # Aufsummierung der Nachfrage
            kpj = (kf + kv * lg1) / lg2
            if kpj > kppj:
                orders[p] = lg2 - dem[j]
                total_c += last_c
                break
            j += 1
            kppj = kpj
        temp = p
        p = j
    total_c += kpj * lg2
    orders[temp] = lg2
    #   print("Total Cost: " + str(total_c))
    #        print(sum(orders))
    return np.array(orders)