`demand_source` Module¶

Overview¶

This module contains the DemandSource class. A DemandSource object represents external demand observed by a node. The demand can be random or deterministic. Attributes specify the type of demand distribution and its parameters. The object can generate demands from the specified distribution.

Note

The notation and references (equations, sections, examples, etc.) used below refer to Snyder and Shen, Fundamentals of Supply Chain Theory (FoSCT), 2nd edition (2019).

Example: Create a DemandSource object representing demand that has a normal distribution with a mean of 50 and a standard deviation of 10. Generate a random demand from the distribution.

>>> ds = DemandSource(type='N', mean=50, standard_deviation=10)
>>> ds.generate_demand()        
46.75370030596123
>>> # Tell object to round demands to integers.
>>> ds.round_to_int = True
>>> ds.generate_demand()        
63

API Reference¶

class DemandSource(**kwargs)[source]¶

A DemandSource object represents external demand observed by a node. The demand can be random or deterministic. Attributes specify the type of demand distribution and its parameters. The object can generate demands from the specified distribution.

Parameters: **kwargs – Keyword arguments specifying values of one or more attributes of the DemandSource, e.g., type='N'.

type¶

The demand type, as a string. Currently supported strings are:

None

‘N’ (normal)

‘P’ (Poisson)

‘UD’ (uniform discrete)

‘UC’ (uniform continuous)

‘D’ (deterministic)

‘CD’ (custom discrete)

Type: str

round_to_int¶

Round demand to nearest integer?

Type: bool

mean¶

Mean of demand per period. Required if type == ‘N’ or ‘P’. [\(\mu\)]

Type: float, optional

standard_deviation¶

Standard deviation of demand per period. Required if type == ‘N’. [\(\sigma\)]

Type: float, optional

demand_list¶

List of demands, one per period (for deterministic demand types), or list of possible demand values (for custom discrete demand types). For deterministic demand types, if demand is required in a period beyond the length of the list, the list is restarted at the beginning. This also allows demand_list to be a singleton, in which case it is used in every period. Required if type == ‘D’ or ‘CD’. [\(d\)]

Type: list, optional

probabilities¶

List of probabilities of each demand value (for custom discrete demand types). Required if type == ‘CD’.

Type: list, optional

lo¶

Low value of demand range (for uniform demand types). Required if type == ‘UD’ or ‘UC’.

Type: float, optional

hi¶

High value of demand range (for uniform demand types). Required if type == ‘UD’ or ‘UC’.

Type: float, optional

property demand_distribution¶: Demand distribution, as a scipy.stats.rv_continuous or scipy.stats.rv_discrete object. Read only.

initialize()[source]¶: Initialize the parameters in the object to their default values.

validate_parameters()[source]¶: Check that appropriate parameters have been provided for the given demand type. Raise an exception if not.

to_dict()[source]¶

Convert the DemandSource object to a dict. List attributes (demand_list, probabilities) are deep-copied so changes to the original object do not get propagated to the dict.

Returns: The dict representation of the object.
Return type: dict

classmethod from_dict(the_dict)[source]¶

Return a new DemandSource object with attributes copied from the values in the_dict. List attributes (demand_list, probabilities) are deep-copied so changes to the original dict do not get propagated to the object. Any missing attributes are set to their default values.

Parameters: the_dict (dict) – Dict representation of a DemandSource, typically created using to_dict().
Returns: The object converted from the dict.
Return type: DemandSource

generate_demand(period=None)[source]¶

Generate a demand value using the demand type specified in type. If type is None, returns None.

Parameters: period (int, optional) – The period to generate a demand value for. If type = ‘D’ (deterministic), this is required if demand_list is a list of demands, one per period. If omitted, will return first (or only) demand in list.
Returns: demand – The demand value.
Return type: float

cdf(x)[source]¶

Cumulative distribution function of demand distribution.

In some cases, this is just a wrapper around cdf() function of scipy.stats.rv_continuous or scipy.stats.rv_discrete object.

Parameters: x (float) – Value to calculate cdf for.
Returns: F – cdf of x.
Return type: float

lead_time_demand_distribution(lead_time)[source]¶

Return lead-time demand distribution, as a scipy.stats.rv_continuous or scipy.stats.rv_discrete object.

Note

For ‘UC’, ‘UD’, and ‘CD’ demands, this method calculates the lead-time demand distribution as the sum of lead_time independent random variables. Therefore, the method requires lead_time to be an integer for these distributions. If it is not, it raises a ValueError.

Parameters: lead_time (float or int) – The lead time. [\(L\)]
Returns: distribution – The lead-time demand distribution object.
Return type: rv_continuous or rv_discrete
Raises: ValueError – If type is ‘UC’, ‘UD’, or ‘CD’ and lead_time is not an integer.

demand_source Module¶

Overview¶

API Reference¶

`demand_source` Module¶