scikit-mcda 0.0.8

Library for Multi-criteria Decision Aid Methods

A python library made to provide multi-criteria decision aid for developers and operacional researchers.

Module for Decision-making Under Uncertainty (DMUU)

dmuu: Module for Decision-making Under Uncertainty

criteria:

• maximax

• maximin

• laplace

• minimax-regret

• hurwicz

functions:

• dataframe(alt_data, alt_labels=[], state_labels=[])

• calc(dmuu_df, dmuu_criteria_list=[], hurwicz_coeficient=-1)

• decision_making(dmuu_df, dmuu_criteria_list=[], hurwicz_coeficient=-1)

Example

from scikitmcda import dmuu

df = dmuu.dataframe([[5000, 2000, 100],
                     [50, 50, 500]],
                    ["ALT_A", "ALT_B"],
                    ["STATE A", "STATE B", "STATE C"])

df
+----+----------------+-----------+-----------+-----------+
|    | alternatives   |   STATE A |   STATE B |   STATE C |
|----+----------------+-----------+-----------+-----------|
|  0 | ALT_A          |      5000 |      2000 |       100 |
|  1 | ALT_B          |        50 |        50 |       500 |
+----+----------------+-----------+-----------+-----------+

df_calc = dmuu.calc(df, ["minimax-regret", "hurwicz"], 0.7)

df_calc
+----+----------------+-----------+-----------+-----------+------------------+------------------+
|    | alternatives   |   STATE A |   STATE B |   STATE C | minimax-regret   | hurwicz          |
|----+----------------+-----------+-----------+-----------+------------------+------------------|
|  0 | ALT_A          |      5000 |      2000 |       100 | (400, 1)         | (3530.0, 1, 0.7) |
|  1 | ALT_B          |        50 |        50 |       500 | (4950, 0)        | (365.0, 0, 0.7)  |
+----+----------------+-----------+-----------+-----------+------------------+------------------+

result = dmuu.decision_making(df)

result

[{'alternative': 'ALT_A',
  'criteria': 'maximax',
  'hurwicz_coeficient': '',
  'index': 0,
  'result': {'ALT_A': 5000, 'ALT_B': 500},
  'type_dm': 'DMUU',
  'value': 5000},
...
{'alternative': 'ALT_A',
  'criteria': 'hurwicz',
  'hurwicz_coeficient': 0.5,
  'index': 0,
  'result': {'ALT_A': 2550.0, 'ALT_B': 275.0},
  'type_dm': 'DMUU',
  'value': 2550.0}]