elpee.StandardProblem

Class to represent the standardized linear programming optimization Problem to be solved

Import

from elpee import StandardProblem

Methods

__init__(matrix: List[List[int]], basic_vars: List[int], n_decision_vars: int, is_max: bool = True, n_artificials: int = 0, var_name_list: List[str] = None)

Initializes a elpee.StandardProblem designed for computational purposes to be solved.

Parameters

• matrixList [ List [ int ]]

  The simplex matrix representation of the LinearProblem

• basic_varsList [ int ]

  The ordered list of indices mapped to the basic variables in the Linear Problem

• n_decision_varsint

  The number of decision variables in the Linear Problem

• is_maxint [default = True]

  Sets a maximization LP problem when True. Else sets a minimization problem when False.

• n_artificialsint [default = 0]

  The number of artificial variables used to set up the simplex matrix representation

• var_name_listList [ str ] [Optional] [default = None]

  The names / symbols of all decision variables

interpret

Obtain a dictionary of variables and values corresponding to the generated elpee.StandardProblem

Returns

Dictionary containing the following keys - Sol : The value of the objective function - All basic variables & Decision variables

# sample dictionary output
{
    'Sol' : optimal_value,
    'Decision_var_1' : x1_value,
    'Decision_var_2' : x2_value,
    'Slack_1' : S1_value,
    'Slack_2' : S2_value,
    'Artificial_1' : A1_value
}
# Only non-zero slack and artificial variable values will be provided

Example Code

standard_problem.interpret()

# Example Output
# {'Sol': 25.0, 'x': 5.0, 'y': 0, 'Slack_2': 22.0, 'Slack_3': 18.0}