CadetCareerProblem – Solution Generation & Algorithms Methods

generate_random_solution(p_dict={}, printing=None)

Generate random solution by assigning cadets to AFSCs that they're eligible for

Source code in afccp/main.py

def generate_random_solution(self, p_dict={}, printing=None):
    """
    Generate random solution by assigning cadets to AFSCs that they're eligible for
    """
    if printing is None:
        printing = self.printing

    if printing:
        print('Generating random solution...')

    # Reset instance model parameters
    self._reset_functional_parameters(p_dict)

    # Generate solution
    solution = {'method': 'Random',
        'j_array': np.array([np.random.choice(self.parameters['J^E'][i]) for i in self.parameters['I']])}

    # Determine what to do with the solution
    self._solution_handling(solution)

    return solution

rotc_rated_board_original(p_dict={}, printing=None)

Source code in afccp/main.py

def rotc_rated_board_original(self, p_dict={}, printing=None):
    if printing is None:
        printing = self.printing

    # Reset instance model parameters
    self._reset_functional_parameters(p_dict)

    # Get the solution we need
    solution = afccp.solutions.algorithms.rotc_rated_board_original(self, printing=printing)

    # Determine what to do with the solution
    self._solution_handling(solution)

    return solution

allocate_ots_candidates_original_method(p_dict={}, printing=None)

Source code in afccp/main.py

def allocate_ots_candidates_original_method(self, p_dict={}, printing=None):
    if printing is None:
        printing = self.printing

    # Reset instance model parameters
    self._reset_functional_parameters(p_dict)

    # Get the solution we need
    solution = afccp.solutions.algorithms.allocate_ots_candidates_original_method(self, printing=printing)

    # Determine what to do with the solution
    self._solution_handling(solution)

    return solution

soc_rated_matching_algorithm(p_dict={}, printing=None)

This is the Hospitals/Residents algorithm that matches or reserves cadets to their Rated AFSCs depending on the source of commissioning (SOCs).

Source code in afccp/main.py

def soc_rated_matching_algorithm(self, p_dict={}, printing=None):
    """
    This is the Hospitals/Residents algorithm that matches or reserves cadets to their Rated AFSCs depending on the
    source of commissioning (SOCs).
    """
    if printing is None:
        printing = self.printing

    # Reset instance model parameters
    self._reset_functional_parameters(p_dict)

    # Get the solution and solution iterations we need
    combined, reserves, matches = afccp.solutions.algorithms.soc_rated_matching_algorithm(
        self, soc=self.mdl_p['soc'], printing=printing)

    # Determine what to do with the solution(s)
    for solution in [reserves, matches, combined]:
        self._solution_handling(solution, printing=False)  # Don't want print updates for this

    return solution

classic_hr(p_dict={}, printing=None)

This method solves the problem instance using the classical "Hospital/Residents" algorithm

Source code in afccp/main.py

def classic_hr(self, p_dict={}, printing=None):
    """
    This method solves the problem instance using the classical "Hospital/Residents" algorithm
    """
    if printing is None:
        printing = self.printing

    # Reset instance model parameters
    self._reset_functional_parameters(p_dict)

    # Get the solution we need
    solution = afccp.solutions.algorithms.classic_hr(self, printing=printing)

    # Determine what to do with the solution
    self._solution_handling(solution)

    return solution