allagash.problem module

Problem

class allagash.problem.Problem(pulp_problem, coverages, problem_type)

A representation of the linear programming problem that can be solved. This is not intended to be created on it’s own but rather from one of the factory methods lscp() or mclp()

Problem.lscp(coverage)
Problem.lscp([coverage1, coverage2])

Parameters:

pulp_problem (LpProblem) – The pulp problem that will be solved
coverages (list[Coverage]) – The coverages that were used to build the problem
problem_type (str) – The type of problem that was generated

classmethod bclp(coverages, max_supply)

Creates a new Problem object representing the Backup Covering Location Problem

Parameters:

coverages (list[Coverage]) – The coverages to be used to create the problem
max_supply (dict[Coverage,int]) – The maximum number of supply locations to allow

Returns:

The created problem

Return type:

Problem

property coverages

Returns:: The coverage used to create the problem
Return type:: list[Coverage]

classmethod lscp(coverages)

Creates a new Problem object representing the Location Covering Set Problem

Parameters:: coverages (list[Coverage]) – The coverages to be used to create the problem
Returns:: The created problem
Return type:: Problem

classmethod mclp(coverages, max_supply)

Creates a new Problem object representing the Maximum Covering Location Problem

Parameters:

coverages (list[Coverage]) – The coverages to be used to create the problem
max_supply (dict[Coverage,int]) – The maximum number of supply locations to allow

Returns:

The created problem

Return type:

Problem

property problem_type

Returns:: The type of problem that this is
Return type:: str

property pulp_problem

Returns:: The pulp problem
Return type:: LpProblem

selected_demand(coverage)

Gets the list of the demand locations that were selected when the optimization problem was solved.

Parameters:: coverage (Coverage) – The coverage that the demand locations may be found in. If multiple coverages were used that have the same demand, locations covered by any other coverages will also be returned.
Returns:: The list of location ids of the covered locations
Return type:: list

selected_supply(coverage, operation=<built-in function eq>, value=1)

Gets the list of the supply locations that were selected when the optimization problem was solved.

Parameters:

coverage (Coverage) – The coverage that selected locations may be found in.
operation (function) – The operation to use when determining whether a location was selected
value (int) – The value to apply the operation to

Returns:

The list of location ids of the selected locations

Return type:

list

solve(solver)

Parameters:: solver (LpSolver) – The solver to use for this problem
Returns:: The solution for this problem
Return type:: Problem

InfeasibleException

class allagash.problem.NotSolvedException(message)

An exception indicating the problem was not solved

Parameters:: message (str) – A descriptive message about the exception

with_traceback(): Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.

NotSolvedException

class allagash.problem.InfeasibleException(message)

An exception indicating the problem as an infeasible solution

Parameters:: message (str) – A descriptive message about the exception

with_traceback(): Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.

UnboundedException

class allagash.problem.UnboundedException(message)

An exception indicating the solution is unbounded

Parameters:: message (str) – A descriptive message about the exception

with_traceback(): Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.

UndefinedException

class allagash.problem.UndefinedException(message)

An exception indicating the problem was not solved for an undefined reason

Parameters:: message (str) – A descriptive message about the exception

with_traceback(): Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.