def test_case_3(self):
# prepare raw problem
variables = [0, 1, 2, 3]
objectives = [{0: -10, 1: -5, 2: -1, 3: -5}, {0: 3, 1: 2, 2: 3, 3: 0}]
constraints = dict()
# prepare solvers
for solver_name in self.binary_solver:
if solver_name == 'epsilon':
problem = NextReleaseProblem.MOIP( \
variables, objectives, constraints, \
dict(), dict() \
)
else:
constraints = JNRP.regularize_constraints(
constraints, len(variables))
problem = JNRP(variables, objectives, constraints)
solver = Solver(solver_name)
# prepare and solve
solver.load(problem)
solver.execute()
# get the solutions
solutions = solver.solutions()
print(solver_name + '\t\t' + str(len(solutions)))
self.display(solutions, 5)
def test_case_2(self):
# prepare raw problem
variables = [0, 1, 2, 3]
objectives = [{0: -10, 1: -5, 2: -1, 3: 5}]
constraints = [{2: 1, 4: 0}, {0: 1, 3: -1, 4: 0}]
# prepare solvers
for solver_name in self.single_solver:
if solver_name == 'single':
problem = NextReleaseProblem.MOIP( \
variables, objectives, constraints, \
['L' for _ in range(len(constraints))], dict() \
)
else:
constraints = JNRP.regularize_constraints(
constraints, len(variables))
problem = JNRP(variables, objectives, constraints)
solver = Solver(solver_name)
# prepare and solve
solver.load(problem)
solver.execute()
# get the solutions
solutions = solver.solutions()
print(solver_name + '\t\t' + str(len(solutions)))
self.display(solutions, 5)
def __to_bi_general_form(self) -> ProblemType:
# only for classic and realistic
assert self.__project.startswith('classic') or self.__project.startswith('realistic')
# requirement dependencies should be eliminated
assert not self.__dependencies
# modelling
variables, objectives, inequations, inequations_operators, equations = \
self.__basic_bi_form()
# construct Problem
if self.__problem_type == 'default':
return NextReleaseProblem.MOIP(variables, objectives, inequations, inequations_operators, equations)
elif self.__problem_type == 'jmetal':
file_name = self.__project + '_' + 'binary.json'
NextReleaseProblem.dump(file_name, variables, objectives, inequations)
return JNRP(variables, objectives, inequations)
else:
assert False
def __to_tri_max_customers_form(self) -> ProblemType:
# only for classic and realistic
assert self.__project.startswith('classic') or self.__project.startswith('realistic')
# requirement dependencies should be eliminated
assert not self.__dependencies
# modelling with bi-objective
variables, objectives, inequations, inequations_operators, equations = \
self.__basic_bi_form()
# add the third objective, max customers <=> min -customers
max_customers = {k:-1 for k in self.__profit}
objectives.append(max_customers)
# construct Problem
if self.__problem_type == 'default':
return NextReleaseProblem.MOIP(variables, objectives, inequations, inequations_operators, equations)
elif self.__problem_type == 'jmetal':
file_name = self.__project + '_' + 'tricus.json'
NextReleaseProblem.dump(file_name, variables, objectives, inequations)
return JNRP(variables, objectives, inequations)
else:
assert False
def __to_bicst_form(self,
max_cost : Union[int, float] = None, \
min_profit : Union[int, float] = None, \
min_requirements : int = None, \
min_customers : int = None\
) -> ProblemType:
# only for classic and realistic
assert self.__project.startswith('classic') or self.__project.startswith('realistic')
# requirement dependencies should be eliminated
assert not self.__dependencies
# modelling
variables, objectives, inequations, inequations_operators, equations = \
self.__basic_bi_form()
# add additional constraints
constant_id = len(variables)
if max_cost: # sum cost <= max_cost
inequation = {k:v for k, v in self.__cost.items()}
if isinstance(max_cost, int):
inequation[constant_id] = max_cost
else:
print('max cost: ', ceil(max_cost*sum(list(self.__cost.values()))))
inequation[constant_id] = ceil(max_cost*sum(list(self.__cost.values())))
inequations.append(inequation)
inequations_operators.append('L')
if min_profit: # sum profit >= min_profit
# -p1 -p2 - ... <= - min_profit
inequation = {k:-v for k, v in self.__profit.items()}
if isinstance(min_profit, int):
inequation[constant_id] = - min_profit
else:
print('min profit: ', floor(min_profit*sum(list(self.__profit.values()))))
inequation[constant_id] = - floor(min_profit*sum(list(self.__profit.values())))
inequations.append(inequation)
inequations_operators.append('L')
if min_requirements: # |requirements| >= min_requirements
inequation = {k:-1 for k in self.__cost}
if isinstance(min_requirements, int):
inequation[constant_id] = - min_requirements
else:
print('min requirements: ', floor(min_requirements*len(self.__cost)))
inequation[constant_id] = - floor(min_requirements*len(self.__cost))
inequations.append(inequation)
inequations_operators.append('L')
if min_customers: # |customers| >= min_customers
inequation = {k:-1 for k in self.__profit}
if isinstance(min_customers, int):
inequation[constant_id] = - min_customers
else:
print('min customers: ', floor(min_customers*len(self.__profit)))
inequation[constant_id] = - floor(min_customers*len(self.__profit))
inequations.append(inequation)
inequations_operators.append('L')
# construct Problem
if self.__problem_type == 'default':
return NextReleaseProblem.MOIP(variables, objectives, inequations, inequations_operators, equations)
elif self.__problem_type == 'jmetal':
file_name = self.__project + '_' + 'bicst.json'
NextReleaseProblem.dump(file_name, variables, objectives, inequations)
return JNRP(variables, objectives, inequations)
else:
assert False