def run(self):
Terminal.print_box(messages = [ f"Neighborhood Function - ENCODING: Can repeat = {self._problem_instance.encoding.can_repeat_elements} - Is Ordered = {self._problem_instance.encoding.is_ordered }" ] )
for _ in range(0, 2):
solution = self._problem_instance.build_solution()
neighbors = self._neighborhood_function( solution = solution, problem = self._problem_instance )
Terminal.print_line( message = f"\nNeighbors of {solution.representation} are:")
for neighbor in neighbors:
print(f" {neighbor.representation} ")
def _build_solution(self):
Terminal.print_box(messages = [f"Build Solution - ENCODING: Can repeat = {self._problem_instance.encoding.can_repeat_elements} - Is Ordered = {self._problem_instance.encoding.is_ordered }"] )
solution = None
for _ in range(0,8):
try:
solution = self._problem_instance.build_solution()
print(f"solution = {solution.representation}")
except:
self._errors.append("Build Solution Failed!")
if solution == None: print(" - Error: Check if build solution is OK or if it was implemented")
def _evaluate(self):
Terminal.print_box(messages = ["Objective Function" ] )
feedback = None
if self._require_feedback:
feedback = self._problem_instance.build_solution()
for _ in range(0,8):
solution = self._problem_instance.build_solution()
self._problem_instance.evaluate_solution( solution = solution , feedback = feedback )
print( f" solution = {solution.representation} | feedback = { feedback.representation } | fitness = {solution.fitness}" )
else:
for _ in range(0,8):
solution = self._problem_instance.build_solution()
self._problem_instance.evaluate_solution( solution = solution )
print( f" solution = {solution.representation} | fitness = {solution.fitness}" )
def run(self):
self._errors = []
Terminal.clear()
Terminal.print_box(messages = ["Name: " + self._problem_instance._name ], font_color=FontColor.Yellow)
try:
print( f" Objective = {self._problem_instance.objective}" )
except:
print( "ERROR: " + self._problem_instance.objective)
self._errors.append()
print( f" Multi-objective = {self._problem_instance.is_multi_objective}" )
print( f" Encoding Rule = {self._problem_instance.encoding_rule }" )
self._build_solution()
self._evaluate()
from lab4.algorithm.hill_climbing import HillClimbing
from lab4.problem.mastermind_problem import MastermindProblem, mastermind_get_neighbors, mastermind_encoding2
from lab4.util.observer import LocalSearcObserver
from lab4.util.terminal import Terminal, FontColor
master_mind_problem = MastermindProblem(encoding_rule=mastermind_encoding2)
secret = master_mind_problem.build_solution()
# Hill Climbing 1 - Classical Stop Condition
hc1 = HillClimbing(problem_instance=master_mind_problem,
neighbohood_function=mastermind_get_neighbors,
params={
"Maximum-Iterations": 10,
"Stop-Conditions": "Alternative-01",
"Target-Fitness": 40
},
feedback=secret)
observer1 = LocalSearcObserver(hc1)
hc1.register_observer(observer1)
hc1.search()
Terminal.print_box(messages=[f"Secret: {secret.representation}"],
font_color=FontColor.Cyan)
def update(self):
state = self._algorithm.get_state()
# {
# "problem" : self._problem_instance,
# "iteration" : self._iteration,
# "message" : message,
# "solution" : self._solution,
# "neighbor" : self._neighbor
# }
message = ""
if "message" in state: message = state["message"]
# started
if message == LocalSearchMessage.Started:
Terminal.clear()
Terminal.print_box(
messages=[self._algorithm.name, self._algorithm.description],
font_color=FontColor.Green)
Terminal.print_box(
messages=["Problem: " + self._algorithm.problem.name],
font_color=FontColor.Yellow)
# initialized
elif message == LocalSearchMessage.Initialized:
Terminal.print_box(messages=["Initialized"])
Terminal.print_line(message="Initial Solution:")
print(
f" Solution: {self._algorithm.solution.representation} - fitness: {self._algorithm.solution.fitness}"
)
Terminal.print_box(messages=["Iterations"])
elif message == LocalSearchMessage.ReplacementAccepted:
iteration = -1
if "iteration" in state:
iteration = state["iteration"]
Terminal.print_line(
message=
f"Iteration {iteration:10d} | Solution: {self._algorithm.solution.representation } | Fitness: {self._algorithm.solution.fitness}"
)
elif message == LocalSearchMessage.ReplacementRejected:
iteration = -1
if "iteration" in state:
iteration = state["iteration"]
Terminal.print_line(
message=
f"Iteration {iteration:10d} | Solution: {self._algorithm.solution.representation } | Fitness: {self._algorithm.solution.fitness} *** (no change)"
)
elif message == LocalSearchMessage.StoppedPrematurely:
Terminal.print_box(messages=["Stopped Prematurely!"],
font_color=FontColor.Yellow)
elif message == LocalSearchMessage.Stopped:
Terminal.print_box(messages=["Stopped Max Iterations!"])
elif message == LocalSearchMessage.StoppedTargetAchieved:
Terminal.print_box(messages=["Stopped Taget Achieved!"],
font_color=FontColor.Green)
from lab4.problem.mastermind_problem import MastermindProblem, mastermind_encoding1, mastermind_encoding2, mastermind_get_neighbors
from lab4.problem.solution import LinearSolution
from lab4.problem.problem_template import ProblemTemplate
from lab4.util.terminal import Terminal, FontColor
# The problem instance must define the
mastermind_problem_instance1 = MastermindProblem()
mastermind_problem_instance2 = MastermindProblem(
encoding_rule=mastermind_encoding2)
Terminal.print_box(messages=["MASTERMIND PROBLEM"])
print(f" Objective = {mastermind_problem_instance1.objective}")
print(f" Multi-objective = {mastermind_problem_instance1.is_multi_objective}")
# -----------------------------------------------------------------------------------------------
# Build Solution Function: build_solution() TESTS
# -----------------------------------------------------------------------------------------------
# Can-Repeat = False - Objetive Function: evaluate_solution() TESTS
# -----------------------------------------------------------------------------------------------
Terminal.print_box(messages=["CanRepeat = False | Build Solution"])
for _ in range(0, 8):
solution = mastermind_problem_instance1.build_solution()
print(f"solution = {solution.representation}")
# Can-Repeat = False - Objetive Function: evaluate_solution() TESTS
# -----------------------------------------------------------------------------------------------
Terminal.print_box(messages=["CanRepeat = False | Build Solution"])
for _ in range(0, 8):
solution = mastermind_problem_instance2.build_solution()
print(f"solution = {solution.representation}")