def main():
"""Test for the DD classes."""
# import logging
# from pymhlib.demos.common import data_dir
parser = get_settings_parser()
parser.add("--inst_file",
type=str,
default=data_dir + 'mknap-small.txt',
help='problem instance file')
# parser.set_defaults(seed=3)
parse_settings()
init_logger()
logger = logging.getLogger("pymhlib")
logger.info("pymhlib demo for using decision diagrams for the MKP")
logger.info(get_settings_as_str())
instance = MKPInstance(settings.inst_file)
logger.info("MKP instance read:\n%s", str(instance))
# solution = MKPSolution(instance)
# solution.initialize(0)
dd = MKPDecisionDiag(instance)
dd.expand_all('relaxed')
logger.info(dd)
sol = dd.derive_solution()
# sol.check()
logger.info("Solution: %s, obj=%f", sol, sol.obj())
def add_general_arguments_and_parse_settings(
default_inst_file: str = 'inst.dat', args=None, seed: int = 0):
"""Some general parameters are registered and the settings are parsed.
:param seed: optional seed value for the random number generators; 0: random initialization
:param default_inst_file: default instance file to be loaded and solved
"""
parser = get_settings_parser()
parser.add_argument("--alg",
type=str,
default='gvns',
help='optimization algorithm to be used '
'(gvns, alns, pbig, par_alns, ssga, sa)')
parser.add_argument("--inst_file",
type=str,
default=default_inst_file,
help='problem instance file')
parser.add_argument("--meths_ch",
type=int,
default=1,
help='number of construction heuristics to be used')
parser.add_argument("--meths_li",
type=int,
default=1,
help='number of local improvement methods to be used')
parser.add_argument("--meths_sh",
type=int,
default=5,
help='number of shaking methods to be used')
parser.add_argument("--meths_de",
type=int,
default=3,
help='number of destroy methods to be used')
parser.add_argument("--meths_re",
type=int,
default=3,
help='number of repair methods to be used')
parse_settings(args=args, seed=seed)
"""A general variable neighborhood search class which can also be used for plain local search, VND, GRASP, IG etc.
It extends the more general scheduler module/class by distinguishing between construction heuristics, local
improvement methods and shaking methods.
"""
from typing import List
import time
from pymhlib.scheduler import Method, Scheduler
from pymhlib.settings import get_settings_parser
from pymhlib.solution import Solution
parser = get_settings_parser()
class GVNS(Scheduler):
"""A general variable neighborhood search (GVNS).
Attributes
- sol: solution object, in which final result will be returned
- meths_ch: list of construction heuristic methods
- meths_li: list of local improvement methods
- meths_sh: list of shaking methods
"""
def __init__(self,
sol: Solution,
meths_ch: List[Method],
meths_li: List[Method],
meths_sh: List[Method],
own_settings: dict = None,
def run_optimization(problem_name: str, Instance, Solution, default_inst_file: str, own_settings=None, embedded=False, iter_cb=None):
"""Run optimization algorithm given by parameter alg on given problem instance."""
if not embedded:
parser = get_settings_parser()
parser.add("--alg", type=str, default='gvns', help='optimization algorithm to be used '
'(gvns, alns, parallel_alns, ssga)')
parser.add("--inst_file", type=str, default=default_inst_file,
help='problem instance file')
parser.add("--meths_ch", type=int, default=1,
help='number of construction heuristics to be used')
parser.add("--meths_li", type=int, default=1,
help='number of local improvement methods to be used')
parser.add("--meths_sh", type=int, default=5,
help='number of shaking methods to be used')
parser.add("--meths_de", type=int, default=3,
help='number of destroy methods to be used')
parser.add("--meths_re", type=int, default=3,
help='number of repair methods to be used')
# parser.set_defaults(seed=3)
parse_settings()
init_logger()
logger = logging.getLogger("pymhlib")
logger.info(f"pymhlib demo for solving {problem_name}")
logger.info(get_settings_as_str())
instance = Instance(settings.inst_file)
logger.info(f"{problem_name} instance read:\n" + str(instance))
solution = Solution(instance)
# solution.initialize(0)
logger.info(f"Solution: {solution}, obj={solution.obj()}\n")
if settings.alg == 'gvns':
alg = GVNS(solution,
[Method(f"ch{i}", Solution.construct, i) for i in range(settings.meths_ch)],
[Method(f"li{i}", Solution.local_improve, i) for i in range(1, settings.meths_li + 1)],
[Method(f"sh{i}", Solution.shaking, i) for i in range(1, settings.meths_sh + 1)],
own_settings)
elif settings.alg == 'alns':
alg = ALNS(solution,
[Method(f"ch{i}", Solution.construct, i) for i in range(settings.meths_ch)],
[Method(f"de{i}", Solution.destroy, i) for i in range(1, settings.meths_de + 1)],
[Method(f"re{i}", Solution.repair, i) for i in range(1, settings.meths_re + 1)],
own_settings)
elif settings.alg == 'pbig':
alg = PBIG(solution,
[Method(f"ch{i}", Solution.construct, i) for i in range(settings.meths_ch)],
[Method(f"li{i}", Solution.local_improve, i) for i in range(1, settings.meths_li + 1)] +
[Method(f"sh{i}", Solution.shaking, i) for i in range(1, settings.meths_sh + 1)],
own_settings)
elif settings.alg == 'par_alns':
alg = ParallelALNS(solution,
[Method(f"ch{i}", Solution.construct, i) for i in range(settings.meths_ch)],
[Method(f"de{i}", Solution.destroy, i) for i in range(1, settings.meths_de + 1)],
[Method(f"re{i}", Solution.repair, i) for i in range(1, settings.meths_re + 1)],
own_settings)
elif settings.alg == 'ssga':
alg = SteadyStateGeneticAlgorithm(solution,
[Method(f"ch{i}", Solution.construct, i) for i in range(settings.meths_ch)],
Solution.crossover,
Method(f"mu", Solution.shaking, 1),
Method(f"ls", Solution.local_improve, 1),
own_settings)
elif settings.alg == 'sa':
alg = SA(solution,
[Method(f"ch{i}", Solution.construct, i) for i in range(settings.meths_ch)],
Solution.random_move_delta_eval, Solution.apply_neighborhood_move, iter_cb, own_settings)
else:
raise ValueError('Invalid optimization algorithm selected (settings.alg): ', settings.alg)
alg.run()
logger.info("")
alg.method_statistics()
alg.main_results()
