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# PuLP : Python LP Modeler
# Version 2.4
# Copyright (c) 2002-2005, Jean-Sebastien Roy (js@jeannot.org)
# Modifications Copyright (c) 2007- Stuart Anthony Mitchell (s.mitchell@auckland.ac.nz)
# $Id:solvers.py 1791 2008-04-23 22:54:34Z smit023 $
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (the
# "Software"), to deal in the Software without restriction, including
# without limitation the rights to use, copy, modify, merge, publish,
# distribute, sublicense, and/or sell copies of the Software, and to
# permit persons to whom the Software is furnished to do so, subject to
# the following conditions:
# The above copyright notice and this permission notice shall be included
# in all copies or substantial portions of the Software.
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
# OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
# IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
# CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
# TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
# SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."""
# Modified by Sam Mathew (@samiit on Github)
# Users would need to install HiGHS on their machine and provide the path to the executable. Please look at this thread: https://github.com/ERGO-Code/HiGHS/issues/527#issuecomment-894852288
# More instructions on: https://www.highs.dev
from .core import LpSolver_CMD, subprocess, PulpSolverError
import os, sys
from .. import constants
import warnings
class HiGHS_CMD(LpSolver_CMD):
"""The HiGHS_CMD solver"""
name = "HiGHS_CMD"
def __init__(
self,
path=None,
keepFiles=False,
mip=True,
msg=True,
options=None,
timeLimit=None,
):
"""
:param bool mip: if False, assume LP even if integer variables
:param bool msg: if False, no log is shown
:param float timeLimit: maximum time for solver (in seconds)
:param list options: list of additional options to pass to solver
:param bool keepFiles: if True, files are saved in the current directory and not deleted after solving
:param str path: path to the solver binary (you can get binaries for your platform from https://github.com/JuliaBinaryWrappers/HiGHS_jll.jl/releases, or else compile from source - https://highs.dev)
"""
LpSolver_CMD.__init__(
self,
mip=mip,
msg=msg,
timeLimit=timeLimit,
options=options,
path=path,
keepFiles=keepFiles,
)
def defaultPath(self):
return self.executableExtension("highs")
def available(self):
"""True if the solver is available"""
return self.executable(self.path)
def actualSolve(self, lp):
"""Solve a well formulated lp problem"""
if not self.executable(self.path):
raise PulpSolverError("PuLP: cannot execute " + self.path)
tmpMps, tmpSol, tmpOptions, tmpLog = self.create_tmp_files(
lp.name, "mps", "sol", "HiGHS", "HiGHS_log"
)
write_lines = [
"solution_file = %s\n" % tmpSol,
"write_solution_to_file = true\n",
]
with open(tmpOptions, "w") as fp:
fp.writelines(write_lines)
if lp.sense == constants.LpMaximize:
# we swap the objectives
# because it does not handle maximization.
warnings.warn(
"HiGHS_CMD does not currently allow maximization, "
"we will minimize the inverse of the objective function."
)
lp += -lp.objective
lp.checkDuplicateVars()
lp.writeMPS(tmpMps) # , mpsSense=constants.LpMinimize)
# just to report duplicated variables:
try:
os.remove(tmpSol)
except:
pass
cmd = self.path
cmd += " %s" % tmpMps
cmd += " --options_file %s" % tmpOptions
if self.timeLimit is not None:
cmd += " --time_limit %s" % self.timeLimit
for option in self.options:
cmd += " " + option
if lp.isMIP():
if not self.mip:
cmd += " --solver simplex"
# warnings.warn("HiGHS_CMD cannot solve the relaxation of a problem")
if self.msg:
pipe = None
else:
pipe = open(os.devnull, "w")
lp_status = None
with subprocess.Popen(
cmd.split(),
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
universal_newlines=True,
) as proc, open(tmpLog, "w") as log_file:
for line in proc.stdout:
if self.msg:
sys.__stdout__.write(line)
log_file.write(line)
# We need to undo the objective swap before finishing
if lp.sense == constants.LpMaximize:
lp += -lp.objective
# The return code for HiGHS on command line follows: 0:program ran successfully, 1: warning, -1: error - https://github.com/ERGO-Code/HiGHS/issues/527#issuecomment-946575028
return_code = proc.wait()
if return_code in [0, 1]:
with open(tmpLog, "r") as log_file:
content = log_file.readlines()
content = [l.strip().split() for l in content]
# LP
model_line = [l for l in content if l[:2] == ["Model", "status"]]
if len(model_line) > 0:
model_status = " ".join(model_line[0][3:]) # Model status: ...
else:
# ILP
model_line = [l for l in content if "Status" in l][0]
model_status = " ".join(model_line[1:])
sol_line = [l for l in content if l[:2] == ["Solution", "status"]]
sol_line = sol_line[0] if len(sol_line) > 0 else ["Not solved"]
sol_status = sol_line[-1]
if model_status.lower() == "optimal": # optimal
status, status_sol = (
constants.LpStatusOptimal,
constants.LpSolutionOptimal,
)
elif sol_status.lower() == "feasible": # feasible
# Following the PuLP convention
status, status_sol = (
constants.LpStatusOptimal,
constants.LpSolutionIntegerFeasible,
)
elif model_status.lower() == "infeasible": # infeasible
status, status_sol = (
constants.LpStatusInfeasible,
constants.LpSolutionNoSolutionFound,
)
elif model_status.lower() == "unbounded": # unbounded
status, status_sol = (
constants.LpStatusUnbounded,
constants.LpSolutionNoSolutionFound,
)
else:
status = constants.LpStatusUndefined
status_sol = constants.LpSolutionNoSolutionFound
raise PulpSolverError("Pulp: Error while executing", self.path)
if status == constants.LpStatusUndefined:
raise PulpSolverError("Pulp: Error while executing", self.path)
if not os.path.exists(tmpSol) or os.stat(tmpSol).st_size == 0:
status_sol = constants.LpSolutionNoSolutionFound
values = None
elif status_sol == constants.LpSolutionNoSolutionFound:
values = None
else:
values = self.readsol(lp.variables(), tmpSol)
self.delete_tmp_files(tmpMps, tmpSol, tmpOptions, tmpLog)
lp.assignStatus(status, status_sol)
if status == constants.LpStatusOptimal:
lp.assignVarsVals(values)
return status
@staticmethod
def readsol(variables, filename):
"""Read a HiGHS solution file"""
with open(filename) as f:
content = f.readlines()
content = [l.strip() for l in content]
values = {}
if not len(content): # if file is empty, update the status_sol
return None
# extract everything between the line Columns and Rows
col_id = [i for i, line in enumerate(content) if "Columns" in line][0]
row_id = [i for i, line in enumerate(content) if "Rows" in line][0]
solution = content[col_id + 1 : row_id]
for line in solution:
var, value = line.split()
values[var] = float(value)
return values
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