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combination based bundle solving

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spushy
2022-02-09 01:13:49 -05:00
parent 744abbb7b8
commit 8ce5e6e540
4 changed files with 139 additions and 74 deletions
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123
app/services/loft_service.py
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@ -9,6 +9,7 @@ from models.solver_run import SolverRun
from models.solution import Solution
from models.form import Form
from models.item import Item
from models.bundle import Bundle
from services.base import Base
@ -25,7 +26,7 @@ class LoftService(Base):
logging.error(error)
self.result = self.stream_to_s3_bucket(ItemGenerationError("Provided params causing error in calculation results"))
def create_solver_run_from_attributes(self):
def create_solver_run_from_attributes(self) -> SolverRun:
logging.info('Retrieving attributes from message...')
# get s3 object
self.key = aws_helper.get_key_from_message(self.source)
@ -52,67 +53,95 @@ class LoftService(Base):
return solver_run
def generate_solution(self):
# unsolved solution
solution = Solution(
response_id=random.randint(100, 5000),
forms=[]
)
def generate_solution(self) -> Solution:
logging.info('Generating Solution...')
# counter for number of forms
f = 0
# setup vars
items = LpVariable.dicts(
"Item", [item.id for item in self.solver_run.items], lowBound=1, upBound=1, cat='Binary')
# check if problem request has bundles
bundle_constraint = self.solver_run.get_constraint_by_type('bundle')
# iterate for number of forms that require creation
# currently creates distinc forms with no item overlap
while f < self.solver_run.total_forms:
# setup vars
items = LpVariable.dicts(
"Item", [item.id for item in self.solver_run.items], lowBound=1, upBound=1, cat='Binary')
bundles = LpVariable.dicts(
"Bundle", [bundle.id for bundle in self.solver_run.bundles], lowBound=1, upBound=1, cat='Binary')
# unsolved solution
solution = Solution(
response_id=random.randint(100, 5000),
forms=[]
)
# initiate problem
problem = None
count = 0
if bundle_constraint:
# generate valid bundle combinations
bundle_combinations = solver_helper.valid_bundle_combinations(
self.solver_run.total_form_items,
int(bundle_constraint.maximum),
int(bundle_constraint.minimum),
self.solver_run.bundles)
problem_objection_functions = []
# create problem
problem = LpProblem("ata-form-generate", LpMinimize)
# dummy objective function, because it just makes things easier™
problem += lpSum([items[item.id]
for item in self.solver_run.items])
# constraints
problem += lpSum([items[item.id]
for item in self.solver_run.items]) == self.solver_run.total_form_items, 'Total form items'
# dynamic constraints
problem = solver_helper.build_constraints(self.solver_run, problem, items, bundles)
# multi-objective constraints
for target in self.solver_run.objective_function.tif_targets:
problem += lpSum([item.iif(self.solver_run, target.theta)*items[item.id]
for item in self.solver_run.items]) >= target.value - 8, f'max tif theta ({target.theta}) target value {target.value}'
problem += lpSum([item.iif(self.solver_run, target.theta)*items[item.id]
for item in self.solver_run.items]) <= target.value + 8, f'min tif theta ({target.theta}) target value {target.value}'
for target in self.solver_run.objective_function.tcc_targets:
problem += lpSum([item.irf(self.solver_run, target.theta)*items[item.id]
for item in self.solver_run.items]) >= target.value - 20, f'max tcc theta ({target.theta}) target value {target.value}'
problem += lpSum([item.irf(self.solver_run, target.theta)*items[item.id]
for item in self.solver_run.items]) <= target.value + 20, f'min tcc theta ({target.theta}) target value {target.value}'
# solve problem
problem.solve()
# scramble bundle_combinations to ensure distinctiveness for each form generated
random.shuffle(bundle_combinations)
for bundles in bundle_combinations:
problem = self.solve_problem(items, bundles)
# if optimal solution found, break loop
if LpStatus[problem.status] == 'Optimal':
break
else: # no bundles
problem = self.solve_problem(items)
# successfull form, increment and exit out of loop
f += 1
# add return items and create as a form
form_items = service_helper.solution_items(problem.variables(), self.solver_run)
# add form to solution
solution.forms.append(Form.create(form_items, self.solver_run, LpStatus[problem.status]))
# successfull form, increment
f += 1
return solution
def solve_problem(self, items: list[Item], bundles: list[Bundle] or None = None) -> LpProblem:
# create problem
problem = LpProblem("ata-form-generate", LpMinimize)
# dummy objective function, because it just makes things easier™
problem += lpSum([items[item.id]
for item in self.solver_run.items])
# constraints
problem += lpSum([items[item.id]
for item in self.solver_run.items]) == self.solver_run.total_form_items, 'Total form items'
# dynamic constraints
problem = solver_helper.build_constraints(self.solver_run, problem, items, bundles)
# multi-objective constraints
for target in self.solver_run.objective_function.tif_targets:
problem += lpSum([item.iif(self.solver_run, target.theta)*items[item.id]
for item in self.solver_run.items]) >= target.value - 8, f'max tif theta ({target.theta}) target value {target.value}'
problem += lpSum([item.iif(self.solver_run, target.theta)*items[item.id]
for item in self.solver_run.items]) <= target.value + 8, f'min tif theta ({target.theta}) target value {target.value}'
for target in self.solver_run.objective_function.tcc_targets:
problem += lpSum([item.irf(self.solver_run, target.theta)*items[item.id]
for item in self.solver_run.items]) >= target.value - 20, f'max tcc theta ({target.theta}) target value {target.value}'
problem += lpSum([item.irf(self.solver_run, target.theta)*items[item.id]
for item in self.solver_run.items]) <= target.value + 20, f'min tcc theta ({target.theta}) target value {target.value}'
# solve problem
problem.solve()
return problem
return solution
def stream_to_s3_bucket(self, error = None):
self.file_name = f'{service_helper.key_to_uuid(self.key)}.csv'