"""Tests for assignment problem parser."""
import pytest
from crew_optimizer.solvers.lp.assignment_parser import parse_assignment_problem
from crew_optimizer.solvers.lp.simplex import solve_lp
from crew_optimizer.schemas import SolveOptions
def test_assignment_problem_small():
"""Test assignment problem with small dataset."""
energy_csv = """job,Machine 1,Machine 2
1,10,20
2,15,25"""
capacity_csv = """machine,capacity
1,1
2,1"""
model = parse_assignment_problem(
energy_file_content=energy_csv,
capacity_file_content=capacity_csv,
)
assert model.sense == "min"
assert len(model.variables) == 4 # 2 jobs × 2 machines
assert len(model.constraints) == 4 # 2 job constraints + 2 capacity constraints
# Check that each job has a constraint summing to 1
job_constraints = [c for c in model.constraints if "job" in c.name]
assert len(job_constraints) == 2
for constraint in job_constraints:
assert constraint.cmp == "=="
assert constraint.rhs == 1.0
# Check capacity constraints
capacity_constraints = [c for c in model.constraints if "capacity" in c.name]
assert len(capacity_constraints) == 2
for constraint in capacity_constraints:
assert constraint.cmp == "<="
assert constraint.rhs == 1.0
def test_assignment_problem_solve():
"""Test solving a small assignment problem."""
energy_csv = """job,Machine 1,Machine 2
1,10,20
2,15,25"""
capacity_csv = """machine,capacity
1,1
2,1"""
model = parse_assignment_problem(
energy_file_content=energy_csv,
capacity_file_content=capacity_csv,
)
solution = solve_lp(model, SolveOptions())
assert solution.status == "optimal"
assert solution.objective_value is not None
assert solution.x is not None
# Check that each job is fully assigned
job1_vars = {k: v for k, v in solution.x.items() if k.startswith("x_1_")}
job2_vars = {k: v for k, v in solution.x.items() if k.startswith("x_2_")}
job1_total = sum(job1_vars.values())
job2_total = sum(job2_vars.values())
assert abs(job1_total - 1.0) < 1e-6
assert abs(job2_total - 1.0) < 1e-6
