FA-67371 / Elevator dispatch scheduling / Open access

Destination dispatch allocation: tie-break · case 01

Equal-cost allocations go to the highest car id.

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ROOT CAUSE

Later cars win ties.

VERIFIED REPAIR

Keep the first (lowest id) car on equal cost.

Unsuccessful approach: Breaking ties by load contradicts the lowest-id rule.

Case contract

Requests (destination, group size) are allocated one by one. A car is eligible if load + group size <= capacity. Cost = ready time + per_stop_s * existing stops + stop_penalty_s if the destination is not already a stop. The lowest cost wins, ties to the lowest car id. The chosen car adds the destination to its stops and the group to its load. None if no car is eligible.

Why this case matters

Lift group controllers make these decisions many times per minute; a wrong answer strands passengers, wastes trips or overrides a safety rule.

1 / The failure

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(x):
    cars = {c['id']: {'ready': c['ready_s'], 'stops': set(c['stops']), 'load': c['load'], 'cap': c['cap']} for c in x['cars']}
    out = []
    for req in x['requests']:
        best = None
        for cid in sorted(cars):
            c = cars[cid]
            if c['load'] + req['n'] > c['cap']:
                continue
            new_stop = 0 if req['dest'] in c['stops'] else 1
            cost = c['ready'] + x['per_stop_s'] * len(c['stops']) + x['stop_penalty_s'] * new_stop
            if best is None or cost <= best[0]:
                best = (cost, cid)
        if best is None:
            out.append(None)
            continue
        c = cars[best[1]]
        c['stops'].add(req['dest'])
        c['load'] += req['n']
        out.append(best[1])
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: equal cost cars', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 4, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('sampled regression 7', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [11, 6], 'load': 8, 'cap': 13}, {'id': 'B', 'ready_s': 20, 'stops': [7], 'load': 8, 'cap': 12}, {'id': 'C', 'ready_s': 10, 'stops': [5], 'load': 0, 'cap': 12}], 'requests': [{'dest': 2, 'n': 1}, {'dest': 8, 'n': 5}, {'dest': 11, 'n': 3}, {'dest': 3, 'n': 1}], 'stop_penalty_s': 15, 'per_stop_s': 5}, ['A', 'C', 'A', 'A']), ('sampled regression 10', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [5], 'load': 0, 'cap': 12}], 'requests': [{'dest': 12, 'n': 1}, {'dest': 8, 'n': 3}], 'stop_penalty_s': 15, 'per_stop_s': 5}, ['A', 'B']), ('boundary: group exactly fills the car', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [], 'load': 10, 'cap': 12}, {'id': 'B', 'ready_s': 30, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 5, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('boundary: coincident destination beats an idle car', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 0, 'stops': [7], 'load': 0, 'cap': 12}], 'requests': [{'dest': 7, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['B']), ('control 1', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [10, 11], 'load': 8, 'cap': 13}, {'id': 'B', 'ready_s': 20, 'stops': [9], 'load': 11, 'cap': 12}, {'id': 'C', 'ready_s': 0, 'stops': [13, 14, 2], 'load': 11, 'cap': 13}], 'requests': [{'dest': 10, 'n': 1}, {'dest': 9, 'n': 5}], 'stop_penalty_s': 10, 'per_stop_s': 3}, ['A', None]), ('control 4', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [], 'load': 11, 'cap': 12}, {'id': 'B', 'ready_s': 10, 'stops': [3], 'load': 4, 'cap': 12}, {'id': 'C', 'ready_s': 5, 'stops': [], 'load': 11, 'cap': 13}], 'requests': [{'dest': 7, 'n': 2}, {'dest': 3, 'n': 1}, {'dest': 8, 'n': 1}, {'dest': 3, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['C', 'B', 'A', 'B']), ('sampled regression 13', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [3], 'load': 0, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [2, 11, 7], 'load': 8, 'cap': 13}, {'id': 'C', 'ready_s': 20, 'stops': [6], 'load': 0, 'cap': 12}], 'requests': [{'dest': 9, 'n': 3}, {'dest': 14, 'n': 5}, {'dest': 14, 'n': 1}, {'dest': 3, 'n': 1}, {'dest': 9, 'n': 5}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['A', 'A', 'A', 'A', 'B'])], [('regression: equal cost cars', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 4, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('sampled regression 10', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [5], 'load': 0, 'cap': 12}], 'requests': [{'dest': 12, 'n': 1}, {'dest': 8, 'n': 3}], 'stop_penalty_s': 15, 'per_stop_s': 5}, ['A', 'B']), ('sampled regression 22', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [7, 5, 11], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 10, 'stops': [], 'load': 8, 'cap': 13}, {'id': 'C', 'ready_s': 0, 'stops': [10, 8], 'load': 0, 'cap': 13}], 'requests': [{'dest': 12, 'n': 2}, {'dest': 11, 'n': 5}, {'dest': 13, 'n': 2}, {'dest': 13, 'n': 1}, {'dest': 7, 'n': 5}], 'stop_penalty_s': 8, 'per_stop_s': 3}, ['C', 'A', 'A', 'A', 'C']), ('sampled regression 27', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [12, 6, 13], 'load': 0, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [6, 14, 5], 'load': 8, 'cap': 12}, {'id': 'C', 'ready_s': 20, 'stops': [], 'load': 4, 'cap': 12}], 'requests': [{'dest': 12, 'n': 3}, {'dest': 2, 'n': 2}, {'dest': 8, 'n': 5}, {'dest': 11, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['C', 'B', 'C', 'B']), ('boundary: empty car earns no discount', {'cars': [{'id': 'A', 'ready_s': 4, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 0, 'stops': [9], 'load': 0, 'cap': 12}], 'requests': [{'dest': 3, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('control 12', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [6, 3], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 20, 'stops': [], 'load': 4, 'cap': 12}, {'id': 'C', 'ready_s': 20, 'stops': [10, 8], 'load': 11, 'cap': 13}], 'requests': [{'dest': 10, 'n': 1}, {'dest': 2, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 3}, ['A', 'A']), ('sampled regression 15', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [3], 'load': 0, 'cap': 13}, {'id': 'B', 'ready_s': 5, 'stops': [7, 2], 'load': 0, 'cap': 13}, {'id': 'C', 'ready_s': 5, 'stops': [12], 'load': 0, 'cap': 12}], 'requests': [{'dest': 2, 'n': 3}, {'dest': 13, 'n': 5}, {'dest': 11, 'n': 1}, {'dest': 2, 'n': 1}, {'dest': 12, 'n': 3}], 'stop_penalty_s': 8, 'per_stop_s': 3}, ['B', 'A', 'C', 'B', 'C']), ('sampled regression 18', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 20, 'stops': [2, 7, 5], 'load': 0, 'cap': 12}], 'requests': [{'dest': 10, 'n': 5}, {'dest': 2, 'n': 1}, {'dest': 6, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A', 'A', 'A'])], [('regression: equal cost cars', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 4, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('sampled regression 13', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [3], 'load': 0, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [2, 11, 7], 'load': 8, 'cap': 13}, {'id': 'C', 'ready_s': 20, 'stops': [6], 'load': 0, 'cap': 12}], 'requests': [{'dest': 9, 'n': 3}, {'dest': 14, 'n': 5}, {'dest': 14, 'n': 1}, {'dest': 3, 'n': 1}, {'dest': 9, 'n': 5}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['A', 'A', 'A', 'A', 'B']), ('sampled regression 34', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [8], 'load': 8, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [2], 'load': 0, 'cap': 12}], 'requests': [{'dest': 6, 'n': 1}, {'dest': 11, 'n': 3}, {'dest': 5, 'n': 1}, {'dest': 9, 'n': 1}, {'dest': 10, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['B', 'B', 'A', 'B', 'A']), ('sampled regression 58', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [12, 2, 9], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [5, 13], 'load': 4, 'cap': 13}, {'id': 'C', 'ready_s': 5, 'stops': [5, 11], 'load': 0, 'cap': 12}], 'requests': [{'dest': 10, 'n': 3}, {'dest': 13, 'n': 2}, {'dest': 4, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 3}, ['B', 'B', 'C']), ('boundary: second group sees the first allocation', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 2, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 6, 'n': 3}, {'dest': 6, 'n': 3}, {'dest': 6, 'n': 3}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A', 'A', 'A']), ('sampled regression 23', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [2], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 20, 'stops': [9, 8], 'load': 4, 'cap': 13}, {'id': 'C', 'ready_s': 10, 'stops': [], 'load': 0, 'cap': 13}], 'requests': [{'dest': 8, 'n': 3}, {'dest': 13, 'n': 1}, {'dest': 9, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['C', 'C', 'B']), ('control 26', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [9], 'load': 8, 'cap': 12}, {'id': 'B', 'ready_s': 10, 'stops': [11, 14, 4], 'load': 8, 'cap': 13}], 'requests': [{'dest': 13, 'n': 1}, {'dest': 5, 'n': 1}, {'dest': 12, 'n': 1}, {'dest': 9, 'n': 1}, {'dest': 7, 'n': 3}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A', 'A', 'A', 'A', 'B']), ('sampled regression 29', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [], 'load': 0, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [2, 5, 7], 'load': 8, 'cap': 13}, {'id': 'C', 'ready_s': 20, 'stops': [2], 'load': 4, 'cap': 12}], 'requests': [{'dest': 6, 'n': 1}, {'dest': 3, 'n': 5}], 'stop_penalty_s': 15, 'per_stop_s': 5}, ['A', 'A'])], [('regression: equal cost cars', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 4, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('sampled regression 18', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 20, 'stops': [2, 7, 5], 'load': 0, 'cap': 12}], 'requests': [{'dest': 10, 'n': 5}, {'dest': 2, 'n': 1}, {'dest': 6, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A', 'A', 'A']), ('sampled regression 59', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [6], 'load': 11, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [8, 13, 14], 'load': 4, 'cap': 13}], 'requests': [{'dest': 7, 'n': 1}, {'dest': 4, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['B', 'A']), ('sampled regression 10', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [5], 'load': 0, 'cap': 12}], 'requests': [{'dest': 12, 'n': 1}, {'dest': 8, 'n': 3}], 'stop_penalty_s': 15, 'per_stop_s': 5}, ['A', 'B']), ('boundary: no eligible car', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [], 'load': 11, 'cap': 12}], 'requests': [{'dest': 5, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 5}, [None]), ('sampled regression 34', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [8], 'load': 8, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [2], 'load': 0, 'cap': 12}], 'requests': [{'dest': 6, 'n': 1}, {'dest': 11, 'n': 3}, {'dest': 5, 'n': 1}, {'dest': 9, 'n': 1}, {'dest': 10, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['B', 'B', 'A', 'B', 'A']), ('control 37', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [], 'load': 8, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [9, 14, 8], 'load': 8, 'cap': 12}], 'requests': [{'dest': 5, 'n': 1}, {'dest': 8, 'n': 1}, {'dest': 2, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A', 'B', 'A']), ('control 40', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [], 'load': 4, 'cap': 13}, {'id': 'B', 'ready_s': 0, 'stops': [10, 5, 7], 'load': 0, 'cap': 12}], 'requests': [{'dest': 5, 'n': 5}, {'dest': 5, 'n': 5}, {'dest': 7, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['A', 'B', 'A'])], [('regression: equal cost cars', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 4, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('sampled regression 22', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [7, 5, 11], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 10, 'stops': [], 'load': 8, 'cap': 13}, {'id': 'C', 'ready_s': 0, 'stops': [10, 8], 'load': 0, 'cap': 13}], 'requests': [{'dest': 12, 'n': 2}, {'dest': 11, 'n': 5}, {'dest': 13, 'n': 2}, {'dest': 13, 'n': 1}, {'dest': 7, 'n': 5}], 'stop_penalty_s': 8, 'per_stop_s': 3}, ['C', 'A', 'A', 'A', 'C']), ('sampled regression 5', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [3, 6, 5], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 0, 'stops': [2, 3], 'load': 8, 'cap': 12}, {'id': 'C', 'ready_s': 5, 'stops': [], 'load': 4, 'cap': 12}], 'requests': [{'dest': 2, 'n': 5}, {'dest': 9, 'n': 1}, {'dest': 3, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['C', 'B', 'B']), ('sampled regression 27', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [12, 6, 13], 'load': 0, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [6, 14, 5], 'load': 8, 'cap': 12}, {'id': 'C', 'ready_s': 20, 'stops': [], 'load': 4, 'cap': 12}], 'requests': [{'dest': 12, 'n': 3}, {'dest': 2, 'n': 2}, {'dest': 8, 'n': 5}, {'dest': 11, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['C', 'B', 'C', 'B']), ('boundary: coincident destination beats an idle car', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 0, 'stops': [7], 'load': 0, 'cap': 12}], 'requests': [{'dest': 7, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['B']), ('sampled regression 45', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [5], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 0, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 6, 'n': 5}, {'dest': 9, 'n': 5}, {'dest': 13, 'n': 1}, {'dest': 9, 'n': 2}, {'dest': 8, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 3}, ['B', 'A', 'B', 'A', 'A']), ('control 48', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [7], 'load': 11, 'cap': 12}, {'id': 'B', 'ready_s': 20, 'stops': [2, 13], 'load': 11, 'cap': 13}, {'id': 'C', 'ready_s': 20, 'stops': [10, 12], 'load': 11, 'cap': 12}], 'requests': [{'dest': 6, 'n': 2}, {'dest': 14, 'n': 5}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['B', None]), ('sampled regression 51', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [3], 'load': 8, 'cap': 12}, {'id': 'B', 'ready_s': 10, 'stops': [12, 8], 'load': 0, 'cap': 12}, {'id': 'C', 'ready_s': 20, 'stops': [10], 'load': 0, 'cap': 13}], 'requests': [{'dest': 14, 'n': 1}, {'dest': 13, 'n': 2}, {'dest': 5, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['A', 'A', 'A'])]]
for label, args, expected in fixtures[N-1]:
    check(label, solve(args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)

Boundary fixture	Actual	Expected	Outcome
regression: equal cost cars	`['B']`	`['A']`	Failed
sampled regression 7	`['C', 'A', 'C', 'C']`	`['A', 'C', 'A', 'A']`	Failed
sampled regression 10	`['B', 'A']`	`['A', 'B']`	Failed
boundary: group exactly fills the car	`['A']`	`['A']`	Passed
boundary: coincident destination beats an idle car	`['B']`	`['B']`	Passed
control 1	`['A', None]`	`['A', None]`	Passed
control 4	`['C', 'B', 'A', 'B']`	`['C', 'B', 'A', 'B']`	Passed
sampled regression 13	`['A', 'A', 'A', 'A', 'C']`	`['A', 'A', 'A', 'A', 'B']`	Failed

SHA-256 / 168bb97140655c495bf94c779e70069c3909d7a6d442b8d1ee4f94c48ef78531

2 / The unsuccessful fix

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(x):
    cars = {c['id']: {'ready': c['ready_s'], 'stops': set(c['stops']), 'load': c['load'], 'cap': c['cap']} for c in x['cars']}
    out = []
    for req in x['requests']:
        best = None
        for cid in sorted(cars):
            c = cars[cid]
            if c['load'] + req['n'] > c['cap']:
                continue
            new_stop = 0 if req['dest'] in c['stops'] else 1
            cost = c['ready'] + x['per_stop_s'] * len(c['stops']) + x['stop_penalty_s'] * new_stop
            if best is None or cost < best[0] or (cost == best[0] and c['load'] < cars[best[1]]['load']):
                best = (cost, cid)
        if best is None:
            out.append(None)
            continue
        c = cars[best[1]]
        c['stops'].add(req['dest'])
        c['load'] += req['n']
        out.append(best[1])
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: equal cost cars', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 4, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('sampled regression 7', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [11, 6], 'load': 8, 'cap': 13}, {'id': 'B', 'ready_s': 20, 'stops': [7], 'load': 8, 'cap': 12}, {'id': 'C', 'ready_s': 10, 'stops': [5], 'load': 0, 'cap': 12}], 'requests': [{'dest': 2, 'n': 1}, {'dest': 8, 'n': 5}, {'dest': 11, 'n': 3}, {'dest': 3, 'n': 1}], 'stop_penalty_s': 15, 'per_stop_s': 5}, ['A', 'C', 'A', 'A']), ('sampled regression 10', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [5], 'load': 0, 'cap': 12}], 'requests': [{'dest': 12, 'n': 1}, {'dest': 8, 'n': 3}], 'stop_penalty_s': 15, 'per_stop_s': 5}, ['A', 'B']), ('boundary: group exactly fills the car', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [], 'load': 10, 'cap': 12}, {'id': 'B', 'ready_s': 30, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 5, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('boundary: coincident destination beats an idle car', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 0, 'stops': [7], 'load': 0, 'cap': 12}], 'requests': [{'dest': 7, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['B']), ('control 1', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [10, 11], 'load': 8, 'cap': 13}, {'id': 'B', 'ready_s': 20, 'stops': [9], 'load': 11, 'cap': 12}, {'id': 'C', 'ready_s': 0, 'stops': [13, 14, 2], 'load': 11, 'cap': 13}], 'requests': [{'dest': 10, 'n': 1}, {'dest': 9, 'n': 5}], 'stop_penalty_s': 10, 'per_stop_s': 3}, ['A', None]), ('control 4', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [], 'load': 11, 'cap': 12}, {'id': 'B', 'ready_s': 10, 'stops': [3], 'load': 4, 'cap': 12}, {'id': 'C', 'ready_s': 5, 'stops': [], 'load': 11, 'cap': 13}], 'requests': [{'dest': 7, 'n': 2}, {'dest': 3, 'n': 1}, {'dest': 8, 'n': 1}, {'dest': 3, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['C', 'B', 'A', 'B']), ('sampled regression 13', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [3], 'load': 0, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [2, 11, 7], 'load': 8, 'cap': 13}, {'id': 'C', 'ready_s': 20, 'stops': [6], 'load': 0, 'cap': 12}], 'requests': [{'dest': 9, 'n': 3}, {'dest': 14, 'n': 5}, {'dest': 14, 'n': 1}, {'dest': 3, 'n': 1}, {'dest': 9, 'n': 5}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['A', 'A', 'A', 'A', 'B'])], [('regression: equal cost cars', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 4, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('sampled regression 10', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [5], 'load': 0, 'cap': 12}], 'requests': [{'dest': 12, 'n': 1}, {'dest': 8, 'n': 3}], 'stop_penalty_s': 15, 'per_stop_s': 5}, ['A', 'B']), ('sampled regression 22', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [7, 5, 11], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 10, 'stops': [], 'load': 8, 'cap': 13}, {'id': 'C', 'ready_s': 0, 'stops': [10, 8], 'load': 0, 'cap': 13}], 'requests': [{'dest': 12, 'n': 2}, {'dest': 11, 'n': 5}, {'dest': 13, 'n': 2}, {'dest': 13, 'n': 1}, {'dest': 7, 'n': 5}], 'stop_penalty_s': 8, 'per_stop_s': 3}, ['C', 'A', 'A', 'A', 'C']), ('sampled regression 27', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [12, 6, 13], 'load': 0, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [6, 14, 5], 'load': 8, 'cap': 12}, {'id': 'C', 'ready_s': 20, 'stops': [], 'load': 4, 'cap': 12}], 'requests': [{'dest': 12, 'n': 3}, {'dest': 2, 'n': 2}, {'dest': 8, 'n': 5}, {'dest': 11, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['C', 'B', 'C', 'B']), ('boundary: empty car earns no discount', {'cars': [{'id': 'A', 'ready_s': 4, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 0, 'stops': [9], 'load': 0, 'cap': 12}], 'requests': [{'dest': 3, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('control 12', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [6, 3], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 20, 'stops': [], 'load': 4, 'cap': 12}, {'id': 'C', 'ready_s': 20, 'stops': [10, 8], 'load': 11, 'cap': 13}], 'requests': [{'dest': 10, 'n': 1}, {'dest': 2, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 3}, ['A', 'A']), ('sampled regression 15', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [3], 'load': 0, 'cap': 13}, {'id': 'B', 'ready_s': 5, 'stops': [7, 2], 'load': 0, 'cap': 13}, {'id': 'C', 'ready_s': 5, 'stops': [12], 'load': 0, 'cap': 12}], 'requests': [{'dest': 2, 'n': 3}, {'dest': 13, 'n': 5}, {'dest': 11, 'n': 1}, {'dest': 2, 'n': 1}, {'dest': 12, 'n': 3}], 'stop_penalty_s': 8, 'per_stop_s': 3}, ['B', 'A', 'C', 'B', 'C']), ('sampled regression 18', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 20, 'stops': [2, 7, 5], 'load': 0, 'cap': 12}], 'requests': [{'dest': 10, 'n': 5}, {'dest': 2, 'n': 1}, {'dest': 6, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A', 'A', 'A'])], [('regression: equal cost cars', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 4, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('sampled regression 13', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [3], 'load': 0, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [2, 11, 7], 'load': 8, 'cap': 13}, {'id': 'C', 'ready_s': 20, 'stops': [6], 'load': 0, 'cap': 12}], 'requests': [{'dest': 9, 'n': 3}, {'dest': 14, 'n': 5}, {'dest': 14, 'n': 1}, {'dest': 3, 'n': 1}, {'dest': 9, 'n': 5}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['A', 'A', 'A', 'A', 'B']), ('sampled regression 34', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [8], 'load': 8, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [2], 'load': 0, 'cap': 12}], 'requests': [{'dest': 6, 'n': 1}, {'dest': 11, 'n': 3}, {'dest': 5, 'n': 1}, {'dest': 9, 'n': 1}, {'dest': 10, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['B', 'B', 'A', 'B', 'A']), ('sampled regression 58', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [12, 2, 9], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [5, 13], 'load': 4, 'cap': 13}, {'id': 'C', 'ready_s': 5, 'stops': [5, 11], 'load': 0, 'cap': 12}], 'requests': [{'dest': 10, 'n': 3}, {'dest': 13, 'n': 2}, {'dest': 4, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 3}, ['B', 'B', 'C']), ('boundary: second group sees the first allocation', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 2, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 6, 'n': 3}, {'dest': 6, 'n': 3}, {'dest': 6, 'n': 3}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A', 'A', 'A']), ('sampled regression 23', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [2], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 20, 'stops': [9, 8], 'load': 4, 'cap': 13}, {'id': 'C', 'ready_s': 10, 'stops': [], 'load': 0, 'cap': 13}], 'requests': [{'dest': 8, 'n': 3}, {'dest': 13, 'n': 1}, {'dest': 9, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['C', 'C', 'B']), ('control 26', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [9], 'load': 8, 'cap': 12}, {'id': 'B', 'ready_s': 10, 'stops': [11, 14, 4], 'load': 8, 'cap': 13}], 'requests': [{'dest': 13, 'n': 1}, {'dest': 5, 'n': 1}, {'dest': 12, 'n': 1}, {'dest': 9, 'n': 1}, {'dest': 7, 'n': 3}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A', 'A', 'A', 'A', 'B']), ('sampled regression 29', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [], 'load': 0, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [2, 5, 7], 'load': 8, 'cap': 13}, {'id': 'C', 'ready_s': 20, 'stops': [2], 'load': 4, 'cap': 12}], 'requests': [{'dest': 6, 'n': 1}, {'dest': 3, 'n': 5}], 'stop_penalty_s': 15, 'per_stop_s': 5}, ['A', 'A'])], [('regression: equal cost cars', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 4, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('sampled regression 18', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 20, 'stops': [2, 7, 5], 'load': 0, 'cap': 12}], 'requests': [{'dest': 10, 'n': 5}, {'dest': 2, 'n': 1}, {'dest': 6, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A', 'A', 'A']), ('sampled regression 59', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [6], 'load': 11, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [8, 13, 14], 'load': 4, 'cap': 13}], 'requests': [{'dest': 7, 'n': 1}, {'dest': 4, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['B', 'A']), ('sampled regression 10', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [5], 'load': 0, 'cap': 12}], 'requests': [{'dest': 12, 'n': 1}, {'dest': 8, 'n': 3}], 'stop_penalty_s': 15, 'per_stop_s': 5}, ['A', 'B']), ('boundary: no eligible car', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [], 'load': 11, 'cap': 12}], 'requests': [{'dest': 5, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 5}, [None]), ('sampled regression 34', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [8], 'load': 8, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [2], 'load': 0, 'cap': 12}], 'requests': [{'dest': 6, 'n': 1}, {'dest': 11, 'n': 3}, {'dest': 5, 'n': 1}, {'dest': 9, 'n': 1}, {'dest': 10, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['B', 'B', 'A', 'B', 'A']), ('control 37', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [], 'load': 8, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [9, 14, 8], 'load': 8, 'cap': 12}], 'requests': [{'dest': 5, 'n': 1}, {'dest': 8, 'n': 1}, {'dest': 2, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A', 'B', 'A']), ('control 40', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [], 'load': 4, 'cap': 13}, {'id': 'B', 'ready_s': 0, 'stops': [10, 5, 7], 'load': 0, 'cap': 12}], 'requests': [{'dest': 5, 'n': 5}, {'dest': 5, 'n': 5}, {'dest': 7, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['A', 'B', 'A'])], [('regression: equal cost cars', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 4, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('sampled regression 22', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [7, 5, 11], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 10, 'stops': [], 'load': 8, 'cap': 13}, {'id': 'C', 'ready_s': 0, 'stops': [10, 8], 'load': 0, 'cap': 13}], 'requests': [{'dest': 12, 'n': 2}, {'dest': 11, 'n': 5}, {'dest': 13, 'n': 2}, {'dest': 13, 'n': 1}, {'dest': 7, 'n': 5}], 'stop_penalty_s': 8, 'per_stop_s': 3}, ['C', 'A', 'A', 'A', 'C']), ('sampled regression 5', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [3, 6, 5], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 0, 'stops': [2, 3], 'load': 8, 'cap': 12}, {'id': 'C', 'ready_s': 5, 'stops': [], 'load': 4, 'cap': 12}], 'requests': [{'dest': 2, 'n': 5}, {'dest': 9, 'n': 1}, {'dest': 3, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['C', 'B', 'B']), ('sampled regression 27', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [12, 6, 13], 'load': 0, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [6, 14, 5], 'load': 8, 'cap': 12}, {'id': 'C', 'ready_s': 20, 'stops': [], 'load': 4, 'cap': 12}], 'requests': [{'dest': 12, 'n': 3}, {'dest': 2, 'n': 2}, {'dest': 8, 'n': 5}, {'dest': 11, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['C', 'B', 'C', 'B']), ('boundary: coincident destination beats an idle car', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 0, 'stops': [7], 'load': 0, 'cap': 12}], 'requests': [{'dest': 7, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['B']), ('sampled regression 45', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [5], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 0, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 6, 'n': 5}, {'dest': 9, 'n': 5}, {'dest': 13, 'n': 1}, {'dest': 9, 'n': 2}, {'dest': 8, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 3}, ['B', 'A', 'B', 'A', 'A']), ('control 48', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [7], 'load': 11, 'cap': 12}, {'id': 'B', 'ready_s': 20, 'stops': [2, 13], 'load': 11, 'cap': 13}, {'id': 'C', 'ready_s': 20, 'stops': [10, 12], 'load': 11, 'cap': 12}], 'requests': [{'dest': 6, 'n': 2}, {'dest': 14, 'n': 5}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['B', None]), ('sampled regression 51', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [3], 'load': 8, 'cap': 12}, {'id': 'B', 'ready_s': 10, 'stops': [12, 8], 'load': 0, 'cap': 12}, {'id': 'C', 'ready_s': 20, 'stops': [10], 'load': 0, 'cap': 13}], 'requests': [{'dest': 14, 'n': 1}, {'dest': 13, 'n': 2}, {'dest': 5, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['A', 'A', 'A'])]]
for label, args, expected in fixtures[N-1]:
    check(label, solve(args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)

Boundary fixture	Actual	Expected	Outcome
regression: equal cost cars	`['A']`	`['A']`	Passed
sampled regression 7	`['C', 'A', 'C', 'C']`	`['A', 'C', 'A', 'A']`	Failed
sampled regression 10	`['B', 'A']`	`['A', 'B']`	Failed
boundary: group exactly fills the car	`['A']`	`['A']`	Passed
boundary: coincident destination beats an idle car	`['B']`	`['B']`	Passed
control 1	`['A', None]`	`['A', None]`	Passed
control 4	`['C', 'B', 'A', 'B']`	`['C', 'B', 'A', 'B']`	Passed
sampled regression 13	`['A', 'A', 'A', 'A', 'C']`	`['A', 'A', 'A', 'A', 'B']`	Failed

SHA-256 / e09a46849ab63e7b553c5badd596fb882286c800a0f98d6a8ad7a75b5266860b

3 / The verified repair

Exit 0

"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(x):
    cars = {c['id']: {'ready': c['ready_s'], 'stops': set(c['stops']), 'load': c['load'], 'cap': c['cap']} for c in x['cars']}
    out = []
    for req in x['requests']:
        best = None
        for cid in sorted(cars):
            c = cars[cid]
            if c['load'] + req['n'] > c['cap']:
                continue
            new_stop = 0 if req['dest'] in c['stops'] else 1
            cost = c['ready'] + x['per_stop_s'] * len(c['stops']) + x['stop_penalty_s'] * new_stop
            if best is None or cost < best[0]:
                best = (cost, cid)
        if best is None:
            out.append(None)
            continue
        c = cars[best[1]]
        c['stops'].add(req['dest'])
        c['load'] += req['n']
        out.append(best[1])
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: equal cost cars', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 4, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('sampled regression 7', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [11, 6], 'load': 8, 'cap': 13}, {'id': 'B', 'ready_s': 20, 'stops': [7], 'load': 8, 'cap': 12}, {'id': 'C', 'ready_s': 10, 'stops': [5], 'load': 0, 'cap': 12}], 'requests': [{'dest': 2, 'n': 1}, {'dest': 8, 'n': 5}, {'dest': 11, 'n': 3}, {'dest': 3, 'n': 1}], 'stop_penalty_s': 15, 'per_stop_s': 5}, ['A', 'C', 'A', 'A']), ('sampled regression 10', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [5], 'load': 0, 'cap': 12}], 'requests': [{'dest': 12, 'n': 1}, {'dest': 8, 'n': 3}], 'stop_penalty_s': 15, 'per_stop_s': 5}, ['A', 'B']), ('boundary: group exactly fills the car', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [], 'load': 10, 'cap': 12}, {'id': 'B', 'ready_s': 30, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 5, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('boundary: coincident destination beats an idle car', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 0, 'stops': [7], 'load': 0, 'cap': 12}], 'requests': [{'dest': 7, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['B']), ('control 1', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [10, 11], 'load': 8, 'cap': 13}, {'id': 'B', 'ready_s': 20, 'stops': [9], 'load': 11, 'cap': 12}, {'id': 'C', 'ready_s': 0, 'stops': [13, 14, 2], 'load': 11, 'cap': 13}], 'requests': [{'dest': 10, 'n': 1}, {'dest': 9, 'n': 5}], 'stop_penalty_s': 10, 'per_stop_s': 3}, ['A', None]), ('control 4', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [], 'load': 11, 'cap': 12}, {'id': 'B', 'ready_s': 10, 'stops': [3], 'load': 4, 'cap': 12}, {'id': 'C', 'ready_s': 5, 'stops': [], 'load': 11, 'cap': 13}], 'requests': [{'dest': 7, 'n': 2}, {'dest': 3, 'n': 1}, {'dest': 8, 'n': 1}, {'dest': 3, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['C', 'B', 'A', 'B']), ('sampled regression 13', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [3], 'load': 0, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [2, 11, 7], 'load': 8, 'cap': 13}, {'id': 'C', 'ready_s': 20, 'stops': [6], 'load': 0, 'cap': 12}], 'requests': [{'dest': 9, 'n': 3}, {'dest': 14, 'n': 5}, {'dest': 14, 'n': 1}, {'dest': 3, 'n': 1}, {'dest': 9, 'n': 5}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['A', 'A', 'A', 'A', 'B'])], [('regression: equal cost cars', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 4, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('sampled regression 10', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [5], 'load': 0, 'cap': 12}], 'requests': [{'dest': 12, 'n': 1}, {'dest': 8, 'n': 3}], 'stop_penalty_s': 15, 'per_stop_s': 5}, ['A', 'B']), ('sampled regression 22', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [7, 5, 11], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 10, 'stops': [], 'load': 8, 'cap': 13}, {'id': 'C', 'ready_s': 0, 'stops': [10, 8], 'load': 0, 'cap': 13}], 'requests': [{'dest': 12, 'n': 2}, {'dest': 11, 'n': 5}, {'dest': 13, 'n': 2}, {'dest': 13, 'n': 1}, {'dest': 7, 'n': 5}], 'stop_penalty_s': 8, 'per_stop_s': 3}, ['C', 'A', 'A', 'A', 'C']), ('sampled regression 27', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [12, 6, 13], 'load': 0, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [6, 14, 5], 'load': 8, 'cap': 12}, {'id': 'C', 'ready_s': 20, 'stops': [], 'load': 4, 'cap': 12}], 'requests': [{'dest': 12, 'n': 3}, {'dest': 2, 'n': 2}, {'dest': 8, 'n': 5}, {'dest': 11, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['C', 'B', 'C', 'B']), ('boundary: empty car earns no discount', {'cars': [{'id': 'A', 'ready_s': 4, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 0, 'stops': [9], 'load': 0, 'cap': 12}], 'requests': [{'dest': 3, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('control 12', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [6, 3], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 20, 'stops': [], 'load': 4, 'cap': 12}, {'id': 'C', 'ready_s': 20, 'stops': [10, 8], 'load': 11, 'cap': 13}], 'requests': [{'dest': 10, 'n': 1}, {'dest': 2, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 3}, ['A', 'A']), ('sampled regression 15', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [3], 'load': 0, 'cap': 13}, {'id': 'B', 'ready_s': 5, 'stops': [7, 2], 'load': 0, 'cap': 13}, {'id': 'C', 'ready_s': 5, 'stops': [12], 'load': 0, 'cap': 12}], 'requests': [{'dest': 2, 'n': 3}, {'dest': 13, 'n': 5}, {'dest': 11, 'n': 1}, {'dest': 2, 'n': 1}, {'dest': 12, 'n': 3}], 'stop_penalty_s': 8, 'per_stop_s': 3}, ['B', 'A', 'C', 'B', 'C']), ('sampled regression 18', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 20, 'stops': [2, 7, 5], 'load': 0, 'cap': 12}], 'requests': [{'dest': 10, 'n': 5}, {'dest': 2, 'n': 1}, {'dest': 6, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A', 'A', 'A'])], [('regression: equal cost cars', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 4, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('sampled regression 13', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [3], 'load': 0, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [2, 11, 7], 'load': 8, 'cap': 13}, {'id': 'C', 'ready_s': 20, 'stops': [6], 'load': 0, 'cap': 12}], 'requests': [{'dest': 9, 'n': 3}, {'dest': 14, 'n': 5}, {'dest': 14, 'n': 1}, {'dest': 3, 'n': 1}, {'dest': 9, 'n': 5}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['A', 'A', 'A', 'A', 'B']), ('sampled regression 34', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [8], 'load': 8, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [2], 'load': 0, 'cap': 12}], 'requests': [{'dest': 6, 'n': 1}, {'dest': 11, 'n': 3}, {'dest': 5, 'n': 1}, {'dest': 9, 'n': 1}, {'dest': 10, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['B', 'B', 'A', 'B', 'A']), ('sampled regression 58', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [12, 2, 9], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [5, 13], 'load': 4, 'cap': 13}, {'id': 'C', 'ready_s': 5, 'stops': [5, 11], 'load': 0, 'cap': 12}], 'requests': [{'dest': 10, 'n': 3}, {'dest': 13, 'n': 2}, {'dest': 4, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 3}, ['B', 'B', 'C']), ('boundary: second group sees the first allocation', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 2, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 6, 'n': 3}, {'dest': 6, 'n': 3}, {'dest': 6, 'n': 3}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A', 'A', 'A']), ('sampled regression 23', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [2], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 20, 'stops': [9, 8], 'load': 4, 'cap': 13}, {'id': 'C', 'ready_s': 10, 'stops': [], 'load': 0, 'cap': 13}], 'requests': [{'dest': 8, 'n': 3}, {'dest': 13, 'n': 1}, {'dest': 9, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['C', 'C', 'B']), ('control 26', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [9], 'load': 8, 'cap': 12}, {'id': 'B', 'ready_s': 10, 'stops': [11, 14, 4], 'load': 8, 'cap': 13}], 'requests': [{'dest': 13, 'n': 1}, {'dest': 5, 'n': 1}, {'dest': 12, 'n': 1}, {'dest': 9, 'n': 1}, {'dest': 7, 'n': 3}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A', 'A', 'A', 'A', 'B']), ('sampled regression 29', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [], 'load': 0, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [2, 5, 7], 'load': 8, 'cap': 13}, {'id': 'C', 'ready_s': 20, 'stops': [2], 'load': 4, 'cap': 12}], 'requests': [{'dest': 6, 'n': 1}, {'dest': 3, 'n': 5}], 'stop_penalty_s': 15, 'per_stop_s': 5}, ['A', 'A'])], [('regression: equal cost cars', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 4, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('sampled regression 18', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 20, 'stops': [2, 7, 5], 'load': 0, 'cap': 12}], 'requests': [{'dest': 10, 'n': 5}, {'dest': 2, 'n': 1}, {'dest': 6, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A', 'A', 'A']), ('sampled regression 59', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [6], 'load': 11, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [8, 13, 14], 'load': 4, 'cap': 13}], 'requests': [{'dest': 7, 'n': 1}, {'dest': 4, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['B', 'A']), ('sampled regression 10', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [5], 'load': 0, 'cap': 12}], 'requests': [{'dest': 12, 'n': 1}, {'dest': 8, 'n': 3}], 'stop_penalty_s': 15, 'per_stop_s': 5}, ['A', 'B']), ('boundary: no eligible car', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [], 'load': 11, 'cap': 12}], 'requests': [{'dest': 5, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 5}, [None]), ('sampled regression 34', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [8], 'load': 8, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [2], 'load': 0, 'cap': 12}], 'requests': [{'dest': 6, 'n': 1}, {'dest': 11, 'n': 3}, {'dest': 5, 'n': 1}, {'dest': 9, 'n': 1}, {'dest': 10, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['B', 'B', 'A', 'B', 'A']), ('control 37', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [], 'load': 8, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [9, 14, 8], 'load': 8, 'cap': 12}], 'requests': [{'dest': 5, 'n': 1}, {'dest': 8, 'n': 1}, {'dest': 2, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A', 'B', 'A']), ('control 40', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [], 'load': 4, 'cap': 13}, {'id': 'B', 'ready_s': 0, 'stops': [10, 5, 7], 'load': 0, 'cap': 12}], 'requests': [{'dest': 5, 'n': 5}, {'dest': 5, 'n': 5}, {'dest': 7, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['A', 'B', 'A'])], [('regression: equal cost cars', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 5, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 4, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['A']), ('sampled regression 22', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [7, 5, 11], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 10, 'stops': [], 'load': 8, 'cap': 13}, {'id': 'C', 'ready_s': 0, 'stops': [10, 8], 'load': 0, 'cap': 13}], 'requests': [{'dest': 12, 'n': 2}, {'dest': 11, 'n': 5}, {'dest': 13, 'n': 2}, {'dest': 13, 'n': 1}, {'dest': 7, 'n': 5}], 'stop_penalty_s': 8, 'per_stop_s': 3}, ['C', 'A', 'A', 'A', 'C']), ('sampled regression 5', {'cars': [{'id': 'A', 'ready_s': 10, 'stops': [3, 6, 5], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 0, 'stops': [2, 3], 'load': 8, 'cap': 12}, {'id': 'C', 'ready_s': 5, 'stops': [], 'load': 4, 'cap': 12}], 'requests': [{'dest': 2, 'n': 5}, {'dest': 9, 'n': 1}, {'dest': 3, 'n': 2}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['C', 'B', 'B']), ('sampled regression 27', {'cars': [{'id': 'A', 'ready_s': 20, 'stops': [12, 6, 13], 'load': 0, 'cap': 13}, {'id': 'B', 'ready_s': 10, 'stops': [6, 14, 5], 'load': 8, 'cap': 12}, {'id': 'C', 'ready_s': 20, 'stops': [], 'load': 4, 'cap': 12}], 'requests': [{'dest': 12, 'n': 3}, {'dest': 2, 'n': 2}, {'dest': 8, 'n': 5}, {'dest': 11, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['C', 'B', 'C', 'B']), ('boundary: coincident destination beats an idle car', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [], 'load': 0, 'cap': 12}, {'id': 'B', 'ready_s': 0, 'stops': [7], 'load': 0, 'cap': 12}], 'requests': [{'dest': 7, 'n': 1}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['B']), ('sampled regression 45', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [5], 'load': 4, 'cap': 12}, {'id': 'B', 'ready_s': 0, 'stops': [], 'load': 0, 'cap': 12}], 'requests': [{'dest': 6, 'n': 5}, {'dest': 9, 'n': 5}, {'dest': 13, 'n': 1}, {'dest': 9, 'n': 2}, {'dest': 8, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 3}, ['B', 'A', 'B', 'A', 'A']), ('control 48', {'cars': [{'id': 'A', 'ready_s': 0, 'stops': [7], 'load': 11, 'cap': 12}, {'id': 'B', 'ready_s': 20, 'stops': [2, 13], 'load': 11, 'cap': 13}, {'id': 'C', 'ready_s': 20, 'stops': [10, 12], 'load': 11, 'cap': 12}], 'requests': [{'dest': 6, 'n': 2}, {'dest': 14, 'n': 5}], 'stop_penalty_s': 10, 'per_stop_s': 5}, ['B', None]), ('sampled regression 51', {'cars': [{'id': 'A', 'ready_s': 5, 'stops': [3], 'load': 8, 'cap': 12}, {'id': 'B', 'ready_s': 10, 'stops': [12, 8], 'load': 0, 'cap': 12}, {'id': 'C', 'ready_s': 20, 'stops': [10], 'load': 0, 'cap': 13}], 'requests': [{'dest': 14, 'n': 1}, {'dest': 13, 'n': 2}, {'dest': 5, 'n': 1}], 'stop_penalty_s': 8, 'per_stop_s': 5}, ['A', 'A', 'A'])]]
for label, args, expected in fixtures[N-1]:
    check(label, solve(args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)

Boundary fixture	Actual	Expected	Outcome
regression: equal cost cars	`['A']`	`['A']`	Passed
sampled regression 7	`['A', 'C', 'A', 'A']`	`['A', 'C', 'A', 'A']`	Passed
sampled regression 10	`['A', 'B']`	`['A', 'B']`	Passed
boundary: group exactly fills the car	`['A']`	`['A']`	Passed
boundary: coincident destination beats an idle car	`['B']`	`['B']`	Passed
control 1	`['A', None]`	`['A', None]`	Passed
control 4	`['C', 'B', 'A', 'B']`	`['C', 'B', 'A', 'B']`	Passed
sampled regression 13	`['A', 'A', 'A', 'A', 'B']`	`['A', 'A', 'A', 'A', 'B']`	Passed

SHA-256 / c1aef74a5c42d4127245781f0241350ab9ba37b3126005a7f4466b3a681e1928

Verification & scope

Stipulated toy lift-control contract for a bounded teaching model; it makes no claim of conformance to any lift code or vendor dispatcher and omits real safety cases. This reproducer isolates one failure mechanism. Results cover the supplied fixtures. Variants within a family share a test contract and should remain grouped when constructing evaluation splits. Related mechanisms with a shared evaluation_group must also remain together; these controlled models are not independent production incidents.

Observations recorded using Python 3.12.14 at 2026-09-29T14:47:52.301373+00:00.

Case digest / a9065391ceba69bc90be4a2229d2485c858572adb6aa50dbcefcb5d3af8fcd81