Aria AI Operations Research Portfolio
Collection
Enterprise OR, optimization, and decomposition demos by Aria AI • 136 items • Updated
Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: ValueError
Message: Expected object or value
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 342, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to string in row 0
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 304, in _generate_tables
batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 111, in json_encode_fields_in_json_lines
examples = [ujson_loads(line) for line in original_batch.splitlines()]
~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
return pd.io.json.ujson_loads(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
ValueError: Expected object or valueNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Airline Disruption Recovery Scenarios
Five synthetic hub-and-spoke airline schedules (one per demo disruption archetype), each with aircraft rotations, crew pairings, and passenger itineraries, generated with a fixed random seed for reproducibility.
Scenarios
| Key | Description |
|---|---|
airport_closure |
Spoke airport closed for 3 hours (low visibility) |
aircraft_failure |
Unscheduled aircraft grounding for maintenance |
crew_shortage |
Reserve crew shortage wave |
cascading_weather_delay |
Thunderstorm line reduces hub arrival/departure rate |
capacity_reduction |
Ground delay program caps hub arrival rate |
Files
| File | Contents |
|---|---|
manifest.json |
Index of all scenario files with entity counts |
sample_<scenario_key>.json |
Full schedule snapshot: airports, aircraft, flights, crew, pairings, itineraries, disruption events |
eval_results.json |
Benchmark KPI results per scenario from the reference solver pipeline |
Schema
Each sample_*.json file is a serialized Schedule object:
{
"scenario_id": "...",
"airports": {"CODE": {"code": "...", "name": "...", "gates": 0, "is_hub": false}},
"aircraft": {"TAIL": {"tail": "...", "fleet_type": "...", "seats": 0, "home_base": "..."}},
"flights": {"F0001": {"flight_id": "...", "origin": "...", "destination": "...", "sched_dep": 0, "sched_arr": 0, "aircraft_tail": "...", "pairing_id": "..."}},
"crew": {"CR0001": {"crew_id": "...", "role": "...", "base": "..."}},
"pairings": {"P0001": {"pairing_id": "...", "crew_ids": [], "leg_ids": []}},
"itineraries": {"I00001": {"itinerary_id": "...", "leg_ids": [], "pax_count": 0, "priority_class": "..."}},
"disruptions": [{"event_type": "...", "description": "...", "start_time": 0, "duration_minutes": 0}]
}
Times are integer minutes from the start of a 24-hour recovery horizon.
Generation
Regenerate with:
python scripts/build_assets.py
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