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Probabilistic Bid Price (ProBP) Actions

ProbabilisticBidPrice

Bases: RmAction

ProBP (ProbabilisticBidPrice) is a path-based optimization algorithm.

requires class-attribute instance-attribute

requires: set[str] = {'path_forecast'}

frequency class-attribute instance-attribute

frequency = 'daily_pre_dep'

cabins instance-attribute

cabins = cabins

Optional list of cabin codes to optimize.

If not provided, this tool will optimize on the leg as a whole.

capacity_sharing instance-attribute

capacity_sharing = capacity_sharing

Capacity sharing flag between cabins.

When set to True, will use method 3 from Peter Belobaba's presentation. Higher cabin(s) will get max of combined cabins or itself alone. Lower cabin(s) will get min of combined cabins or itself alone.

capacity_sharing_start_dcp_index instance-attribute

capacity_sharing_start_dcp_index = (
    capacity_sharing_start_dcp_index
)

use_adjusted_fares instance-attribute

use_adjusted_fares = use_adjusted_fares

If True, ProBP will use the adjusted fares for the optimization.

The default is False, which means that ProBP will use the original fares. This should be set to True if fare adjustment is being used for this carrier.

bid_price_vector instance-attribute

bid_price_vector = bid_price_vector

If True, we create a bid price vector in ProBP, rather than just keep a constant bid-price untiol daily re-optimization

maxiter instance-attribute

maxiter = maxiter

The maximum number of iterations to run ProBP.

If the algorithm has not converged by the time this number of iterations has been reached, it will stop and return the current results.

__init__

__init__(
    *,
    carrier: str = "",
    cabins: str | list[str] | None = None,
    minimum_sample: int = 10,
    dcps: Collection[int] = (),
    capacity_sharing: bool | None = False,
    capacity_sharing_start_dcp_index: int | None = 0,
    use_adjusted_fares: bool = False,
    bid_price_vector: bool | None = False,
    maxiter: int = 10,
)

run

run(sim: Simulation, days_prior: int)