ExpectedMarginalSeatRevenue¶

Bases: RmAction

EMSR (Expected Marginal Seat Revenue) is a leg-based optimization algorithm.

The EMSR (Expected Marginal Seat Revenue) algorithm is a widely adopted heuristic for capacity allocation in revenue management, primarily used to determine how many seats to protect for higher-fare classes in a restricted product marketplace. It works by calculating a booking limit for each fare class, starting with the lowest, to maximize expected revenue.

The “A” algorithm compares each class individually, and is not generally used in practice. The “B” algorithm, often called EMSR-B, aggregates displaced low-fare passengers. This method uses Littlewood’s rule with the aggregate demand and average fare to statistically determine optimal protection levels for the remaining higher-priced inventory, effectively balancing the risk of selling a seat cheaply now versus the potential of selling it at a higher price later.

Applying the EMSR algorithm requires a forecast of leg demand by fare class. Protection levels are updated at each decision control point (DCP) based on the latest sales and demand forecasts, allowing for dynamic adjustment to changing booking patterns.

Methods

`__init__`(*[, variant, carrier, cabins, ...])
`apply_snapshot_filters`(sim, days_prior, ...)	Apply this action's snapshot filters, if any, and return the resulting instruction.
`configure`([fixed])	Create an RmActionFactory for this action with the given configuration.
`get_dcp_index`(days_prior[, allow_between])
`init`(sim)	Initialize the action for the given simulation.
`run`(sim, days_prior)	Execute the action for the given simulation.
`should_run`(sim, days_prior)	Determine if the action should run on the given days_prior.

Attributes

`OPT`
`frequency`	The frequency with which to run this action.
`produces`
`requires`
`snapshot_filter_type`
`variant`	"a", "b", or "c".
`cabins`	Optional list of cabin codes to optimize.
`snapshots`	Optional list of snapshots to grap when running this action.
`dcps`	Set of days prior to departure on which to run this action.
`carrier`	The carrier upon which to apply this action.
`minimum_sample`	The minimum sample number before this action will run.

requires : set[str] = {'leg_forecast'}¶

frequency : Literal['dcp', 'daily', 'daily_pre_dep', 'non_dcp', 'begin_sample', 'end_sample', 'weekly'] = 'dcp'¶

The frequency with which to run this action.

This can be one of the following values: - “dcp”: run only on the specified DCPs. - “daily”: run every day. - “daily_pre_dep”: run every day prior to departure (i.e., days_prior > 0).” - “non_dcp”: run on days that are not in the specified DCPs. - “begin_sample”: run only on the first DCP (i.e., the maximum days_prior). - “end_sample”: run only on the day of departure (i.e., days_prior == 0). - “weekly”: run every 7 days (i.e. when days_prior is a multiple of 7).

The run method of RM actions is actually called every day (as it is implemented as a daily callback), but the first thing the run method should do is check whether it should actually execute on that day, using the should_run method, which uses this frequency setting to determine whether to proceed.

OPT = <passengersim.core.EMSR>¶

variant¶

“a”, “b”, or “c”.

Type:: EMSR variant to use

cabins¶

Optional list of cabin codes to optimize.

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

apply_snapshot_filters(sim: Simulation, days_prior: int, *args, **kwargs) → SnapshotInstruction | None¶

Apply this action’s snapshot filters, if any, and return the resulting instruction.

If there are no snapshot filters, or if none of the filters trigger, then this returns None.

classmethod configure(fixed: dict[str, Any] | None = None, **kwargs) → RmActionFactory¶

Create an RmActionFactory for this action with the given configuration.

Each keyword argument name should correspond to a parameter in the RmAction subclass’s __init__ method. The value of each keyword argument will be the keyword argument used in the RmSys that uses this factory.

Fixed values can be provided via the fixed parameter, which is a dictionary of parameter names to fixed values. These values will always be passed to the RmAction constructor, and cannot be overridden via the RmSys.

get_dcp_index(days_prior: int, allow_between: bool = False) → int¶

init(sim: Simulation)¶

Initialize the action for the given simulation.

This is a hook called once at the beginning of the simulation, after the entire network and all core data structures have been set up but before any simulation samples have been run. It can be used to perform any necessary setup before the first call to run. By default, this does nothing, but subclasses can override it if needed.

produces : set[str] = {}¶

should_run(sim: Simulation, days_prior: int) → bool¶: Determine if the action should run on the given days_prior.

snapshot_filter_type : type[GenericSnapshotFilter] = None¶

dcps : set[int]¶: Set of days prior to departure on which to run this action.

carrier¶: The carrier upon which to apply this action.

minimum_sample¶: The minimum sample number before this action will run.

snapshots¶: Optional list of snapshots to grap when running this action.

run(sim: Simulation, days_prior: int)[source]¶

Execute the action for the given simulation.

Subclasses must implement this method.