EMSR-B with Low Demand¶

In this example, we include product and advance purchase (AP) restrictions in the simulation, and have each airline use the leg-based EMSR-B algorithm to manage revenue. Demand is simulated at a level 50% lower than normal.

In [1]:

import passengersim as pax
pax.versions()

import passengersim as pax pax.versions()

passengersim 0.18.1
passengersim.core 0.18.1

The yaml file for this example contains an explicit include instruction directly in the file. This emulates calling multiple file names in the from_yaml command, but the other file references are written directly into the code, so that groups of configurations can be managed together easily, without necessarily needing the user to carefully assemble the correct set of filenames every time they run the simulation.

In [2]:

from passengersim.utils.codeview import show_file
show_file("network/04-emsrb-low-demand.yaml")

from passengersim.utils.codeview import show_file show_file("network/04-emsrb-low-demand.yaml")

include:
  - 01-base.yaml
  - 02-buyup.yaml
  - 03-ap.yaml

simulation_controls:
  demand_multiplier: 0.5

airlines:
  - name: AL1
    rm_system: rm_no_detruncation
  - name: AL2
    rm_system: rm_no_detruncation

In [3]:

sim = pax.Simulation.from_yaml([
    "network/04-emsrb-low-demand.yaml",
])

sim = pax.Simulation.from_yaml([ "network/04-emsrb-low-demand.yaml", ])

In [4]:

summary = sim.run()

summary = sim.run()

Task Completed after 17.43 seconds

In [5]:

summary.fig_carrier_revenues()

summary.fig_carrier_revenues()

Out[5]:

In [6]:

summary.fig_carrier_load_factors()

summary.fig_carrier_load_factors()

Out[6]:

In [7]:

summary.fig_fare_class_mix()

summary.fig_fare_class_mix()

Out[7]:

In [8]:

summary.fig_bookings_by_timeframe()

summary.fig_bookings_by_timeframe()

Out[8]:

In [9]:

summary.to_xlsx("outputs/3mkt-04.xlsx")

summary.to_xlsx("outputs/3mkt-04.xlsx")

Download 3mkt-04.xlsx

Comparing against Targets¶

In [10]:

import targets

target = targets.load(4, sim.config)

import targets target = targets.load(4, sim.config)

In [11]:

from passengersim import contrast

comps = contrast.Contrast({
    "simulation": summary,
    "target": target,
})

from passengersim import contrast comps = contrast.Contrast({ "simulation": summary, "target": target, })

In [12]:

comps.fig_carrier_revenues()

comps.fig_carrier_revenues()

Out[12]:

In [13]:

comps.fig_carrier_load_factors()

comps.fig_carrier_load_factors()

Out[13]:

In [14]:

comps.fig_fare_class_mix()

comps.fig_fare_class_mix()

Out[14]:

In [15]:

comps.fig_bookings_by_timeframe(by_carrier="AL1", by_class=True)

comps.fig_bookings_by_timeframe(by_carrier="AL1", by_class=True)

Out[15]: