ProBP Optimization¶

In [1]:

from textwrap import fill

import passengersim as pax

pax.versions()

from textwrap import fill import passengersim as pax pax.versions()

passengersim 0.51.dev11+g921f2a8
passengersim.core 0.51.dev2+g02d3ce20

In [2]:

cfg = pax.Config.from_yaml(pax.demo_network("3MKT"))

cfg = pax.Config.from_yaml(pax.demo_network("3MKT"))

In [3]:

cfg.carriers.AL1.rm_system = "P"
cfg.carriers.AL2.rm_system = "E"

cfg.simulation_controls.num_trials = 1
cfg.simulation_controls.num_samples = 600

cfg.outputs.reports.clear()
cfg.db = None

cfg.carriers.AL1.rm_system = "P" cfg.carriers.AL2.rm_system = "E" cfg.simulation_controls.num_trials = 1 cfg.simulation_controls.num_samples = 600 cfg.outputs.reports.clear() cfg.db = None

In [4]:

cfg = cfg.model_revalidate()

cfg = cfg.model_revalidate()

In [5]:

print(fill(cfg.rm_systems.E.description))

print(fill(cfg.rm_systems.E.description))

Leg-based additive pickup forecast, EM detruncation, EMSR-B
optimization.

In [6]:

print(fill(cfg.rm_systems.P.description))

print(fill(cfg.rm_systems.P.description))

Path-based additive pickup forecast, EM detruncation, ProBP
optimization.

In [7]:

sim = pax.Simulation(cfg)

sim = pax.Simulation(cfg)

In [8]:

summary = sim.run()

summary = sim.run()

Task Completed after 3.08 seconds

In [9]:

summary.fig_carrier_revenues()

summary.fig_carrier_revenues()

Out[9]:

In [10]:

summary.fig_carrier_load_factors()

summary.fig_carrier_load_factors()

Out[10]:

In [11]:

summary.fig_carrier_rasm()

summary.fig_carrier_rasm()

Out[11]:

In [12]:

summary.fig_fare_class_mix()

summary.fig_fare_class_mix()

Out[12]:

In [13]:

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

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

Out[13]:

In [14]:

summary.fig_carrier_head_to_head_revenue("AL1", "AL2")

summary.fig_carrier_head_to_head_revenue("AL1", "AL2")

Out[14]:

In [15]:

summary.fig_select_leg_analysis(101)

summary.fig_select_leg_analysis(101)

Out[15]: