SSBLP¶

class passengersim.rm.linear_program.SSBLP(_carrier: str, *, num_samples: int = 3, max_dcp_index: int = 16, by_timeframe: bool = True, print_timings: bool = False, debug: bool = False)[source]¶

Bases: LpBase

Stochastic Sales-Based LP, following [Ratliff 2025] - Probably not the most efficient code to setup the LP, but it

lets me follow the formulation line-by-line

Methods

__init__(_carrier, *[, num_samples, ...])
create_OA_variables(eng, mkt_key)
create_balance_constraints_x(eng, mkt_key, ...)
create_balance_constraints_y(eng, mkt_key, ...)
create_capacity_constraints(eng)
create_decision_variables(eng, mkt_key, mkt, ...)
create_nesting_constraints(eng, mkt_key, path)
create_scale_constraints_x(eng, mkt_key, ...)
create_scale_constraints_y(eng, mkt_key, ...)
initialize(eng)
solve(eng[, debug])	Solve the LP and write dual values (displacement costs / bid prices) back to each leg.
test_status(status, eng[, debug])
update(eng)

Attributes

carrier
solver
objective
lp_vars
constraints
epsilon
num_samples
set_bp
debug

carrier¶

debug¶

solver¶

lp_vars¶

num_samples¶

objective¶

initialize(eng: SimulationEngine)[source]¶

create_decision_variables(eng, mkt_key, mkt, revenue_c)[source]¶

create_OA_variables(eng, mkt_key)[source]¶

create_nesting_constraints(eng, mkt_key, path)[source]¶

create_balance_constraints_y(eng, mkt_key, mkt, dmd_info)[source]¶

create_balance_constraints_x(eng, mkt_key, mkt, dmd_info)[source]¶

create_scale_constraints_y(eng, mkt_key, mkt, dmd_info)[source]¶

create_scale_constraints_x(eng, mkt_key, mkt, dmd_info)[source]¶

create_capacity_constraints(eng)[source]¶

update(eng: SimulationEngine)[source]¶

constraints¶

epsilon¶

set_bp¶

solve(eng: SimulationEngine, debug: bool = False)[source]¶

Solve the LP and write dual values (displacement costs / bid prices) back to each leg.

test_status(status, eng, debug=False)¶