Transportation recovery

Description

This analysis computes the damage to bridges, first calling the bridge damage analysis. It then uses nodes and links in transportation path and Average Daily Traffic (ADT) data of bridges to calculate a transportation network post-disaster recovery. Additionally, the analysis can be used in stochastic calculations with an integer value being imported to seed the random number generator.

The output of this analysis is a CSV file with recovery trajectory timelines and data.

Input Parameters

key name	type	name	description
pm *	int	Performance metrics	Name of the result dataset.
ini_num_population *	int	Population number	An initial population number.
population_size *	int	Population size	A population size.
num_generation *	int	Number generation	Number of iterations per scenario.
mutation_rate *	float	Mutation rate	Mutation rate for the NSGA-II algorithm used for recovery rate.
crossover_rate *	float	Crossover rate	Crossover rate for the NSGA-II algorithm used for recovery rate.
num_cpu	int	Number of CPUs	Number of CPUs used for parallel computations. Default 1.

Input Datasets

key name	type	name	description
bridges *	ergo:bridges	Bridge dataset	A bridge dataset.
nodes *	ergo:roadNetwork	Rad nodes	A road network dataset.
links *	ergo:roadNetwork	Road links	A road network dataset.
bridge_damage_value *	incore:bridgeDamageValue	Bridge damages	A bridge dataset.
unrepaired_bridge *	incore:unrepairedBridge	Unrepaired bridges	An unrepaired bridge dataset.
ADT *	incore:ADT	Bridge traffic	A dataset of daily traffic.

Output Datasets

key name	type	name	description
optimal_solution_of_bridge_repair_schedule *	incore:transportationRepairSchedule	Repair schedule	A dataset containing results (format: CSV).
overall_transportation_recovery_trajectory *	incore:transportationRecovery	Recovery trajectory	A dataset containing results (format: CSV).

(* required)

Execution

code snippet:

    # Create transportation recovery instance
    transportation_recovery = TransportationRecovery(client)

    # Load input datasets
    transportation_recovery.load_remote_input_dataset("nodes", nodes)
    transportation_recovery.load_remote_input_dataset("links", links)
    transportation_recovery.load_remote_input_dataset('bridges', bridges)
    transportation_recovery.load_remote_input_dataset('bridge_damage_value', bridge_damage)
    transportation_recovsery.load_remote_input_dataset('unrepaired_bridge', unrepaired)
    transportation_recovery.load_remote_input_dataset('ADT', ADT_data)

    # Set analysis parameters
    transportation_recovery.set_parameter("num_cpu", 4)
    transportation_recovery.set_parameter("pm", 1)
    transportation_recovery.set_parameter('ini_num_population', 5)
    transportation_recovery.set_parameter("population_size", 3)
    transportation_recovery.set_parameter("num_generation", 2)
    transportation_recovery.set_parameter("mutation_rate", 0.1)
    transportation_recovery.set_parameter("crossover_rate", 1.0)

    # Run transportation recovery analysis
    transportation_recovery.run_analysis()

full analysis: transportation_recovery.ipynb