Datasets:

alirezaaminzadeh
/

reliefopt-sample-scenarios

crisis stringclasses 7 values	stress stringclasses 6 values	strategy stringclasses 7 values	population_coverage_pct float64 0 400	worst_region_service_pct float64 0 84.1	avg_response_time_hours float64 0 0.17	cvar_shortage float64 87.4 1.14k	fairness_gap float64 0 100	total_cost float64 29.7k 91.5k	solve_time_sec float64 0 0.64
natural_disaster	baseline	two_stage_stochastic	392.3	67.5	0.15	372.1	32.5	80,909.62	0.001369
pandemic_response	demand_uncertainty_high	progressive_hedging	386.7	75	0.14	138.5	25	75,460.05	0.005809
supply_chain_disruption	limited_fleet	min_cost_flow	0	0	0	978.2	0	73,178.75	0.002692
infrastructure_failure	road_network_damage	robust_routing	400	82.2	0.16	154	17.8	33,659.55	0.001721
drug_shortage	facility_damage	inventory_preposition	400	75	0.13	87.4	25	71,311.39	0.002233
emergency_repair	weather_disruption	facility_location	400	84.1	0.17	202.1	15.9	29,681.6	0.001273
demand_surge	baseline	nsga_multi_objective	315.8	0	0.16	1,138.2	100	91,512.21	0.640401

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Check out the documentation for more information.

ReliefOpt Sample Crisis Scenarios

Synthetic humanitarian logistics scenarios for ReliefOpt benchmarking.

File	Crisis	Stress	Algorithm
`sample_natural_disaster.json`	Natural disaster	Baseline	Two-stage stochastic
`sample_pandemic_response.json`	Pandemic	High uncertainty	Progressive hedging
`sample_supply_chain_disruption.json`	Supply chain	Limited fleet	Min-cost flow
`sample_infrastructure_failure.json`	Infrastructure	Road damage	Robust routing
`sample_drug_shortage.json`	Drug shortage	Facility damage	Prepositioning
`sample_emergency_repair.json`	Emergency repair	Weather	Facility location
`sample_demand_surge.json`	Demand surge	Baseline	NSGA-II

Gradio console available at space-bundle/ for manual Space deployment.