HUMANITARIAN LOGISTICS · CRISIS RESPONSE · FAIR ALLOCATION

Humanitarian Logistics and Emergency Response Optimizer

Two-stage stochastic programming, max-min fair allocation, robust routing under network damage, chance-constrained inventory prepositioning, and NSGA-II multi-objective optimization for crisis logistics.

Dataset Solver Config Gradio Bundle

Algorithms

Crisis Types

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Avg Coverage %

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Worst Service %

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Avg Fairness Gap

Two-Stage Decision Model

Pre-Crisis — Warehouse & Inventory

Stochastic facility location for pre-positioned warehouses
Chance-constrained inventory prepositioning
Transport contract capacity planning
Scenario reduction for stochastic programming

Post-Crisis — Allocation & Routing

Max-min fair resource distribution
Robust routing under link survivability constraints
Temporary relief center placement
Service prioritization for urgent casualties

Scenario Explorer

Pre-computed optimization results. Select a crisis scenario.

Crisis:

Benchmark Summary

Crisis	Stress	Coverage %	Worst Svc %	Response (h)	Fairness Gap	Cost ($)	Solve (s)

Stack

Two-Stage Stochastic · Max-Min Fair · NetworkX Min-Cost Flow · Robust Routing · pymoo NSGA-II · Progressive Hedging · Plotly Maps · Gradio console (bundled)