Evacuation and Logistics Planning Project

Evacuation Network Diagram

Project Overview

This project develops a comprehensive evacuation model using a directed graph to optimize the routing and resource allocation for individuals and families needing to evacuate from a crisis-stricken country. The model addresses one of the most critical challenges in emergency management: efficiently moving large populations to safety while minimizing travel time and maximizing operational effectiveness.

By leveraging advanced operations research techniques and optimization algorithms, this simulation provides actionable insights for strategic planning and decision-making during critical emergency evacuations.

Network Architecture

3

Primary Locations

Initial evacuation points where individuals and families begin their journey

9

Intermediate Stops

Transit hubs that facilitate distribution and resource management

4

Final Destinations

Safe zones where evacuees reach their ultimate destination

Network Design Principles

  • Primary locations feed into multiple intermediate stops to distribute load
  • Each node in the network is actively utilized to prevent bottlenecks
  • Intermediate stops connect to final destinations with capacity constraints
  • Network structure ensures redundancy and alternative routing options

Optimization Objectives

Minimize Travel Time

Optimize routing to reduce total evacuation time while considering road conditions, traffic patterns, and transportation capacity.

Maximize Safety

Prioritize routes that avoid high-risk areas while ensuring adequate security and medical support at each node.

Balance Resource Allocation

Distribute evacuees efficiently across available transportation and shelter resources to prevent overcrowding at any single location.

Maintain Network Flow

Ensure continuous movement through the network while adhering to capacity constraints at each node and edge.

Model Features

Directed Graph Modeling

Network flow optimization using graph theory principles

Capacity Constraints

Real-world limitations on transportation and shelter resources

Multi-Stage Routing

Three-tier network structure for flexible evacuation planning

Bottleneck Identification

Automatic detection of potential choke points in the network

Real-World Applications

Emergency Response Planning

Government agencies and humanitarian organizations can use this model to prepare for natural disasters, conflicts, or other crisis situations requiring mass evacuations.

Military Operations

Optimize troop and civilian movements during non-combatant evacuation operations (NEO) or humanitarian assistance missions.

Disaster Relief Logistics

Coordinate the distribution of aid supplies and personnel through multi-stage logistics networks in disaster-affected regions.

Technical Implementation

Technologies Used

Python
NetworkX
SciPy
Matplotlib
OR-Tools
Pandas

View Full Implementation

Explore the complete optimization model with code, visualizations, and detailed analysis.