🚚 Supply Chain & Logistics
Optimizing global logistics with quantum computing
Your Progress
0 / 5 completed←
Previous Module
Materials Science Applications
🌍 The Logistics Challenge
Global logistics moves $10 trillion of goods annually, but inefficiencies cost 20% in wasted fuel, delays, and missed deliveries. The Traveling Salesman Problem (finding optimal routes) is NP-hard—classical computers struggle with just 20 cities. Quantum computing offers exponential speedup for these combinatorial challenges.
💡 The Complexity Problem
With N locations, there are N!/2 possible routes. For 10 cities: 181,440 routes. For 20 cities: 1.2 quintillion. Classical algorithms use heuristics (near-optimal). Quantum optimization explores all possibilities simultaneously via superposition.
Classical (10 cities):
~1 second
Classical (20 cities):
~77,000 years
Quantum (10 cities):
~0.1 second
Quantum (20 cities):
~5 seconds
🎯 What You'll Learn
⚛️
QAOA & Annealing
Quantum optimization algorithms
🚛
Route Optimization
Vehicle routing & scheduling
🏭
Industry Applications
Delivery, airlines, warehouses
💰
Cost Savings
10-30% efficiency gains
📊 Logistics by the Numbers
$10T
Global logistics market
20%
Waste from inefficiency
30%
Quantum improvement