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Business Impact of Quantum Optimization in Trajectory Planning

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Challenges
  • Optimizing airline routes by considering deconflicting measures and maintaining safe trajectory radius between each flight is a complex problem taking into account altitude, speed, weather, and route restrictions  
  • Existing approaches do not scale well for a large number of variables and constraints.

Results

BQPhy's QIO Optimization solver achieved optimal flight pathsexploring global minima for over 100 flights across Europe

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Comparing with classical algorithms, BQPhy QIO reduced

  • CO2 emissions by 18% (220,000 kg),
  • fuel consumption by 4% (USD 70,000 savings),
  • and flight time by 1% (6.5 hours)  

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Comparing with classical algorithms, BQPhy QIO reduced

Emissions Reduced 220,000 kg

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Savings of USD 70,000
Flight time saved 6.5 hours
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