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@Q-Zee

Quzzi

Q-Zee
Canada

Dear sponsors...

The advent of Quantum Annealing technology has ignited my interest to model solvers, using Quantum Annealing, capable of solving real-world hard airline optimization problems. Along the way, it became apparent that all industries beyond airlines can benefit from this technology.

The creation of a proof-of-concept Airline Crew Trip solver demonstrate this technology's capabilities. Even in its infancy, it offers promising results, usable today, and commands further expansion.

Successes thus far

The prototype was instrumental to a successful graduation at the CDL Toronto Quantum Stream in June 2021 as one of the 10 successful Quantum Computing project candidates, leading to the creation of VYouPointAero, which implemented the Quzzi Trip Solver prototype in its MVP in 2021.

Why start with airline use cases?

Airlines, as with many other transportation industry companies, encounter a rich variety of hard problems to solve, day to day, for which existing Classical solvers continue to struggle limited by time and power.

What does the airline industry think about using Quantum Computing today?

A recent Airline Group of the International Federation of Operational Research Societies (AGIFORS) conference (June 2021) revealed that the airline industry is currently generally unaware of the accessibility of Quantum Annealing technology today and there exists a perception that all Quantum technologies will only be usable in 7 to 10 years from today (2021).

This may not be entirely true in relation to Quantum Annealing, a specialized application of Quantum focused on optimization, commercially available today. The work published on Quzzi is demonstrating early results and aims at publishing more examples applicable to more industries and businesses.

Calling for your support

There is much work ahead and we need the help of supporters who would like to benefit from this work or merely encourage it to flourish.

Thank you in advance to all your support and contributions to the work!

2 sponsors have funded Q-Zee’s work.

@Q-Zee

Strength in numbers! Aiming for a good sponsor base to add useful contents for those wanting to solve or learn to solve difficult optimization problems using quantum computing for your industry of interest, including airlines, own initial focus. Every little bit counts! Thank you in advance.

Private Sponsor
@Zykap

Featured work

  1. Q-Zee/Q-Zee

    Config files for my GitHub profile.

  2. Q-Zee/DWave

    DWave Quantum Annealing Solvers

    Python 3

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