Qiskit Implementation and Study: Optimizing Maritime Routing problems

[Travis-S-IBM]

Description

Several years ago, IBM Quantum researchers -- in collaboration with ExxonMobil -- studied how to formulate a particular optimization problem in a quantum-computing-friendly way. That work, Formulating and Solving Routing Problems on Quantum Computers, explored various formulations of the problem, examined the quantum compute resources required, and did some simple numerical simulations to validate both the formulations proposed, and various quantum algorithms for solving the resulting optimization problems.

IIRC, at the time, neither Qiskit Optimization nor Qiskit Runtime existed.

Along with you, I'd like to go back to this work, take some pieces of it, implement those pieces using the help of the Qiskit Optimization module and Qiskit Runtime, and run experiments on hardware, to get a better sense of what's needed -- in practice -- to tackle this routing problem at scale (large numbers of variables). Note that Qiskit Optimization is Runtime-enabled, so you won't be expected to implement interfaces between these two pieces of SW (unless there are gaps that we need to close for the purposes of the project).

I do not intend to re-implement the entire paper; instead, I'd want to figure out what piece(s) would make sense to be cobbled together for the purposes of this project.

Deliverables

For the project:

• Code that can take instances of at least 1 of the formulations, produce QUBOs, and solve those QUBOs using hardware
• Numerical results showing the quantum compute time required as a function of instance size (i.e., runtime scaling)
• A blog post or other writeup

For you:

• Growth in your ability to read and understand a research paper
• Growth in your ability to use Qiskit Optimization & Qiskit Runtime
• A better understanding of the quantum computing industry

For me:

• Learning more about quantum optimization
• Getting a better handle on the quantum/classical resources required to address this (and similar) problems at scale
• Validating some other hypotheses I have

Mentors details

• Mentor 1
  • Name: Travis L Scholten (http://travisscholten.com/)
  • GitHub ID: https://github.com/Travis-S-IBM
  • What they do: Quantum Applications Architect

Number of mentees

1

Type of mentees

• Mentee 1
  • Required:
  • Proficient with Qiskit
  • Some prior exposure to research
  • A willingness to learn and grow
  • Nice to have:
  • Prior use of Qiskit Optimization
  • Prior use of Qiskit Runtime
  • Prior research output

If additional mentees wanted to participate, the profile would be the same.

[MarcoBarroca]

I'm interested in this and I have experience with Qiskit-runtime. Also, I like working on applications, currently my research is in chemistry applications using qiskit-nature.

I feel like this could help me become more familiar with other qiskit modules.

[ritu-thombre99]

This looks very interesting. I have studied routing problem during my undergrad senior year, and I have experience with Qiskit. I also participated and completed QAMP Fall 22 under James Weaver to develop quantum version of Nim (QNim) game using pygame and qiskit.

Hope we can connect soon to discuss more about this project.

[pranshi24yati]

Hello, I am interested in working on this project. At present, I am working as a QML Researcher at Deloitte, and I have previously worked on some optimization problems like Portfolio Optimization, Employee Scheduling Optimization and currently I am benchmarking Vehicle Routing Optimization on gurobi/qiskit/dwave I was also mentee for QAMP 2022, where I worked on I worked on redesigning Transpiler for Qiskit Terra. Looking forward to connect with you and work on this project.

[Qcatty]

Hey, I am working on solving VRP with F-VQE with Qworld Reaearch, I am interested about this project!

[GemmaDawson]

This project will not be going forward at this time.