Exploring Airline Gate-Scheduling Optimization Using Quantum Computers

TL;DR

This paper explores the potential of quantum computing to optimize airline gate scheduling by adapting classical quadratic assignment problems to quantum algorithms, tested on IBM hardware and simulators.

Contribution

It introduces quantum algorithms for gate scheduling, including variational quantum eigensolvers and graph coloring, tailored for quantum hardware implementation.

Findings

Quantum algorithms successfully tested on small-scale gate scheduling problems.

Demonstrated feasibility of using IBM quantum hardware for combinatorial optimization.

Enhanced quantum algorithms show promise for future larger-scale applications.

Abstract

This paper investigates the application of quantum computing technology to airline gate-scheduling quadratic assignment problems (QAP). We explore the quantum computing hardware architecture and software environment required for porting classical versions of these type of problems to quantum computers. We discuss the variational quantum eigensolver and the inclusion of space-efficient graph coloring to the Quadratic Unconstrained Binary Optimization (QUBO). These enhanced quantum computing algorithms are tested with an 8 gate and 24 flight test case using both the IBM quantum computing simulator and a 27 qubit superconducting transmon IBM quantum computing hardware platform.