A symbolic approach to discrete structural optimization using quantum annealing

TL;DR

This paper explores translating a 2D truss optimization problem into a QUBO format suitable for quantum annealing, demonstrating feasibility but noting scalability challenges for larger systems.

Contribution

It introduces a method to convert discrete structural optimization problems into QUBO form for quantum annealing applications.

Findings

Feasibility of translating truss optimization to QUBO format

Successful solution of small-scale problems using quantum annealing

Scalability issues identified for larger truss systems

Abstract

With the advent of novel quantum computing technologies, and the knowledge that such technology might be used to fundamentally change computing applications, a prime opportunity has presented itself to investigate the practical application quantum computing. The goal of this research is to consider one of the most basic forms of mechanical structure, namely a 2D system of truss elements, and find a method by which such a structure can be optimized using quantum annealing. The optimization will entail a discrete truss sizing problem - to select the best size for each truss member so as to minimize a stress-based objective function. To make this problem compatible with quantum annealing devices, it will be written in a QUBO format. This work is focused on exploring the feasibility of making this translation, and investigating the practicality of using a quantum annealer for structural optimization problems. Using the methods described, it is found that it is possible to translate this traditional engineering problem to a QUBO form and have it solved by a quantum annealer. However, scaling the method to larger truss systems faces some challenges that would require further research to address.