Quantum Computing might help companies paint…cars. Optimization problems of the Auto Industry can be tackled with Quantum Algorithms

Quantum Optimization has already been demonstrated for routing, but in many settings, there is a need to efficiently allocate resources and perform actions accordingly. It should be therefore no surprise that industrialists around the globe are looking to Quantum to provide an efficiency edge. In a recent article, a generalization of the binary paint shop problem (BPSP) to tackle an automotive industry application, the multi-car paint shop (MCPS) problem is highlighted. The objective of the optimization is to minimize the number of colour switches between cars in a paint shop queue during manufacturing, a known NP-hard problem in mathematics.

In the paper: “Multi-car paint shop optimization with quantum annealing”, the multi-disciplined team from auto giant VW, study real-world data from an actual factory from Wolfsburg, Germany (the headquarters of VW and where they build many of their cars). The team compare the performance of the D-Wave 2000Q and Advantage quantum processors to other classical solvers and a hybrid quantum-classical algorithm offered by D-Wave Systems

Read the article here.