Beating classical heuristics for the binary paint shop problem with the quantum approximate optimization algorithm
نویسندگان
چکیده
The binary paint shop problem (BPSP) is an APX-hard optimization of the automotive industry. In this work, we show how to use quantum approximate algorithm (QAOA) find solutions BPSP. We demonstrate that QAOA with constant depth able beat all known heuristics for on average in infinite size limit $n\ensuremath{\rightarrow}\ensuremath{\infty}$. complete our studies by running first experiments small-sized instances a trapped-ion computer through Amazon Braket.
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15 صفحه اولThe Binary Paint Shop Problem
We consider the binary paint shop problem (PPW(2,1)). We describe an approach to solve PPW(2,1). This approach is based on constructing a logical model for PPW(2,1). Mathematics Subject Classification: 68T20
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ژورنال
عنوان ژورنال: Physical review
سال: 2021
ISSN: ['0556-2813', '1538-4497', '1089-490X']
DOI: https://doi.org/10.1103/physreva.104.012403