Condensed Matter > Statistical Mechanics
[Submitted on 28 Mar 2024 (v1), last revised 14 Jul 2024 (this version, v2)]
Title:Toward Practical Benchmarks of Ising Machines: A Case Study on the Quadratic Knapsack Problem
View PDF HTML (experimental)Abstract:Combinatorial optimization has wide applications from industry to natural science. Ising machines bring an emerging computing paradigm for efficiently solving a combinatorial optimization problem by searching a ground state of a given Ising model. Current cutting-edge Ising machines achieve fast sampling of near-optimal solutions of the max-cut problem. However, for problems with additional constraint conditions, their advantages have been hardly shown due to difficulties in handling the constraints. In this work, we focus on benchmarks of Ising machines on the quadratic knapsack problem (QKP). To bring out their practical performance, we propose fast two-stage post-processing for Ising machines, which makes handling the constraint easier. Simulation based on simulated annealing shows that the proposed method substantially improves the solving performance of Ising machines and the improvement is robust to a choice of encoding of the constraint condition. Through evaluation using an Ising machine called Amplify Annealing Engine, the proposed method is shown to dramatically improve its solving performance on the QKP. These results are a crucial step toward showing advantages of Ising machines on practical problems involving various constraint conditions.
Submission history
From: Kentaro Ohno [view email][v1] Thu, 28 Mar 2024 06:51:08 UTC (2,828 KB)
[v2] Sun, 14 Jul 2024 07:07:07 UTC (2,788 KB)
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