.png){kind=icon}
.png){kind=icon}
Return
Moderate exponential-time quantum dynamic programming across the subsets for scheduling problems
.png){kind=icon}
OA
AI
DOI：10.1016/j.ejor.2024.09.005.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Grover Search is currently one of the main quantum algorithms leading to hybrid quantum-classical methods that reduce the worst-case time complexity for some combinatorial optimization problems. Specifically, the combination of Quantum Minimum Finding (obtained from Grover Search) with dynamic programming has proved particularly efficient in improving the complexity of NP-hard problems currently solved by classical dynamic programming. For these problems, the classical dynamic programming complexity in O-& lowast;(c(n)), where O-& lowast; denotes that polynomial factors are ignored, can be reduced by a hybrid algorithm to O-& lowast;(c(quant)(n)), with c(quant)
Keywords:
Discrete optimization
Quantum computing
Scheduling
Dynamic programming
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
6
Papers:
2.2W
Citations:
6.4W