How does the choice of rollout strategy affect the performance of deterministic algorithms in combinatorial optimization?
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The choice of rollout strategy can significantly affect the performance of deterministic algorithms in combinatorial optimization. Rollout algorithms, which estimate the value-to-go at each decision stage by simulating future events while following a heuristic policy, have shown excellent performance on dynamic and discrete optimization problems . In the context of deterministic problems, the rollout algorithm can be used as an approximate dynamic programming algorithm, where the base heuristic policy plays a crucial role. The performance improvement of the rollout algorithm over the base policy has been theoretically proven in certain cases, such as the subset sum problem and 0-1 knapsack problem . Additionally, the use of rollout algorithms in constrained deterministic dynamic programming problems, including combinatorial optimization problems, has been explored, showing that the rollout algorithm can produce feasible solutions with improved costs compared to the base heuristic .
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| The provided paper does not discuss the performance of deterministic algorithms in combinatorial optimization or the effect of rollout strategy on their performance. | |
Open access•Posted Content | The paper does not directly address the impact of the choice of rollout strategy on the performance of deterministic algorithms in combinatorial optimization. |
15 Dec 2022 | The provided paper does not discuss the performance of deterministic algorithms in combinatorial optimization or the effect of rollout strategy on their performance. |
01 Aug 2021 | The provided paper does not discuss the performance of deterministic algorithms in combinatorial optimization or the effect of the choice of rollout strategy on their performance. |
3 Citations | The provided paper does not discuss the performance of deterministic algorithms in combinatorial optimization or the effect of rollout strategy on it. |
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