Analysing heuristic subsequences for offline hyper-heuristic learning
Yates, W; Keedwell, EC
Date: 13 July 2019
Publisher
Association for Computing Machinery (ACM)
Publisher DOI
Abstract
The paper explores the impact of sequences of search operationson the performance of an optimiser through the use of log returnsand a database of sequences. The study demonstrates that althoughthe performance of individual perturbation operators is important,understanding their performance in sequence provides greater op-portunity for ...
The paper explores the impact of sequences of search operationson the performance of an optimiser through the use of log returnsand a database of sequences. The study demonstrates that althoughthe performance of individual perturbation operators is important,understanding their performance in sequence provides greater op-portunity for performance improvements within and across opera-tions research domains.
Computer Science
Faculty of Environment, Science and Economy
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