Constructing selection hyper-heuristics for open vehicle routing with time delay neural networks using multiple experts Article Swipe
Raras Tyasnurita
,
Ender Özcan
,
John H. Drake
,
Shahriar Asta
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.knosys.2024.111731
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.knosys.2024.111731
Hyper-heuristics are general purpose search methods for solving computationally difficult problems. A selection hyper-heuristic is composed of two key components: a heuristic selection method and move acceptance criterion. Under an iterative single-point search framework, a solution is modified by selecting and applying a predefined low-level heuristic, with a decision then taken to accept or reject the resulting solution. Designing a selection hyper-heuristic is an extremely challenging task. In this study, we investigate computer-aided design of a selection hyper-heuristic for the open vehicle routing problem. A time delay neural network is used as an offline apprenticeship learning method. Our approach first observes the search behaviour of multiple expert human-designed selection hyper-heuristics on a selected sample of training instances, before automatically generating a selection hyper-heuristic capable of solving unseen instances effectively. The proposed approach is tested on open vehicle routing problem instances of different sizes to examine the performance and generality of the selection hyper-heuristics generated. Improved performance is demonstrated over a set of well-known benchmarks from the literature when compared to using the existing expert systems directly.
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- Type
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- Language
- en
- Landing Page
- https://doi.org/10.1016/j.knosys.2024.111731
- OA Status
- hybrid
- Cited By
- 9
- References
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- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4394912678Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.knosys.2024.111731Digital Object Identifier
- Title
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Constructing selection hyper-heuristics for open vehicle routing with time delay neural networks using multiple expertsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-04-18Full publication date if available
- Authors
-
Raras Tyasnurita, Ender Özcan, John H. Drake, Shahriar AstaList of authors in order
- Landing page
-
https://doi.org/10.1016/j.knosys.2024.111731Publisher landing page
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://doi.org/10.1016/j.knosys.2024.111731Direct OA link when available
- Concepts
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Heuristics, Selection (genetic algorithm), Computer science, Vehicle routing problem, Routing (electronic design automation), Artificial neural network, Artificial intelligence, Machine learning, Computer network, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
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9Total citation count in OpenAlex
- Citations by year (recent)
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2025: 8, 2024: 1Per-year citation counts (last 5 years)
- References (count)
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101Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| referenced_works_count | 101 |
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