Sampled Walk and Binary Fitness Landscapes Exploration
| Autor: | Adrien Goëffon, Sara Tari, Matthieu Basseur |
|---|---|
| Přispěvatelé: | Laboratoire d'Etudes et de Recherche en Informatique d'Angers (LERIA), Université d'Angers (UA), Univ Angers, Okina |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Optimization problem
Theoretical computer science business.industry Computer science Iterated local search Fitness landscape 05 social sciences 050301 education Binary number Sample (statistics) 02 engineering and technology [INFO] Computer Science [cs] Tabu search Search algorithm 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Local search (optimization) [INFO]Computer Science [cs] business 0503 education |
| Zdroj: | International Conference on Artificial Evolution (EA) International Conference on Artificial Evolution (EA), 2017, Paris, France. pp.53-64 Lecture Notes in Computer Science ISBN: 9783319781327 Artificial Evolution |
| Popis: | In this paper we present and investigate partial neighborhood local searches, which only explore a sample of the neighborhood at each step of the search. We particularly focus on establishing link between the structure of optimization problems and the efficiency of such local search algorithms. In our experiments we compare partial neighborhood local searches to state-of-the-art tabu search and iterated local search and perform a parameter sensitivity analysis by observing the efficiency of partial neighborhood local searches with different size of neighborhood sample. In order to facilitate the extraction of links between instances structure and search algorithm behavior we restrain the scope to binary fitness landscapes, such as NK landscapes and landscapes derived from UBQP. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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