Learning ensembles of priority rules for online scheduling by hybrid evolutionary algorithms
| Autor: | María Sierra, Carlos Mencía, Francisco J. Gil-Gala, Ramiro Varela |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Operations research Computer science Evolutionary algorithm 02 engineering and technology Computer Science Applications Theoretical Computer Science Scheduling (computing) Scholarship 020901 industrial engineering & automation Computational Theory and Mathematics Artificial Intelligence 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Software |
| Zdroj: | RUO: Repositorio Institucional de la Universidad de Oviedo Universidad de Oviedo (UNIOVI) RUO. Repositorio Institucional de la Universidad de Oviedo Universidad de las Islas Baleares |
| ISSN: | 1875-8835 1069-2509 |
| DOI: | 10.3233/ica-200634 |
| Popis: | This paper studies the computation of ensembles of priority rules for the One Machine Scheduling Problem with variable capacity and total tardiness minimization. Concretely, we address the problem of building optimal ensembles of priority rules, starting from a pool of rules evolved by a Genetic Programming approach. Building on earlier work, we propose a number of new algorithms. These include an iterated greedy search method, a local search algorithm and a memetic algorithm. Experimental results show the potential of the proposed approaches. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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