Hybrid Multi-objective Workflow Scheduling on Utility Grids
Workflow scheduling is solved using heuristics and meta heuristics. Heuristics are problem-dependent techniques. Meta heuristics are general purpose method of solving different types of problem. It can be single objective or multiple objectives. This paper focuses on our proposed algorithm named as...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2014 |
| País: | Brasil |
| Institución: | Universidade Federal de Lavras (UFLA) |
| Repositorio: | INFOCOMP: Jornal de Ciência da Computação |
| Idioma: | inglés |
| OAI Identifier: | oai:infocomp.dcc.ufla.br:article/18 |
| Acceso en línea: | https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/18 |
| Access Level: | acceso abierto |
| Palabra clave: | NSGA-II hybrid ranking workflow scheduling |
| Sumario: | Workflow scheduling is solved using heuristics and meta heuristics. Heuristics are problem-dependent techniques. Meta heuristics are general purpose method of solving different types of problem. It can be single objective or multiple objectives. This paper focuses on our proposed algorithm named as Double Hybrid NSGA-II Algorithm (DHNSGA-II) that improves up the convergence of the NSGA-II algorithm by employing Pre-selection and Memetic algorithms. DHNSGA-II does hybridization at two levels. At the first level, it uses Pre-selection operator and the second level it uses Memetic algorithm. Pre-selection operator seeds the DHNSGA-II with the previously generated solutions. Memetic algorithm improves the current population using multi-objective local search. Apart from DHSNGA-II we introduced an approach to rank the Pareto frontiers because Pareto frontier has many solutions; it is nearly impossible to choose the best solution. The experimental result reveals that the proposed approach in this research performs well in optimizing the workflow scheduling jobs. |
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