Multi-Objective Problem Solving With Offspring on Enterprise Clouds
| Publication Type | Journal Article | |
| Year of Publication | 2009 | |
| Authors | Vecchiola, Christian; Kirley, Michael; Buyya, Rajkumar | |
| Journal Date | Mar | |
| Key Words | cloud; computing | |
| Abstract | In this paper, we present a distributed implementation of a network based multi-objective evolutionary algorithm, called EMO, by using Offspring. Network based evolutionary algorithms have proven to be effective for multi-objective problem solving. They feature a network of connections between individuals that drives the evolution of the algorithm. Unfortunately, they require large populations to be effective and a distributed implementation can leverage the computation time. Most of the existing frameworks are limited to providing solutions that are basic or specific to a given algorithm. Our Offspring framework is a plug-in based software environment that allows rapid deployment and execution of evolutionary algorithms on distributed computing environments such as Enterprise Clouds. Its features and benefits are presented by describing the distributed implementation of EMO. | |
| URL | http://arxiv.org/abs/0903.1386 | |
| Export | Tagged XML BibTex |

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