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A model of swarm intelligence based optimization framework adjustable according to problems
Swarm Intelligence has been a popular sub-field of Artificial Intelligence as including intelligent approaches, methods, and techniques for optimization problems. When the associated literature is examined, it can be seen that there are lots of different Swarm Intelligence techniques and researchers are still in an unstoppable interest in designing and developing newer ones. At this point, it is possible to imagine a general Swarm Intelligence system combining all developed techniques to enable researchers, who just want to solve their optimization problems with necessary features and functions. In this context, objective of this study is to introduce essentials of a modular framework, which is currently being developed for such purposes. The system introduced here consists of feature and function sets of different Swarm Intelligence techniques and employs an adaptive, adjustable infrastructure, which is also improved by additions of new techniques and results regarding to performed optimization tasks. © Springer International Publishing AG 2018.
Springer Science and Business Media Deutschland GmbH
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