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Large-scale global optimization is a challenging task which is embedded in many scientific and engineering applications. Among large scale problems, multimodal functions present an exceptional challenge because of the need to promote exploration. In this paper we present a hybrid heuristic specifically designed for optimizing large scale multimodal functions. The hybrid is based on the unbiased exploration...
Multi-swarm systems base their search on multiple sub-swarms instead of one standard swarm. The use of diverse sub-swarms increases performance when optimizing multi-modal functions. However, new design decisions arise when implementing multi-swarm systems such as how to select the initial positions and initial velocities, and how to coordinate the different sub-swarms. Starting from the relatively...
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