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Particle swarm optimization with thresheld convergence

Chen, Stephen; Montgomery, James

Description

Many heuristic search techniques have concurrent processes of exploration and exploitation. In particle swarm optimization, an improved 'pbest' position can represent a new more promising region of the search space (exploration) or a better solution within the current region (exploitation). The latter can interfere with the former since the identification of a new more promising region depends on finding a (random) solution in that region which is better than the current 'pbest'. Ideally, every...[Show more]

CollectionsANU Research Publications
Date published: 2013
Type: Conference paper
URI: http://hdl.handle.net/1885/9936
Source: 2013 IEEE Congress on Evolutionary Computation
DOI: 10.1109/CEC.2013.6557611

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