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A Novel Smart Multi-Objective Particle Swarm Optimisation Using Decomposition

The originality stems from applying the idea of simultaneously searching for solutions to multi-objective optimization problems by using particle swarms. In addition, a novel approach for sharing information between particles was proposed, which led to a significant improvement in performance. The rigour of this work is demonstrated by a thorough analysis of the algorithm’s performance on the state-of-the-art benchmark of test optimisation problems. The work led to the development of more efficient algorithms (DOI: 10.1007/978-3-642-23878-9_13, 10.1109/CEC.2012.6252991, 10.1109/SMDCM.2011.5949264) applicable in various problem domains. This paper appears in in the proceedings of a well-established international conference specializing in parallel problem solving.