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Multi-objective particle swarm optimisation control

Multi-objective particle swarm optimisation control

Abstract

This chapter provides a brief introduction to the basic particle swarm optimisation (PSO) algorithm and some of its notable variants available in the literature. Then a process of developing multi-objective PSO (MOPSO) algorithms is described, and the approach is utilised to develop two alternative MOPSO algorithms. A case study exercise is presented where the two MOPSO algorithms are used in the design of command shapers for vibration reduction of a single-link flexible manipulator. The implementation results achieved are assessed and discussed.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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