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Particle Swarm optimisation (PSO) is a particular form of swarm intelligence, which itself is an innovative intelligent paradigm for solving optimization problems. PSO is generally used to find a global optimum in a single optimisation function. This typically occurs on one node(machine) but there has been a significant body of research into creating distributed implementations of the PSO algorithm. Such research has often focused on the creation and performance of the distributed implementation in an isolated manner or compared to different distributed algorithms.
This research piece aims to bridge a gap in the existing literature, by testing a distributed implementation of a PSO algorithm against a centralised implementation, and investigating what, if any, gains there are to utilising a distributed implementation over a centralised implementation. The focus will primarily be on the time taken for the algorithm to successfully find a global minimum to a specific fitness function, but other elements will be examined over the course of the study.
O’Loughlin, C. (2021). Performance comparison between a distributed particle swarm algorithm and a centralised algorithm. Technological University Dublin. DOI: 10.21427/3BT8-C038