A survey, taxonomy and progress evaluation of three decades of swarm optimisation

While the concept of swarm intelligence was introduced in 1980s, the first swarm optimisation algorithm was introduced a decade later, in 1992. In this paper, nineteen representative original swarm optimisation algorithms are analysed to extract their common features and design a taxonomy for swarm optimisation. We use twenty-nine benchmark problems to compare the performance of these nineteen algorithms in the form they were first introduced in the literature against five state-of-the-art swarm algorithms. This comparison reveals the advancements made in this field over three decades. It reveals that, while the state-of-the-art swarm optimisation algorithms are indeed competitive in terms of the quality of solutions they find, their complexities have evolved to be more computationally demanding when compared to the nineteen original algorithms of swarm optimisation. The investigation suggests that there is an urge to continue to design swarm optimisation algorithms that are simpler, while maintaining their current competitive performance.

Automated summary

While the concept of swarm intelligence was introduced in the 1980s, the first swarm optimisation algorithm was not introduced until 1992. Analyzing nineteen original swarm optimisation algorithms revealed that while state-of-the-art algorithms are competitive in finding solutions, they are more computationally demanding compared to the original algorithms.