
Dynamic multi-objective optimisation problems have more than one objective with at least one objective that changes over time. Previous studies indicated that different knowledge sharing strategies increase the performance of the dynamic vector evaluated particle swarm optimisation (DVEPSO) algorithm in different dynamic environments. Therefore, this paper investigates the performance of the DVEPSO algorithm using heterogeneous particle swarm optimisation (HPSO) algorithms, where each particle uses a different knowledge sharing strategy. The goal of this study is to determine whether the use of HPSOs will improve the performance of DVEPSO by incorporating particles with different knowledge sharing strategies in a single DVEPSO algorithm. The results indicate that using HPSOs improves the performance of DVEPSO for dynamic multi-objective optimisation problems with a complex Pareto-optimal set and that the performance of heterogeneous DVEPSO compares favourably with that of DVEPSO.
| 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). | 1 | |
| 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. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
