We have adapted the use of exponentially averaged momentum in PSO to multi-objective optimization problems. The algorithm was built on top of SMPSO, a state-of-the-art MOO solver, and we present a novel mathematical analysis of constriction fairness. We extend this analysis to the use of momentum and propose rich alternatives of parameter sets which are theoretically sound. We call our proposed algorithm "Fairly Constricted PSO with Exponentially-Averaged Momentum", FCPSO-em.
翻译:我们已经将使用PSO指数平均动力的指数平均动力来适应多目标优化问题。算法建在SMPSO的顶端,这是一个最先进的MOO解答器,我们提出了关于收缩公平性的新颖数学分析。我们将这一分析扩展至使用动力并提出在理论上合理的参数组的丰富替代方法。我们称我们提议的算法为“公平受限制的PSO,具有极强的电动脉冲 ”, FCPSO-em。