论文标题
一种基于共识的算法，用于多目标优化及其平均场描述
A consensus-based algorithm for multi-objective optimization and its mean-field description
论文作者
论文摘要
我们提出了用于多目标优化问题的多代理算法，该算法扩展了基于共识的优化方法，并依赖标量策略。优化是通过探索搜索空间并尝试同时解决所有标量子问题的一组相互作用的代理来实现的。我们表明，这些动力学是通过平均场模型描述的，该模型适用于算法收敛的理论分析。数值结果表明该方法的有效性。
We present a multi-agent algorithm for multi-objective optimization problems, which extends the class of consensus-based optimization methods and relies on a scalarization strategy. The optimization is achieved by a set of interacting agents exploring the search space and attempting to solve all scalar sub-problems simultaneously. We show that those dynamics are described by a mean-field model, which is suitable for a theoretical analysis of the algorithm convergence. Numerical results show the validity of the proposed method.
