Generalized Polarity and Weakest Constraint Qualifications in Multiobjective Optimization
将单目标优化中的法锥推广到多目标情形，并引入最弱约束资格条件，使得局部弱帕累托最优点成为弱库恩-塔克点，同时扩展到其他类型的帕累托最优点与库恩-塔克点。
Abstract In Haeser and Ramos (J Optim Theory Appl, 187:469–487, 2020), a generalization of the normal cone from single objective to multiobjective optimization is introduced, along with a weakest constraint qualification such that any local weak Pareto optimal point is a weak Kuhn–Tucker point. We extend this approach to other generalizations of the normal cone and corresponding weakest constraint qualifications, such that local Pareto optimal points are weak Kuhn–Tucker points, local proper Pareto optimal points are weak and proper Kuhn–Tucker points, respectively, and strict local Pareto optimal points of order one are weak, proper and strong Kuhn–Tucker points, respectively. The constructions are based on an appropriate generalization of polarity to pairs of matrices and vectors.