Separation functions and optimality conditions in vector optimization
The authors consider a constrained vector optimization problem with nonconvex data. They introduce a class of nonconvex separation functions and use them to establish a relationship between efficient/weakly efficient solutions of the problem and associated Lagrangian functions. They derive also Karush-Kuhn-Tucker conditions for the problem when the data are Lipschitz continuous.
scientific article; zbMATH DE number 6819197
scientific article