In this paper, both Fritz John and Karush-Kuhn-Tucker necessary optimality conditions are established for a （weakly） LU-efficient solution in the considered nonsmooth multiobjective programming problem with the mult...In this paper, both Fritz John and Karush-Kuhn-Tucker necessary optimality conditions are established for a （weakly） LU-efficient solution in the considered nonsmooth multiobjective programming problem with the multiple interval-objective function. Further, the sufficient optimality conditions for a （weakly） LU-efficient solution and several duality results in Mond-Weir sense are proved under assumptions that the functions constituting the considered nondifferentiable multiobjective programming problem with the multiple interval- objective function are convex.展开更多
Based on the interval analysis,a practical interval algorithm is developed for finding all global minimizers of a nonsmooth function on a closed domain XR n, which is given by defining a special derivative to the func...Based on the interval analysis,a practical interval algorithm is developed for finding all global minimizers of a nonsmooth function on a closed domain XR n, which is given by defining a special derivative to the function and using the interval inclusion of derivative. Both theoretical analysis and numerical results show that this method is practical and effective.展开更多
Presents an inexact trust region algorithm for solving constrained nonsmooth optimization problems. Global convergence of the algorithm; Assumptions on the algorithm; Relation between critical points and stationary po...Presents an inexact trust region algorithm for solving constrained nonsmooth optimization problems. Global convergence of the algorithm; Assumptions on the algorithm; Relation between critical points and stationary points.展开更多
This paper considers a distributed nonsmooth resource allocation problem of minimizing a global convex function formed by a sum of local nonsmooth convex functions with coupled constraints.A distributed communication-...This paper considers a distributed nonsmooth resource allocation problem of minimizing a global convex function formed by a sum of local nonsmooth convex functions with coupled constraints.A distributed communication-efficient mirror-descent algorithm,which can reduce communication rounds between agents over the network,is designed for the distributed resource allocation problem.By employing communication-sliding methods,agents can find aε-solution in O(1/ε)communication rounds while maintaining O(1/ε^(2))subgradient evaluations for nonsmooth convex functions.A numerical example is also given to illustrate the effectiveness of the proposed algorithm.展开更多
This paper investigates the feedback stabilization problem for a class of discontinuous systems which is characterized by Filippov differential inclusion. Lyapunov-based backstepping design method is generalized with ...This paper investigates the feedback stabilization problem for a class of discontinuous systems which is characterized by Filippov differential inclusion. Lyapunov-based backstepping design method is generalized with nons- mooth Lyapunov functions to solve the control problem. A set-valued time derivative is introduced first for nonsmooth function along discontinuous vector fields, which enables us to perform Lyapunov-based design with nondifferentiable Lyapunov function. Conditions for designing a virtual control law which is shown nondifferentiable in general in the re- cursive design problem are proposed. Finally, as a special case, piecewise linear system is discussed to demonstrate the application of the presented design approach.展开更多
The aim of this paper is to provide a sys- tematic review on the framework to analyze dynamics in recurrently connected neural networks with discontinu- ous right-hand sides with a focus on the authors＇ works in the ...The aim of this paper is to provide a sys- tematic review on the framework to analyze dynamics in recurrently connected neural networks with discontinu- ous right-hand sides with a focus on the authors＇ works in the past three years. The concept of the Filippov so- lution is employed to define the solution of the neural network systems by transforming them to differential in- clusions. The theory of viability provides a tool to study the existence and uniqueness of the solution and the Lya- punov function （functional） approach is used to investi- gate the global stability and synchronization. More pre- cisely, we prove that the diagonal-dominant conditions guarantee the existence, uniqueness, and stability of a general class of integro-differential equations with （al- most） periodic self-inhibitions, interconnection weights, inputs, and delays. This model is rather general and in- cludes the well-known Hopfield neural networks, Cohen- Grossberg neural networks, and cellular neural networks as special cases. We extend the absolute stability anal- ysis of gradient-like neural network model by relaxing the analytic constraints so that they can be employed to solve optimization problem with non-smooth cost func- tions. Furthermore, we study the global synchronization problem of a class of linearly coupled neural network with discontinuous right-hand sides.展开更多
文摘In this paper, both Fritz John and Karush-Kuhn-Tucker necessary optimality conditions are established for a （weakly） LU-efficient solution in the considered nonsmooth multiobjective programming problem with the multiple interval-objective function. Further, the sufficient optimality conditions for a （weakly） LU-efficient solution and several duality results in Mond-Weir sense are proved under assumptions that the functions constituting the considered nondifferentiable multiobjective programming problem with the multiple interval- objective function are convex.
文摘Based on the interval analysis,a practical interval algorithm is developed for finding all global minimizers of a nonsmooth function on a closed domain XR n, which is given by defining a special derivative to the function and using the interval inclusion of derivative. Both theoretical analysis and numerical results show that this method is practical and effective.
基金The authors are supported by the Natronal Natural Science Foundation of China
文摘Presents an inexact trust region algorithm for solving constrained nonsmooth optimization problems. Global convergence of the algorithm; Assumptions on the algorithm; Relation between critical points and stationary points.
基金supported by the National Natural Science Foundation of China under Grant Nos.72101026,61621063the State Key Laboratory of Intelligent Control and Decision of Complex Systems。
文摘This paper considers a distributed nonsmooth resource allocation problem of minimizing a global convex function formed by a sum of local nonsmooth convex functions with coupled constraints.A distributed communication-efficient mirror-descent algorithm,which can reduce communication rounds between agents over the network,is designed for the distributed resource allocation problem.By employing communication-sliding methods,agents can find aε-solution in O(1/ε)communication rounds while maintaining O(1/ε^(2))subgradient evaluations for nonsmooth convex functions.A numerical example is also given to illustrate the effectiveness of the proposed algorithm.
文摘This paper investigates the feedback stabilization problem for a class of discontinuous systems which is characterized by Filippov differential inclusion. Lyapunov-based backstepping design method is generalized with nons- mooth Lyapunov functions to solve the control problem. A set-valued time derivative is introduced first for nonsmooth function along discontinuous vector fields, which enables us to perform Lyapunov-based design with nondifferentiable Lyapunov function. Conditions for designing a virtual control law which is shown nondifferentiable in general in the re- cursive design problem are proposed. Finally, as a special case, piecewise linear system is discussed to demonstrate the application of the presented design approach.
文摘The aim of this paper is to provide a sys- tematic review on the framework to analyze dynamics in recurrently connected neural networks with discontinu- ous right-hand sides with a focus on the authors＇ works in the past three years. The concept of the Filippov so- lution is employed to define the solution of the neural network systems by transforming them to differential in- clusions. The theory of viability provides a tool to study the existence and uniqueness of the solution and the Lya- punov function （functional） approach is used to investi- gate the global stability and synchronization. More pre- cisely, we prove that the diagonal-dominant conditions guarantee the existence, uniqueness, and stability of a general class of integro-differential equations with （al- most） periodic self-inhibitions, interconnection weights, inputs, and delays. This model is rather general and in- cludes the well-known Hopfield neural networks, Cohen- Grossberg neural networks, and cellular neural networks as special cases. We extend the absolute stability anal- ysis of gradient-like neural network model by relaxing the analytic constraints so that they can be employed to solve optimization problem with non-smooth cost func- tions. Furthermore, we study the global synchronization problem of a class of linearly coupled neural network with discontinuous right-hand sides.
