集值优化问题在有效意义下的最优性条件

本文在赋范空间中,讨论集值优化问题的有效元导数型最优性条件.当目标映射和约束映射的下方向导数存在时,在近似锥次类凸假设下利用有效点的性质和凸集分离定理得到了集值优化问题有效元导数型Kuhn-Thcker必要条件,在可微Г-拟凸性的假设下得到了Kuhn-Tucker最优性充分条件;此外利用集值映射沿弱方向锥的导数的特性给出了有效解最优性的另一种刻画.     

内部锥-凸集值映射Henig有效性的Morea-Rockafellar定理

本文利用集值映射弱次梯度的Morea-Rockafellar定理,在内部(锥)-凸性假设下,得到了集值映射关于Henig有效性的Morea-Rockafellar定理.其结论为:在内部(锥)-凸条件下,两个集值映射和的Henig有效次梯度可以表示成它们Henig有效次梯度的和.     

集值优化问题Borwein真有效解与Benson真有效解的等价性

在局部凸空间中锥弱似凸集值映射的假设下,集值优化问题Borwein真有效解与Benson真有效解的等价性被获得.为了说明结果,一些例子被给出.     

一类集值映射向量优化问题的ε-有效解

集值映射向量优化问题是最优化理论中的一个重要方向.在集值映射为生成锥内部-锥一类凸(简记为ic-锥类凸)的假设条件下,利用择一定理,给出了集值映射向量优化问题ε-弱有效解和ε-有效解的最优性条件和ε-Lagrange乘子定理,是弱有效解和有效解相应结果的推广.     

含参集值向量均衡问题各种有效解映射的下半连续性

在实Hausdorff拓扑向量空间中,引进含参集值向量均衡问题,给出各种有效解的概念.在锥-次类凸的条件下,得到各种有效解的标量化结果.结合集值映射的弱f-性,在适当假设条件下,得到含参集值向量均衡问题各种有效解映射的下半连续性.     

D-E-半预不变真拟凸映射与向量优化

提出了一类新的向量值映射-D-E-半预不变真拟凸映射,它是D-半预不变真拟凸映射和D-E-预不变真拟凸映射的真推广.首先,举例验证了D-E半预不变真拟凸映射的存在性;其次,说明了D-E-半预不变真拟凸映射的水平集是E-半不变凸集,讨论了D-E-严格半预不变真拟凸映射和D-E-半严格半预不变真拟凸映射的关系;再次,在D-E-半严格(严格)半预不变真拟凸性下,得出了向量优化问题的E-局部有效解为E-全局有效解,E-局部弱有效解为E-全局弱有效解,并举例验证了所得结果;最后,在D-E-严格半预不变真拟凸性下,建立了向量优化问题的E-全局弱有效解和E-局部弱有效解的唯一性刻画.     

Benson真有效意义下向量集值优化的广义Fritz-John条件

借助Clarke切锥并用上图引入了关于集值映射的Clarke切导数.借助于一种新的择一性定理建立了向量集值优化问题在弱Benson真有效意义下的广义Fritz-John最优性条件,而且证明在一种伪凸的假设下,这种最优性条件还为充分的.     

Banach空间扰动集值映射最优化的锥次微分稳定性

本文研究Ｂａｎａｃｈ空间中扰动集值映射最优化的稳定性问题,在目标映射和约束映射均为半连续和锥凸的条件下,得到了扰动问题的锥有效点集和锥弱有效点集分别在锥次秃分和锥弱次微分意义下的稳定性结果。     

集值映射全局真有效次梯度下的Moreau-Rockafellar定理

本文研究了集值映射的Moreau-Rockafellar型定理的问题.利用集值映射弱次梯度的Moreau-Rockafellar定理,在内部(锥)-凸条件下,获得了集值映射关于全局真有效性的Moreau-Rockafellar型定理结果,推广了集值映射在锥-凸假设下的Moreau-Rockafellar型定理的结果,所得结论深化和丰富了最优化理论的内容.     

凸约束伪单调方程组的无导数投影算法

基于HS共轭梯度法的结构,本文在弱假设条件下建立了一种求解凸约束伪单调方程组问题的迭代投影算法.该算法不需要利用方程组的任何梯度或Jacobian矩阵信息,因此它适合求解大规模问题.算法在每一次迭代中都能产生充分下降方向,且不依赖于任何线搜索条件.特别是,我们在不需要假设方程组满足Lipschitz条件下建立了算法的全局收敛性和R-线收敛速度.数值结果表明,该算法对于给定的大规模方程组问题是稳定和有效的.     

Inner and outer estimates for the solution sets and their asymptotic cones in vector optimization

We use asymptotic analysis to develop finer estimates for the efficient, weak efficient and proper efficient solution sets (and for their asymptotic cones) to convex/quasiconvex vector optimization problems. We also provide a new representation for the efficient solution set without any convexity assumption, and the estimates involve the minima of the linear scalarization of the original vector problem. Some new necessary conditions for a point to be efficient or weak efficient solution for general convex vector optimization problems, as well as for the nonconvex quadratic multiobjective optimization problem, are established.     

UNIFORM APPROXIMATION OF A MULTIOBJECTIVE OPTIMIZATION SEQUENCE

In this paper the Pareto efficiency of a uniformly convergent multiobjective optimization sequence is studied. We obtain some relation between the Pareto efficient solutions of a given multiobjective optimization problem and those of its uniformly convergent optimization sequence and also some relation between the weak Pareto efficient solutions of the same optimization problem and those of its uniformly convergent optimization sequence. Besides, under a compact convex assumption for constraints set and a certain convex assumption for both objective and constraint functions, we also get some sufficient and necessary conditions that the limit of solutions of a uniformly convergent multiobjective optimization sequence is the solution of a given multiobjective optimization problem.     

Some properties of approximate solutions for vector optimization problem with set-valued functions

In this paper, we study the approximate solutions for vector optimization problem with set-valued functions. The scalar characterization is derived without imposing any convexity assumption on the objective functions. The relationships between approximate solutions and weak efficient solutions are discussed. In particular, we prove the connectedness of the set of approximate solutions under the condition that the objective functions are quasiconvex set-valued functions.     

The structure of weak Pareto solution sets in piecewise linear multiobjective optimization in normed spaces

In general normed spaces,we consider a multiobjective piecewise linear optimization problem with the ordering cone being convex and having a nonempty interior.We establish that the weak Pareto optimal solution set of such a problem is the union of finitely many polyhedra and that this set is also arcwise connected under the cone convexity assumption of the objective function.Moreover,we provide necessary and suffcient conditions about the existence of weak(sharp) Pareto solutions.     

On Duality in Nonconvex Vector Optimization in Banach Spaces Using Augmented Lagrangians

This paper shows how the use of penalty functions in terms of projections on the constraint cones, which are orthogonal in the sense of Birkhoff, permits to establish augmented Lagrangians and to define a dual problem of a given nonconvex vector optimization problem. Then the weak duality always holds. Using the quadratic growth condition together with the inf-stability or a kind of Rockafellar's stability called stability of degree two, we derive strong duality results between the properly efficient solutions of the two problems. A strict converse duality result is proved under an additional convexity assumption, which is shown to be essential.     

多目标优化问题Proximal真有效解的最优性条件

在广义凸性假设下,给出了集合proximal真有效点的线性标量化,并在此基础上证明了它与Benson真有效点和Borwein真有效点的等价性.将这些结果应用到多目标优化问题上,得到proximal真有效解的最优性条件.最后,利用proximal次微分,得到了proximal真有效解的模糊型最优性条件.     

Generalized asymptotic functions in nonconvex multiobjective optimization problems

In this paper, we use generalized asymptotic functions and second-order asymptotic cones to develop a general existence result for the nonemptiness of the proper efficient solution set and a sufficient condition for the domination property in nonconvex multiobjective optimization problems. A new necessary condition for a point to be efficient or weakly efficient solution is given without any convexity assumption. We also provide a finer outer estimate for the asymptotic cone of the weakly efficient solution set in the quasiconvex case. Finally, we apply our results to the linear fractional multiobjective optimization problem.     

On Benson’s scalarization in multiobjective optimization

In this paper, a popular scalarization problem in multiobjective optimization, introduced by Benson, is considered. In the literature it was proved that, under convexity assumption, the set of properly efficient points is empty when the Benson’s problem is unbounded. In this paper, it is shown that this result is still valid in general case without convexity assumption.     

Duality and existence theory for nondifferentiable programming

Necessary and sufficient conditions of optimality are given for a nonlinear nondifferentiable program, where the constraints are defined via closed convex cones and their polars. These results are then used to obtain an existence theorem for the corresponding stationary point problem, under some convexity and regularity conditions on the functions involved, which also guarantee an optimal solution to the programming problem. Furthermore, a dual problem is defined, and a strong duality theorem is obtained under the assumption that the constraint sets of the primal and dual problems are nonempty.     

Nonsmooth Multiobjective Problems and Generalized Vector Variational Inequalities Using Quasi-Efficiency

In this paper, a multiobjective problem with a feasible set defined by inequality, equality and set constraints is considered, where the objective and constraint functions are locally Lipschitz. Here, a generalized Stampacchia vector variational inequality is formulated as a tool to characterize quasi- or weak quasi-efficient points. By using two new classes of generalized convexity functions, under suitable constraint qualifications, the equivalence between Kuhn–Tucker vector critical points, solutions to the multiobjective problem and solutions to the generalized Stampacchia vector variational inequality in both weak and strong forms will be proved.