关于线性多目标数学规划强有效解的讨论

文章[5]对多目标数学规划提出了一种新的关于局部强有效解、强有效解的概念,它是单目标规划中严格局部最优解、严格整体最优解概念的一种拓广,本文对线性多目标数学规划的强有效解作一些讨论。     

多目标规划αk-较多有效解类的若干性质

在［１］中,作者提出多目标规划的较多有效解和较多最优解概念,并研究了它们的基本性质．文［３］则讨论了ｋ－较多最优解的若干性质．文［４］利用较多序类进一步引进多目标规划问题的αｋ－较多有效解,并证明了这类解的最优性必要条件．本文再给出多目标规划问题的αｋ－较多最优解的概念,并讨论了多目标规划αｋ－较多有效解和αｋ－较多最优解的若干重要性质．     

线性交叉规划的等价形式

本文利用参数规划的逆问题考虑交叉规划与多目标规划的关系,把交叉规划转变为部分同变量规划组,再把部分同变量规划组转化为一个多目标规划,并说明了交叉规划的均衡解与多目标规划的最优解的关系．     

非光滑多目标规划的不动点算法(英)

本文讨论不动点算法在非光滑多目标规划中的应用，得到了一些新的最优性条件以及不动点与非光滑多目标的解之间的关系，并且给出了解非光滑多目标规划的不动点算法的收敛性．     

广义多目标数学规划非支配解的二阶条件

§1.引言在不等式约束规划中,解的二阶条件是十分重要的课题.关于解的二阶条件,在单目标规划中已经得到了一些很重要的结果,如文献[1—4]等,都从各个不同的方面,引进不同的约束规格来讨论单目标数学规划解的二阶条件.在多目标数学规划中,有关“有效解”、“弱有效解”及“真有效解”的性质及一阶条件,已在不少书及文章中出现,如文献[5—9]等.本文试图就广义多目标数学规划相对于一般凸锥及某个多面体锥的局部和整体非支配解的二阶条件进行讨论.     

非凸多目标规划有效解的充分条件

本文对于含有η－凸性函数的多目标规划问题的有效解，提出若干充分条件，它们是单目标问题最优解相应充分条件的推广．     

双扰动多目标规划的锥次微分稳定性

关于多目标规划解的稳定性问题，一些学者在半连续意义下曾得到比较系统的结果．以后，在锥次微分意义下又获得了更深入的描述．近年，则进一步对目标和约束，以及确定目标空间序的控制锥均受扰动的多目标规划研究其解的稳定性问题，并在Ｂａｎａｃｈ空间和半连续的意义下，得到了很好的刻划．本文则对这类双扰动多目标规划问题，在局部凸拓扑向量空间和锥次微分的意义下，获得了相应的稳定性结论。     

ε－次可微多目标规划的最优性条件

本文主要从多目标规划相应的加权问题出发，讨论了在ε－次可微的条件下，凸多目标规划问题η－有效解存在的必要条件与充分条件．     

极小扰动约束非线性规划的最优性条件

考虑当目标函数在约束条件下的最优值作扰动时，使各约束作极小扰动的非线性规划问题．文中引进了极小扰动约束规划的极小扰动有效解概念．利用把问题归为一个相应的多目标规划问题，给出了极小扰动约束有效解的最优性条件．     

物资分配问题的一个逐次最优解法

本文专门讨论多目标规划问题真有效解的判断．对某些特殊点（如使每个目标函数的导数值为零的所有有效点），给出了Geoffrion意义下真有效解的判别方法．     

Strong Duality with Proper Efficiency in Multiobjective Optimization Involving Nonconvex Set-Valued Maps

In this paper, we consider some dual problems of a primal multiobjective problem involving nonconvex set-valued maps. For each dual problem, we give conditions under which strong duality between the primal and dual problems holds in the sense that, starting from a Benson properly efficient solution of the primal problem, we can construct a Benson properly efficient solution of the dual problem such that the corresponding objective values of both problems are equal. The notion of generalized convexity of set-valued maps we use in this paper is that of near-subconvexlikeness.     

On Characterizations of Proper Efficiency for Nonconvex Multiobjective Optimization

In this paper, nonconvex multiobjective optimization problems are studied. New characterizations of a properly efficient solution in the sense of Geoffrion's are established in terms of the stability of one scalar optimization problem and the existence of an exact penalty function of a scalar constrained program, respectively. One of the characterizations is applied to derive necessary conditions for a properly efficient control-parameter pair of a nonconvex multiobjective discrete optimal control problem with linear constraints.     

Nearly Subconvexlike Set-Valued Maps and Vector Optimization Problems

This paper gives several characterizations of nearly subconvexlike set-valued maps (see Ref. 1) and shows that a weakly efficient solution and a Benson properly efficient solution of a vector optimization problem with nearly-subconvexlike objectives and constraints can be expressed in terms of saddle points defined in a suitable sense.     

G恰当有效点集和G恰当有效解集的连通性

与多目标规划问题的G恰当有效解相应，引进了集合的G恰当有效点的概念，并互研究了G恰当有效点集和G恰当有效解集的连通性．利用所得的结果，还获得多目标规划问题的Pareto有效解集是连通的一个新的结论。     

Global efficiency in multiobjective programming *

In this paper, we are concerned with global efficiency in multiobjective optimization. After exposing a property of a cone-subconvexlike function, we prove that a local weakly efficient solution, a local efficient solution and a local properly efficient solution are respectively a global weakly efficient solution, a global efficient solution and a global properly efficient solution of a multiobjective programming problem if cone- subconvexlikeness or cone-pre-invexity is assumed     

多目标优化问题的完全标量化

本文首先利用松弛变量和广义Tchebycheff范数的推广形式提出一类新的标量化优化问题.进一步,通过调整几种参数范围获得一般多目标优化问题弱有效解、有效解和真有效解的一些完全标量化刻画.此外,本文提出例子对主要结果进行说明,利用相应的标量化方法判定给定的多目标优化问题的可行解是否是弱有效解、有效解和真有效解.     

Optimization Over the Efficient Set of Multi-objective Convex Optimal Control Problems

We consider multi-objective convex optimal control problems. First we state a relationship between the (weakly or properly) efficient set of the multi-objective problem and the solution of the problem scalarized via a convex combination of objectives through a vector of parameters (or weights). Then we establish that (i) the solution of the scalarized (parametric) problem for any given parameter vector is unique and (weakly or properly) efficient and (ii) for each solution in the (weakly or properly) efficient set, there exists at least one corresponding parameter vector for the scalarized problem yielding the same solution. Therefore the set of all parametric solutions (obtained by solving the scalarized problem) is equal to the efficient set. Next we consider an additional objective over the efficient set. Based on the main result, the new objective can instead be considered over the (parametric) solution set of the scalarized problem. For the purpose of constructing numerical methods, we point to existing solution differentiability results for parametric optimal control problems. We propose numerical methods and give an example application to illustrate our approach.     

Isolated efficiency in nonsmooth semi-infinite multi-objective programming

ABSTRACT

In this paper, isolated efficient solutions of a given nonsmooth Multi-Objective Semi-Infinite Programming problem (MOSIP) are studied. Two new Data Qualifications (DQs) are introduced and it is shown that these DQs are, to a large extent, weaker than already known Constraint Qualifications (CQs). The relationships between isolated efficiency and some relevant notions existing in the literature, including robustness, are established. Various necessary and sufficient conditions for characterizing isolated efficient solutions of a general problem are derived. It is done invoking the tangent cones, the normal cones, the generalized directional derivatives, and some gap functions. Using these characterizations, the (strongly) perturbed Karush-Kuhn-Tucker (KKT) optimality conditions for MOSIP are analyzed. Furthermore, it is shown that each isolated efficient solution is a Geoffrion properly efficient solution under appropriate assumptions. Moreover, Kuhn-Tucker (KT) and Klinger properly efficient solutions for a nonsmooth MOSIP are defined and it is proved that each isolated efficient solution is a KT properly efficient solution in general, and a Klinger properly efficient solution under a DQ. Finally, in the last section, the largest isolated efficiency constant for a given isolated efficient solution is determined.     

Existence of efficient solutions for vector maximization problems

The vector maximization problem arises when more than one objective function is to be maximized over a given feasibility region. The concept of efficiency has played a useful role in analyzing this problem. In order to exclude efficient solutions of a certain anomalous type, the concept of proper efficiency has also been utilized. In this paper, an examination of the existence of efficient and properly efficient solutions for the vector maximization problem is undertaken. Given a feasible solution for the vector maximization problem, a related single-objective mathematical programming problem is investigated. Any optimal solution to this program, if one exists, yields an efficient solution for the vector maximization problem. In many cases, the unboundedness of this problem shows that no properly efficient solutions exist. Conditions are pointed out under which the latter conclusion implies that the set of efficient solutions is null. As a byproduct of our results, conditions are derived which guarantee that the outcome of any improperly efficient point is the limit of the outcomes of some sequence of properly efficient points. Examples are provided to illustrate these results.The author would like to thank Professor T. L. Morin for his helpful comments. Thanks also go to an anonymous reviewer for his useful comments concerning an earlier version of this paper.The author would like to acknowledge a useful discussion with Professor G. Bitran which helped in motivating Example 4.1.