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.     

Connectedness of the Efficient Set for Three-Objective Quasiconcave Maximization Problems

For three-objective maximization problems involving continuous, semistrictly quasiconcave functions over a compact convex set, it is shown that the set of efficient solutions is connected. With that, an open problem stated by Choo, Schaible, and Chew in 1985 is solved.     

On the connectedness of the efficient set for strictly quasiconvex vector minimization problems

In this paper, we investigate the connectedness of the efficient solution set for vector minimization problems defined by a continuous vector-valued strictly quasiconvex functionf=(f ₁,...,f _m ) _T and a convex compact setX. It is shown that the efficient solution set is connected if one component off is strongly quasiconvex onX.The author would like to thank Professor H. P. Benson and the referees for many valuable comments and for pointing out some errors in the previous draft.Formerly, Assistant, Department of Applied Mathematics, Shanghai Jiao Tong University, Shanghai, China.     

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。     

A maximization method for a class of quasiconcave programs

An implementable linearized method of centers is presented for solving a class of quasiconcave programs of the form (P): maximizef ⁰(x), subject tox B andf ⁱ (x)0, for everyi{1, ...,m}, whereB is a convex polyhedral subset ofR ⁿ (Euclideann-space). Each problem function is a continuous quasiconcave function fromR ⁿ intoR ¹. Also, it is assumed that the feasible region is bounded and there existsx B such thatf _i (x) for everyi {1, ...,m}. For a broad class of continuous quasiconcave problem functions, which may be nonsmooth, it is shown that the method produces a sequence of feasible points whose limit points are optimal for Problem (P). For many programs, no line searches are required. Additionally, the method is equipped with a constraint dropping devise.The author wishes to thank a referee for suggesting the use of generalized gradients and a second referee whose detailed informative comments have enhanced the paper.This work was done while the author was in the Department of Mathematical Sciences at the University of Delaware.     

锥连续锥拟凹向量函数最大化问题有效解集的连通性

本文讨论了锥连续函数及锥最大下果的性质，在此基础上讨论了锥连续锥拟凹向量函数最大化问题有效解集的连通性，证明了当象集为锥凸集时锥有效解集是连通的。     

Inverse programming and the linear vector maximization problem

This paper presents a new concept of efficient solution for the linear vector maximization problem. Briefly, these solutions are efficient with respect to the constraints, in addition to being efficient with respect to the multiple objectives. The duality theory of linear vector maximization is developed in terms of this solution concept and then is used to formulate the problem as a linear program.This research has been partially supported by grants from the Canada Council and the National Research Council of Canada.     

Connectedness structure of the solution sets of vector variational inequalities

By a scalarization method and properties of semi-algebraic sets, it is proved that both the Pareto solution set and the weak Pareto solution set of a vector variational inequality, where the constraint set is polyhedral convex and the basic operators are given by polynomial functions, have finitely many connected components. Consequences of the results for vector optimization problems are discussed in details. The results of this paper solve in the affirmative some open questions for the case of general problems without requiring monotonicity of the operators involved.