Connectedness of the efficient set in strictly quasiconcave vector maximization

In this paper, the concepts of quasiconcave set and strictly quasiconcave set are introduced. By using these concepts, we get a new sufficient condition for the efficient outcome set to be connected. This leads to the connectedness of the efficient solution set in strictly quasiconcave vector maximization under the mild condition that the efficient frontier is closed.The authors would like to thank Professor E. U. Choo and the referees for their many valuable comments and helpful suggestions.     

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.     

New Results on Second-Order Optimality Conditions in Vector Optimization Problems

In this paper, we study second-order optimality conditions for multiobjective optimization problems. By means of different second-order tangent sets, various new second-order necessary optimality conditions are obtained in both scalar and vector optimization. As special cases, we obtain several results found in the literature (see reference list). We present also second-order sufficient optimality conditions so that there is only a very small gap with the necessary optimality conditions. The authors thank Professor P.L. Yu and the referees for valuable comments and helpful suggestions.     

Density of the set of positive proper minimal points in the set of minimal points

One of the important problems of vector optimization concerns the density of the set of positive proper minimal points in the set of minimal points. We use the concepts of dentable point and approximating cones to derive sufficient conditions guaranteeing that the set of minimal points is contained in the closure of the set of positive proper minimal points. The result can be applied to obtain a density result for the unit ball in 1 ^p , 1<p<+, which does not follow from any other well-known density theorem.The author would like to thank Professor W. T. Fu for helpful comments. Moreover, the author is grateful to Professor H. P. Benson and the referees for valuable remarks and suggestions concerning a previous draft of this paper.     

Geometric consideration of duality in vector optimization

Recently, duality in vector optimization has been attracting the interest of many researchers. In order to derive duality in vector optimization, it seems natural to introduce some vector-valued Lagrangian functions with matrix (or linear operator, in some cases) multipliers. This paper gives an insight into the geometry of vector-valued Lagrangian functions and duality in vector optimization. It is observed that supporting cones for convex sets play a key role, as well as supporting hyperplanes, traditionally used in single-objective optimization.The author would like to express his sincere gratitude to Prof. T. Tanino of Tohoku University and to some anonymous referees for their valuable comments.     

On equating the difference between optimal and marginal values of general convex programs

Unlike elementary finite linear programming, the optimal program value of a convex optimization problem is generally different from the vector product of the marginal price vector and the resource right-hand side vector. In this paper, a duality approach is developed, based on objective function parametrizations, to characterize this difference under rather general circumstances.The approach generalizes the concept of Kuhn-Tucker vectors of a convex program. It is shown that nonstandard polynomial Kuhn-Tucker vectors exist for any convex program having finite value. Two examples illustrate the procedure.An earlier version of this paper was presented at the International Symposium on Extremal Methods and Systems Analysis on the Occasion of Professor A. Charnes' Sixtieth Birthday, Austin, Texas, 1977. Partial support of the research of the first author was provided by NSF Grants Nos. ENG-76-05191 and ENG-78-25488. The authors gratefully acknowledge Professor F. J. Gould, University of Chicago, for bringing the valuable Balinski-Baumol reference (Ref. 1) to their attention. They also gratefully acknowledge criticisms of a referee reminding them of the sophistication which a convex analysis approach can bring to bear on the main problem treated in this paper. This paper is dedicated to Professor Charnes.     

On constraint qualifications

The linear independence constraint qualification (LICQ) and the weaker Mangasarian-Fromovitz constraint qualification (MFCQ) are well-known concepts in nonlinear optimization. A theorem is proved suggesting that the set of feasible points for which MFCQ essentially differs from LICQ is small in a specified sense. As an auxiliary result, it is shown that, under MFCQ, the constraint set (even in semi-infinite optimization) is locally representable in epigraph form.The author wishes to thank Professor H. T. Jongen for valuable advice.     

Image Space Analysis and Scalarization of Multivalued Optimization

Using a new method based on generalized sections of feasible sets, we obtain optimality conditions for vector optimization of objective multifunctions with multivalued constraints. The authors express their sincere gratitude to Professor F. Giannessi and the referees for comments and valuable suggestions. The second author was partially supported by the Center of Excellence for Mathematics (University of Isfahan).     

Parametric approximation problems arising in vector optimization

In this paper, a known scalarization result of vector optimization theory is reviewed and stated in a different form and a new short proof is presented. Moreover, it is shown how to apply this result to multi-objective optimization problems and to special problems in statistics and optimal control theory.The author is grateful to Professor H. Schellhaas and T. Staib for helpful discussions on this subject and to a referee for pointing out an error in an earlier version of this paper.     

Sufficient optimality conditions and duality in vector optimization with invex-convexlike functions

We prove the Kuhn-Tucker sufficient optimality condition, the Wolfe duality, and a modified Mond-Weir duality for vector optimization problems involving various types of invex-convexlike functions. The class of such functins contains many known generalized convex functions. As applications, we demonstrate that, under invex-convexlikeness assumptions, the Pontryagin maximum principle is a sufficient optimality condition for cooperative differential games. The Wolfe duality is established for these games.The author is indebted to the referees and Professor W. Stadler for valuable remarks and comments, which have been used to revise considerably the paper.     

Three kinds of generalized convexity

This paper gives some properties of quasiconvex, strictly quasiconvex, and strongly quasiconvex functions. Relationships between them are discussed.This research was supported in part by the National Natural Science Foundation of China. The author would like to thank Professor M. Avriel for valuable comments about this paper.     

Stampacchia Generalized Vector Quasiequilibrium Problems and Vector Saddle Points

In this paper, Stampacchia generalized vector quasiequilibrium problem and generalized vector loose saddle points for set-valued mappings are introduced. By using the scalarization method and the fixed-point theorem, existence theorems are established.This work was supported by the National Natural Science Foundation of China and the Natural Science Foundation of Jiangxi Province, China. The author is grateful to Professor F. Giannessi and the referee for valuable comments and careful reading improving the original draft.Communicated by F. Giannessi     

Vector optimization problems with nonconvex preferences

In this paper, some vector optimization problems are considered where pseudo-ordering relations are determined by nonconvex cones in Banach spaces. We give some characterizations of solution sets for vector complementarity problems and vector variational inequalities. When the nonconvex cone is the union of some convex cones, it is shown that the solution set of these problems is either an intersection or an union of the solution sets of all subproblems corresponding to each of these convex cones depending on whether these problems are defined by the nonconvex cone itself or its complement. Moreover, some relations of vector complementarity problems, vector variational inequalities, and minimal element problems are also given. While this paper was being revised in September 2006, Professor Alex Rubinov (the second author of the paper) left us due to the illness. This is a very sad news to us. We dedicate this paper to the memory of Professor Rubinov as a mathematician and truly friend.     

Connectedness of super efficient solution sets for set-valued maps in Banach spaces

In this paper, we study the connectedness of the super efficient solution sets in convex vector optimization for set-valued maps in Banach spaces.     

Semivectorial Bilevel Optimization Problem: Penalty Approach

We consider a bilevel optimization problem where the upper level is a scalar optimization problem and the lower level is a vector optimization problem. For the lower level, we deal with weakly efficient solutions. We approach our problem using a suitable penalty function which vanishes over the weakly efficient solutions of the lower-level vector optimization problem and which is nonnegative over its feasible set. Then, we use an exterior penalty method.Communicated by H. P. Benson(Formerly Serban Bolintinéanu) Professor, University of New Caledonia, ERIM, Nouméa, New Caledonia. This author thanks the University of Naples Federico II for its support and the Department of Mathematics and Statistics for its hospitality.     

Some properties of efficient solutions for vector optimization

In this paper, we discuss the optimality conditions for vector optimization problems. Properties of efficient and weakly efficient solutions are studied, and some new necessary conditions are obtained. Most of them are related to the mapping properties of the derivative operatorf(x) of the objective functionf. Almost all of our results are based on the methods of functional analysis and the theory of degree.The authors would like to thank Professor Y. D. Hu, Deputy General Secretary of the Chinese Operations Research Society, for his help and directions. Also, the authors would like to thank Professors T. K. Sung and Y. J. Chang, Chairmen of the authors' present department, for their sincere concern and encouragement. Finally, the authors are grateful to Professor G. Leitmann for his valuable comments, suggestions, and his careful editing of an earlier version of this paper.     

On necessary and sufficient conditions in vector optimization

It is shown that some general multiplier rules are necessary conditions for vector optimization in infinite-dimensional spaces. Under additional convexity assumptions, these conditions are sufficient. As an application, the Pontryagin maximum principle for cooperative differential games is examined.The authors are grateful to Professor W. Stadler and the referees of the previous edition of this paper for their valuable remarks and suggestions, which have been very helpful in the preparation of this paper.     

Existence and stability of solutions for a class of generalized vector equilibrium problems

In this paper, two existence theorems concerning the strong efficient solutions and the weakly efficient solutions of generalized vector equilibrium problems are derived by using the Fan-KKM Theorem and an existence theorem for the efficient solutions of generalized vector equilibrium problems is established by using the scalarization method. Moreover, the lower semicontinuity of the strong efficient solution mapping and the weakly efficient solution mapping to parametric generalized vector equilibrium problems are showed under suitable conditions with neither monotonicity nor any information of the solution mappings. Finally, some applications to the vector optimization problems and the Stackelberg equilibrium problem are also given.     

A Result on Vector Variational Inequalities with Polyhedral Constraint Sets

In this note, by using some well-known results on properly efficient solutions of vector optimization problems, we show that the Pareto solution set of a vector variational inequality with a polyhedral constraint set can be expressed as the union of the solution sets of a family of (scalar) variational inequalities.     

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.