On global minima of semistrictly quasiconcave functions

This paper studies the global behaviour of semistrictly quasiconcave functions with (possibly) nonconvex domain in the presence of global minima. We mainly present necessary conditions for the existence of global minima of a semistrictly quasiconcave real-valued function f with domain , and we show how the geometric structure of its graph and the cardinality of its range depend on the location of global minimum points. Our main result states that if a global minimum of f is achieved in the algebraic interior of K, then f can attain at the most n + 1 distinct function values, and the graph of f has a simple structure determined by a sequence of nested affine subspaces such that, essentially, f is constant on the set difference of each pair of successive affine subspaces.     

A note on the maximum points of the minimum of quasiconvex functions

The paper deals with the problem of maximizing the minimum of quasiconvex functions over a compact convex set Z. Subsets of Zare given which contain all solutions or at least one solution.     

Global solutions of mathematical programs with intrinsically concave functions

An implicit enumeration technique for solving a certain type of nonconvex program is described. The method can be used for solving signomial programs with constraint functions defined by sums of quasiconcave functions and other types of programs with constraint functions called intrinsically concave functions. A signomial-type example is solved by this method. The algorithm is described together with a convergence proof. No computational results are available at present.     

Analytical representation of concave and quasiconcave homogeneous functions

The formula which implements bijection between the class of concave linearly homogeneous functions defined on the nonnegative orthant of an arithmetic space and the simpler class of concave functions defined on the standard (probabilistic) simplex is presented. Two generalizations of this formula for analytical representation of quasiconcave homogeneous function are also proposed. These formulas particularly extend opportunities of modelling production objects and consumption.     

A note on functions whose local minima are global

In this note, a simple proof of a theorem concerning functions whose local minima are global is presented and some closedness properties of this class of functions are discussed.The authors would like to thank Dr. Tatsuro Ichiishi of CORE for outlining the new proof of Theorem 2.1.This research was done while the author was a research fellow at the Center for Operations Research and Econometrics, University of Louvain, Heverlee, Belgium.     

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.     

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.     

A note on polyharmonic functions

In this note we prove the following theorem:Suppose 0<p<∞ and α>−1. Then there is a constant C=C(p,m,n,α) such that

     

A note on functions whose local minima are global

In this note, we introduce a new class of generalized convex functions and show that a real functionf which is continuous on a compact convex subsetM of ⁿ and whose set of global minimizers onM is arcwise-connected has the property that every local minimum is global if, and only if,f belongs to that class of functions.     

A quasiconcave minimization method for solving linear two-level programs

In this paper the linear two-level problem is considered. The problem is reformulated to an equivalent quasiconcave minimization problem, via a reverse convex transformation. A branch and bound algorithm is developed which takes the specific structure into account and combines an outer approximation technique with a subdivision procedure.     

Some properties of explicitly quasiconcave functions

Quasiconcave functions are characterized by the convexity of the upper level sets. This paper presents the additional properties which are required to characterize explicitly quasiconcave functions, which include the strictly quasiconcave functions. These additional properties are expressed in terms of the properties of and relationships between the level set, the upper level set, the boundary, and the profile of the upper level set.     

A note on hyperharmonic and polyharmonic functions

We show that the spaces of harmonic functions with respect to the Poincaré metric in the unit ball B^N in have many different properties depending upon whether N is even or odd.     

A note on the complementarity problem

We show by an example that, in a complementarity problem where the given map is continuous and monotone on the nonnegative orthant, the existence of a feasible solution is not sufficient to guarantee existence of a solution to the complementarity problem.The author thanks Professor S. Karamardian and Dr. J. More for helpful discussions regarding this note.     

A Framework for Globally Convergent Algorithms Using Gradient Bounding Functions

This paper presents a novel framework for developing globally convergent algorithms without evaluating the value of a given function. One way to implement such a framework for a twice continuously differentiable function is to apply linear bounding functions (LBFs) to its gradient function. The algorithm thus obtained can get a better point in each iteration without using a line search. Under certain conditions, it can achieve at least superlinear convergent rate 1.618 without calculating explicitly the Hessian. Furthermore, the strategy of switching from the negative gradient direction to the Newton-alike direction is derived in a natural manner and is computationally effective. Numerical examples are used to show how the algorithm works.     

A Class of penalty functions for optimization problema with bound constraints

In this paper we propose a new class of continuously differentiable globally exact penalty functions for the solution of minimization problems with simple bounds on some (all) of the variables. The penalty functions in this class fully exploit the structure of the problem and are easily computable. Furthermore we introduce a simple updating rule for the penalty parameter that can be used in conjunction with unconstrained minimization techniques to solve the original problem.     

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.     

A modified Newton's method for minimizing factorable functions

Many functions of several variables used in nonlinear programming are factorable, i.e., complicated compositions of transformed sums and products of functions of a single variable. The Hessian matrices of twice-differentiable factorable functions can easily be expressed as sums of outer products (dyads) of vectors. A modified Newton's method for minimizing unconstrained factorable functions which exploits this special form of the Hessian is developed. Computational experience with the method is presented.This material is based upon work supported by the National Science Foundation under Grant No. MCS-79-04106.The author would like to thank Professor G. P. McCormick, George Washington University, for several enlightening discussions on factorable programming and for his valuable comments which improved an earlier version of this paper.     

Vector maximization with two objective functions

This note gives a characterization of an efficient solution for the vector maximization problem with two objective functions. This characterization yields a parametric procedure for generating the set of all efficient solutions for this problem. The parametric procedure can also be used to solve certain bicriterion mathematical programs.     

Nonlinear programming and an optimization problem on infinitely differentiable functions

A nonnegative, infinitely differentiable function ø defined on the real line is called a Friedrichs mollifier function if it has support in [0, 1] and ₀ ¹ ø(t)dt=1. In this article the following problem is considered. Determine _k =inf ₀ ¹ vø^(k)(t)dt, k=1,..., where ø^(k) denotes thekth derivative of ø and the infimum is taken over the set of all mollifier functions. This problem has applications to monotone polynomial approximation as shown by this author elsewhere. In this article, the structure of the problem of determining _k is analyzed, and it is shown that the problem is reducible to a nonlinear programming problem involving the minimization of a strictly convex function of [(k–1)/2] variables, subject to a simple ordering restriction on the variables. An optimization problem on the functions of bounded variation, which is equivalent to the nonlinear programming problem, is also developed. The results of this article and those from approximation of functions theory are applied elsewhere to derive numerical values of various mathematical quantities involved in this article, e.g., _k =k~2^2k–1 for allk=1, 2, ..., and to establish certain inequalities of independent interest. This article concentrates on problem reduction and equivalence, and not numerical value.This research was supported in part by the National Science Foundation under Grant No. GK-32712.