Loading [MathJax]/extensions/MathZoom.js
Displaying 41 –
60 of
353
Is it possible to label the edges of Kₙ with distinct integer weights so that every Hamilton cycle has the same total weight? We give a local condition characterizing the labellings that witness this question's perhaps surprising affirmative answer. More generally, we address the question that arises when "Hamilton cycle" is replaced by "k-factor" for nonnegative integers k. Such edge-labellings are in correspondence with certain vertex-labellings, and the link allows us to determine (up to a constant...
We consider a multiobjective optimization problem with a feasible set defined by inequality and equality constraints such that all functions are, at least, Dini differentiable (in some cases, Hadamard differentiable and sometimes, quasiconvex). Several constraint qualifications are given in such a way that generalize both the qualifications introduced by Maeda and the classical ones, when the functions are differentiable. The relationships between them are analyzed. Finally, we give several Kuhn-Tucker...
We consider a multiobjective optimization problem with a feasible set
defined by inequality and equality constraints such that all functions
are, at least, Dini differentiable (in some cases, Hadamard differentiable
and sometimes, quasiconvex). Several constraint qualifications are given
in such a way that generalize both the qualifications introduced by Maeda
and the classical ones, when the functions are differentiable. The
relationships between them are analyzed. Finally, we give several
Kuhn-Tucker...
Part II of the paper aims at providing conditions which may serve as a bridge between existing stability assertions and asymptotic results in probability theory and statistics. Special emphasis is put on functions that are expectations with respect to random probability measures. Discontinuous integrands are also taken into account. The results are illustrated applying them to functions that represent probabilities.
Continuous convergence and epi-convergence of sequences of random functions are crucial assumptions if mathematical programming problems are approximated on the basis of estimates or via sampling. The paper investigates “almost surely” and “in probability” versions of these convergence notions in more detail. Part I of the paper presents definitions and theoretical results and Part II is focused on sufficient conditions which apply to many models for statistical estimation and stochastic optimization....
We consider the following version of the standard problem of empirical estimates in stochastic optimization. We assume that the underlying random vectors are independent and not necessarily identically distributed but that they satisfy a "slow variation" condition in the sense of the definition given in this paper. We show that these assumptions along with the usual restrictions (boundedness and equicontinuity) on a class of functions allow one to use the empirical mean method to obtain a consistent...
This paper shows that cycling of the simplex method for the m × n transportation problem where k-1 zero basic variables are leaving and reentering the basis does not occur once it does not occur in the k × k assignment problem. A method to disprove cycling for a particular k is applied for k=2,3,4,5 and 6.
In this paper we introduce some improvements on an approach that we described elsewhere for solving a modification of the well-known extended rapid transit network design problem. Firstly, we propose an integer programming model for selecting the stations to be constructed and the links between them, in such a way that a connected rapid transit network is obtained. Secondly, we consider a linear 0-1 programming model for determining a route of minimum length in the rapid transit network between...
In this paper we introduce some improvements on an approach that we described elsewhere
for solving a modification of the well-known extended rapid transit network design
problem. Firstly, we propose an integer programming model for selecting the stations to be
constructed and the links between them, in such a way that a connected rapid transit
network is obtained. Secondly, we consider a linear 0-1 programming model for determining
a route of minimum...
In this paper we present the image space analysis, based on a general separation scheme, with the aim of studying lagrangian duality and shadow prices in Vector Optimization. Two particular kinds of separation are considered; in the linear case, each of them is applied to the study of sensitivity analysis, and it is proved that the derivatives of the perturbation function can be expressed in terms of vector Lagrange multipliers or shadow prices.
In this paper we present the image space analysis, based
on a general separation scheme, with the aim of studying Lagrangian duality
and shadow prices in Vector Optimization. Two particular kinds of separation
are considered; in the linear case, each of them is applied to the study of
sensitivity analysis, and it is proved that the derivatives of the
perturbation function can be expressed in terms of vector Lagrange
multipliers or shadow prices.
We investigate the existence of the solution to the following problem
min φ(x) subject to G(x)=0,
where φ: X → ℝ, G: X → Y and X,Y are Banach spaces. The question of existence is considered in a neighborhood of such point x₀ that the Hessian of the Lagrange function is degenerate. There was obtained an approximation for the distance of solution x* to the initial point x₀.
Currently displaying 41 –
60 of
353