Directed graphs, Hamiltonicity and doubly stochastic matrices

نویسندگان

  • Vivek S. Borkar
  • Vladimir Ejov
  • Jerzy A. Filar
چکیده

We consider the Hamiltonian cycle problem embedded in singularly perturbed (controlled)Markov chains. We also consider a functional on the space of stationary policies of the process that consists of the (1,1)-entry of the fundamental matrices of the Markov chains induced by the same policies. In particular, we focus on the subset of these policies that induce doubly stochastic probability transition matrices, which we refer to as the “doubly stochastic policies.” We show that when the perturbation parameter ε is sufficiently small the minimum of this functional over the space of the doubly stochastic policies is attained very close to a Hamiltonian cycle, provided that the graph is Hamiltonian. We also derive precise analytical expressions for the elements of the fundamental matrix that lend themselves to probabilistic interpretation as well as asymptotic expressions for the first diagonal element, for a variety of deterministic policies that are of special interest, including those that correspond to Hamiltonian cycles. © 2004 Wiley Periodicals, Inc. Random Struct. Alg., 25, 376–395, 2004

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

On the Hamiltonicity Gap and doubly stochastic matrices

We consider the Hamiltonian cycle problem embedded in singularly perturbed (controlled) Markov chains. We also consider a functional on the space of stationary policies of the process that consists of the (1,1)-entry of the fundamental matrices of the Markov chains induced by these policies. We focus on the subset of these policies that induce doubly stochastic probability transition matrices w...

متن کامل

Distributed Mirror Descent over Directed Graphs

In this paper, we propose Distributed Mirror Descent (DMD) algorithm for constrained convex optimization problems on a (strongly-)connected multi-agent network. We assume that each agent has a private objective function and a constraint set. The proposed DMD algorithm employs a locally designed Bregman distance function at each agent, and thus can be viewed as a generalization of the well-known...

متن کامل

Some results on the symmetric doubly stochastic inverse eigenvalue problem

‎The symmetric doubly stochastic inverse eigenvalue problem (hereafter SDIEP) is to determine the necessary and sufficient conditions for an $n$-tuple $sigma=(1,lambda_{2},lambda_{3},ldots,lambda_{n})in mathbb{R}^{n}$ with $|lambda_{i}|leq 1,~i=1,2,ldots,n$‎, ‎to be the spectrum of an $ntimes n$ symmetric doubly stochastic matrix $A$‎. ‎If there exists an $ntimes n$ symmetric doubly stochastic ...

متن کامل

On Doubly Stochastic Graph Optimization

In this paper we introduce an approximate optimization framework for solving graphs problems involving doubly stochastic matrices. This is achieved by using a low dimensional formulation of the matrices and the approximate solution is achieved by a simple subgradient method. We also describe one problem that can be solved using our method.

متن کامل

Double-null operators and the investigation of Birkhoff's theorem on discrete lp spaces

Doubly stochastic matrices play a fundamental role in the theory of majorization. Birkhoff's theorem explains the relation between $ntimes n$ doubly stochastic matrices and permutations. In this paper, we first introduce double-null  operators and we will find some important properties of them. Then with the help of double-null operators, we investigate Birkhoff's theorem for descreate $l^p$ sp...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Random Struct. Algorithms

دوره 25  شماره 

صفحات  -

تاریخ انتشار 2004