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- K A Ariyawansa, P L Jiang
- 1996

Traditional simplex-basedalgorithms for two-stage stochastic linear programscan be broadly divided into two classes: (a) those that explicitly exploit the structure of the equivalent large-scale linear program and (b) those based on cutting planes (or equivalently on decomposition) that implicitly exploit that structure. Algorithms of class (b) are in… (More)

- Burke, Tseng Goldstein, Ye For Convex, Minimax Problems, K A Ariyawansa, P L Jiang
- 2007

Burke, Goldstein, Tseng and Ye (Ref. 1) have presented an interesting interior point algorithm for a class of smooth convex minimax problems. They have also presented a complexity analysis leading to a worst-case bound on the total work necessary to obtain a solution within a prescribed tolerance. In this paper we present reenements to the analysis of Burke… (More)

- K A Ariyawansa, P L Jiang
- 2007

Recently, Bertsimas and Orlin 1] have given polynomial complexity for several combinatorial optimization subproblems using Vaidya's volumetric center algorithm as a subroutine. These complexity results improve on the previously best known for several problems, including for example computing the Held-Karp lower bound for Traveling Sales-person problem and… (More)

- V K Jandhyala, P L Jiang
- 2007

We determine the eigenvalues of a Fredholm integral operator of the second kind. The solution of the eigenvalue problem has applications to nding the distribution function of a stochastic integral. The stochastic integral itself represents the asymptotic form of a statistical test. Also discussed are related results for inference and applications.

- K A Ariyawansa, P L Jiang
- 2007

Burke, Goldstein, Tseng and Ye 4] have presented an interior point algorithm for the smooth convex minimax problem: minimization of the pointwise maximum of n thrice-diierentiable convex functions of m variables. Their algorithm is based on analytic centers. The novel feature of their algorithm relative to several other algorithms based on analytic centers… (More)

- K A Ariyawansa, P L Jiang
- 2007

We point out several oversights in statements concerning stochastic programming in a paper of Bertsimas and Orlin (this journal, 1994).

In this paper, we consider the extended linear-quadratic problems arising in stochas-tic programming. This class of problems is a nonlinear extension of the two-stage stochastic linear programming problem considered in [3]. The work reported in this paper is an analog of the work in [3] with extensions of the three polynomial cutting plane algorithms given… (More)

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