3期

最新文章

• Duality gaps in nonconvex stochastic optimization AI翻译
  作者：Dentcheva, D; Römisch, W
  作者单位：Stevens Institute of Technology; Humboldt University of Berlin
  摘要：We consider multistage stochastic optimization models containing nonconvex constraints, e.g., due to logical or integrality requirements. We study three variants of Lagrangian relaxations and of the corresponding decomposition schemes, namely, scenario, nodal and geographical decomposition. Based on convex equivalents for the Lagrangian duals, we compare the duality gaps for these decomposition schemes. The first main result states that scenario decomposition provides a smaller or equal dualit...
• Estimation of an optimal solution of a LP problem with unknown objective function - A stochastic approximation approach based on the simplex method AI翻译
  作者：Prieto-Rumeau, T
  作者单位：Universidad Nacional de Educacion a Distancia (UNED)
  摘要：We consider a linear programming problem with unknown objective function. Random observations related to the unknown objective function are sequentially available. We define a stochastic algorithm, based on the simplex method, that estimates an optimal solution of the linear programming problem. It is shown that this algorithm converges with probability one to the set of optimal solutions and that its failure probability is of order inversely proportional to the sample size. We also introduce ...
• Global optimization of mixed-integer nonlinear programs: A theoretical and computational study AI翻译
  作者：Tawarmalani, M; Sahinidis, NV
  作者单位：Purdue University System; Purdue University; University of Illinois System; University of Illinois Urbana-Champaign
  摘要：This work addresses the development of an efficient solution strategy for obtaining global optima of continuous. integer. and mixed-integer nonlinear programs. Towards this end, we develop novel relaxation schemes, range reduction tests, and branching strategies which we incorporate into the prototypical branch-and-bound algorithm. In the theoretical/algorithmic part of the paper. we begin by developing novel strategies for constructing linear relaxations of mixed-integer nonlinear programs an...
• Solving variational inequality and fixed point problems by line searches and potential optimization AI翻译
  作者：Magnanti, TL; Perakis, G
  作者单位：Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT); Massachusetts Institute of Technology (MIT)
  摘要：We introduce a general adaptive line search framework for solving fixed point and variational inequality problems. Our goals are to develop iterative schemes that (i) compute solutions when the underlying map satisfies properties weaker than contractiveness, for example, weaker forms of nonexpansiveness, (ii) are more efficient than the classical methods even when the underlying map is contractive, and (iii) unify and extend several convergence results from the fixed point and variational ineq...
• Holder and Lipschitz stability of solution sets in programs with probabilistic constraints AI翻译
  作者：Henrion, R; Römisch, W
  作者单位：Leibniz Association; Weierstrass Institute for Applied Analysis & Stochastics; Humboldt University of Berlin
  摘要：We study perturbations of a stochastic program with a probabilistic constraint and r-concave original probability distribution. First we improve our earlier results substantially and provide conditions implying Holder continuity properties of the solution sets w.r.t. the Kolmogorov distance of probability distributions. Secondly, we derive an upper Lipschitz continuity property for solution sets under more restrictive conditions on the original program and on the perturbed probability measures...
• Optimal accumulation of Jacobian matrices by elimination methods on the dual computational graph AI翻译
  作者：Naumann, U
  作者单位：United States Department of Energy (DOE); Argonne National Laboratory
  摘要：The accumulation of the Jacobian matrix F' of a vector function F : R-n --> R-m can be regarded as a transformation of its linearized computational graph into a subgraph of the directed complete bipartite graph K-n,K-m. This transformation can be performed by applying different elimination techniques that may lead to varying costs for computing F'. This paper introduces face elimination as the basic technique for accumulating Jacobian matrices by using a minimal number of arithmetic operations...
• An accelerated central cutting plane algorithm for linear semi-infinite programming AI翻译
  作者：Betrò, B
  作者单位：Consiglio Nazionale delle Ricerche (CNR); Istituto di Matematica Applicata e Tecnologie Informatiche Enrico Magenes (IMATI-CNR)
  摘要：An algorithm for linear semi-infinite programming is presented which accelerates the convergence of the central cutting plane algorithm first proposed in [4]. Compared with other algorithms, the algorithm in [4] has the advantage of being applicable under mild conditions and of providing feasible solutions. However its convergence has been shown to be rather slow in practical instances. The algorithm proposed in this paper introduces a simple acceleration scheme which gives faster convergence,...
• An optimization approach to the problem of protein structure prediction AI翻译
  作者：Eskow, E; Bader, B; Byrd, R; Crivelli, S; Head-Gordon, T; Lamberti, V; Schnabel, R
  作者单位：University of Colorado System; University of Colorado Boulder; United States Department of Energy (DOE); Lawrence Berkeley National Laboratory; University of California System; University of California Berkeley; University of California System; University of California Berkeley; United States Department of Energy (DOE); Lawrence Berkeley National Laboratory; United States Department of Energy (DOE); Lawrence Berkeley National Laboratory; University of California System; University of California Berkeley
  摘要：We describe a large-scale, stochastic-perturbation global optimization algorithm used for determining the structure of proteins. The method incorporates secondary structure predictions (which describe the more basic elements of the protein structure) into the starting structures, and thereafter minimizes using a purely physics-based energy model. Results show this method to be particularly successful on protein targets where structural information from similar proteins is unavailable, i.e., th...
• Sub-quadratic convergence of a smoothing Newton algorithm for the P0 and monotone LCP AI翻译
  作者：Huang, ZH; Qi, LQ; Sun, DF
  作者单位：Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; Hong Kong Polytechnic University; National University of Singapore
  摘要：Given M is an element of R-nxn and q is an element of R-n, the linear complementarity problem (LCP) is to find (x, s) is an element of R-n x R-n such that (x, s) greater than or equal to 0, s = M-x + q, x(T)s = 0. By using the Chen-Harker-Kanzow-Sniale (CHKS) smoothing function, the LCP is reformulated as a system of parameterized smooth-nonsmooth equations. As a result, a smoothing Newton algorithm, which is a modified version of the Qi-Sun-Zhou algorithm [Matheniatical Programming, Vol. 87, ...
• Proximity theorems of discrete convex functions AI翻译
  作者：Murota, K; Tamura, A
  作者单位：University of Tokyo; Japan Science & Technology Agency (JST); Kyoto University
  摘要：A Proximity theorem is a statement that, given an optimization problem and its relaxation, an optimal solution to the original problem exists in a certain neighborhood of a solution to the relaxation. Proximity theorems have been used successfully, for example, in designing efficient algorithms for discrete resource allocation problems. After reviewing the recent results for L-convex and M-convex functions, this paper establishes Proximity theorems for larger classes of discrete convex functio...