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iterative linear-programming SOLUTION OF CONVEX-PROGRAMS

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 1990年第1期65卷 53-65页

作者： FERRIS, MC 1. Computer Sciences Department University of Wisconsin Madison Wisconsin

An iterative linear programming algorithm for the solution of the convex programming problem is proposed. The algorithm partially solves a sequence of linear programming subproblems whose solution is shown to converge quadratically, superlinearly, or linearly to the solution of the convex program, depending on the accuracy to which the subproblems are solved. The given algorithm is related to inexact Newton methods for the nonlinear complementarity problem. Preliminary results for an implementation of the algorithm are given.

关键词： iterative linear programming complementarity problems inexact Newton methods finite termination

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Matheuristics based on iterative linear programming and slope scaling for multicommodity capacitated fixed charge network design

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2018年第1期268卷 70-81页

作者： Gendron, Bernard Hanafi, Said Todosijevic, Raca Univ Montreal Dept Informat & Rech Operat Interuniv Res Ctr Enterprise Networks Logist & Tr Montreal PQ Canada Univ Valenciennes LAMIH UMR CNRS 8201 F-59313 Valenciennes 9 France

We present new matheuristics for the multicommodity capacitated fixed-charge network design problem (MCND). The matheuristics are based on combining iterative linear programming (ILP) methods and slope scaling (SS) heuristics. Each iteration alternates between solving a linear program obtained by adding pseudo-cuts and a restricted mixed-integer programming (MIP) model. The SS heuristic is used as a warm start to a state-of-the-art generic method that solves the restricted MIP model. The resulting ILP/SS matheuristics are compared against state-of-the-art heuristics for the MCND on a set of large-scale difficult instances. The computational results show that the approach is competitive: when performed for a time limit of 1 hour, it finds more best solutions than any other heuristic, using comparable running times;when performed for a time limit of 5 hours, it identifies an optimal solution for each instance for which an optimal solution is known and it is able to find new best solutions for some very hard instances. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Heuristics Mixed-integer programming Multicommodity capacitated fixed charge network design iterative linear programming Slope scaling

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Automatic Estimation of Decoding Parameters Using Large-Margin iterative linear programming

Automatic Estimation of Decoding Parameters Using Large-Marg...

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10th INTERSPEECH 2009 Conference

作者： Mak, Brian Ko, Tom Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781615676927

The decoding parameters in automatic speech recognition grammar factor and word insertion penalty are usually determined by performing a grid search on a development set. Recently, we cast their estimation as a convex optimization problem, and proposed a solution using an iterative linear programming algorithm. However, the solution depends on how well the development data set matches with the test set. In this paper, we further investigates an improvement on the generalization property of the solution by using large margin training within the iterative linear programming framework. Empirical evaluation on the WSJ0 5K speech recognition tasks shows that the recognition performance of the decoding parameters found by the improved algorithm using only a subset of the acoustic model training data is even better than that of the decoding parameters found by grid search on the development data, and is close to the performance of those found by grid search on the test set.

关键词： discriminative training convex optimization large margin training iterative linear programming ranking support vector machine

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Min-max Discriminative Training of Decoding Parameters Using iterative linear programming

Min-max Discriminative Training of Decoding Parameters Using...

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9th Annual Conference of the International-Speech-Communication-Association (INTERSPEECH 2008)

作者： Mak, Brian Ko, Tom Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781615673780

In automatic speech recognition, the decoding parameters - grammar factor and word insertion penalty - are usually hand-tuned to give the best recognition performance. This paper investigates an automatic procedure to determine their values using an iterative linear programming (LP) algorithm. LP naturally implements discriminative training by mapping linear discriminants into LP constraints. A min-max cost function is also defined to get more stable and robust result. Empirical evaluations on the RM1 and WSJ0 speech recognition tasks show that decoding parameters found by the proposed algorithm are as good as those found by a brute-force grid search;their optimal values also seem to be independent of the initial values set to start the iterative LP algorithm.

关键词： iterative linear programming discriminative training decoding parameters min-max optimization

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Discriminative training by iterative linear programming optimization

Discriminative training by iterative linear programming opti...

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33rd IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Mak, Brian Ng, Benny Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781424414833

In this paper, we cast discriminative training problems into standard linear programming (LP) optimization. Besides being convex and having globally optimal solution(s), LP program are wen-studied with well-established solutions, and efficient LP solvers are freely available. In practice, however, one may not have complete knowledge of the feasible region since it is constructed from a limited number of competing hypotheses based on the current model - not the final model which, by definition, is not known a priori at the time of hypotheses generation. We investigate an iterative LP optimization algorithm in which an additional constraint on the parameters being optimized is further imposed. Our proposed method is evaluated on the estimation of global and state-dependent stream weights and biases of a multi-stream hidden Markov model system. Results show that the stream weights and biases found by our iterative LP optimization algorithm may give better recognition performance than the ones found by a brute-force grid search.

关键词： iterative linear programming discriminative training multi-stream HMM parameter tying

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Rapid design of system-wide metabolic network modifications using iterative linear programming

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IFAC Proceedings Volumes 2010年第5期43卷 391-396页

作者： Laurence Yang William R. Cluett Radhakrishnan Mahadevan Department of Chemical Engineering & Applied Chemistry University of Toronto Toronto ON M5S3E5 Canada Institute of Biomaterials and Biomedical Engineering University of Toronto Toronto ON M5S3E5 Canada

Computationally-aided metabolic engineering is an important, complementary strategy to combinatorial strain design for enhanced biochemical production by microbes. Bilevel optimization problems have been formulated for optimal strain design via reaction removal, activation, and inhibition. Deterministic global optimization of the resulting mixed integer linear programs (MILPs) requires extensive computational effort, especially for genome-scale models of metabolism. Improving the computational efficiency of such algorithms is an ongoing challenge. Here, we present Enhancing Metabolism with iterative linear Optimization (EMILiO)–a novel bilevel optimization-based algorithm that includes all possible flux modifications and is solved with remarkable computational efficiency via iterative linear programming. The resulting solution is recursively pruned to generate alternate, parsimonious strain designs with maximal biochemical production rates. We demonstrate our algorithm for succinate production using the i AF1260 genome-scale model of Escherichia coli metabolism. Our algorithm identifies aerobic succinate-producing strains with increased glyoxylate shunt activity, which is consistent with experiments in the literature. We also identified novel strain design strategies that may have implications for the control of industrial bioreactors to maximize succinate production.

关键词： mathematical programming biotechnology integer programming iterative linear programming metabolic engineering complementarity constraints successive linear programming flux balance analysis succinate production

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Lexicographic maxmin fairness for data collection in wireless sensor networks

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2007年第7期6卷 762-776页

作者： Chen, Shigang Fang, Yuguang Xia, Ye Univ Florida Dept Comp & Informat Sci & Engn Gainesville FL 32611 USA Univ Florida Dept Elect & Comp Engn Gainesville FL 32611 USA

The ad hoc deployment of a sensor network causes unpredictable patterns of connectivity and varied node density, resulting in uneven bandwidth provisioning on the forwarding paths. When congestion happens, some sensors may have to reduce their data rates. It is an interesting but difficult problem to determine which sensors must reduce rates and how much they should reduce. This paper attempts to answer a fundamental question about congestion resolution: What are the maximum rates at which the individual sensors can produce data without causing congestion in the network and unfairness among the peers? We define the maxmin optimal rate assignment problem in a sensor network, where all possible forwarding paths are considered. We provide an iterative linear programming solution, which finds the maxmin optimal rate assignment and a forwarding schedule that implements the assignment in a low-rate sensor network. We prove that there is one and only one such assignment for a given configuration of the sensor network. We also study the variants of the maxmin fairness problem in sensor networks.

关键词： multipath maxmin fairness wireless sensor networks data collection applications iterative linear programming

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Limit analysis of masonry walls by rigid block modelling with cracking units and cohesive joints using linear programming

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ENGINEERING STRUCTURES 2013年 57卷 232-247页

作者： Portioli, Francesco Cascini, Lucrezia Casapulla, Claudia D'Aniello, Mario Univ Naples Federico II Dept Struct Engn & Architecture I-80134 Naples Italy

In this paper a rigid block model with cracking units and cohesive joints is developed for limit analysis of masonry structures using linear programming. The model is applicable to in-plane loaded unreinforced masonry block walls with regular textures and provides as output failure loads and collapse mechanisms. A simplified micro-modelling approach is adopted, based on the discretization of masonry units into triangular blocks separated by contact interfaces. Tensionless contact interfaces are used to model dry joints and cohesive contacts are introduced for mortar joints and internal unit interfaces. Failure modes at contact interfaces involve cracking, crushing and sliding. An iterative solution procedure is used to model non-associative flow rule in sliding and to take into account no-tension behaviour of cohesive joints in case of cracking. The modelling approach is validated and applied to different structural examples from the literature, including unconfined and confined masonry panels and a masonry beam. To show the accuracy of the proposed model and the improvement of the predicted response, the obtained results are compared with experimental tests and with the outcomes of standard rigid block models using a single block per masonry unit and tensionless interfaces. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： In-plane loaded masonry walls Rigid block model Cracking units Cohesive joints Limit analysis iterative linear programming

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Parametric analysis of metabolic fluxes of α-amylase and protease-producing Bacillus subtilis

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BIOPROCESS AND BIOSYSTEMS ENGINEERING 2007年第5期30卷 337-348页

作者： Skolpap, W. Nuchprayoon, S. Scharer, J. M. Moo-Young, M. Thammasat Univ Dept Chem Engn Pathum Thani 12120 Thailand Chiang Mai Univ Dept Elect Engn Chiang Mai 50000 Thailand Univ Waterloo Dept Chem Engn Waterloo ON N2L 3G1 Canada

Parametric analysis was applied for a metabolic flux model for the fed-batch culture of Bacillus subtilis producing recombinant alpha-amylase and protease. The metabolic flux model was formulated as a linear programming problem consisting of 49 reactions (decision variables) and 50 metabolites (equality constraints). This study was aimed to determine the response of the metabolic fluxes and objective function value of minimizing the difference between ATP consumption and ATP production (ATP balance). With regard to intracellular metabolite accumulation, the objective function value was least sensitive to variation in succinate and most sensitive to variation in malate. Amongst the variations in the accumulation rates of extracellular metabolites, the objective function value was least sensitive to variation in glutamate and most sensitive to variation in starch hydrolysis and triglyceride synthesis. A 10% variation in metabolite accumulation rates caused a maximum of 13.8% variation (standard error = 3.8%) in the objective function value.

关键词： parametric analysis flux balance analysis Bacillus subtilis iterative linear programming

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