An Improved Gradient Projection-based Decomposition Technique for Support Vector Machines

In this paper we propose some improvements to a recent decomposition technique for the large quadratic program arising in training support vector machines. As standard decomposition approaches, the technique we consider is based on the idea to optimize, at each iteration, a subset of the variables through the solution of a quadratic programming subproblem. The innovative features of this approach consist in using a very effective gradient projection method for the inner subproblems and a special rule for selecting the variables to be optimized at each step. These features allow to obtain promising performance by decomposing the problem into few large subproblems instead of many small subproblems as usually done by other decomposition schemes. We improve this technique by introducing a new inner solver and a simple strategy for reducing the computational cost of each iteration. We evaluate the effectiveness of these improvements by solving large-scale benchmark problems and by comparison with a widely used decomposition package.     

Balance constraints reduction of large-scale linear programming problems

This paper describes a method and the corresponding algorithms for simplification of large-scale linear programming models. It consists of the elimination of the balance constraints (i.e. constraints with zero RHS term). The idea is to apply some linear transformations to the original problem in order to nullify the balance constraints. These transformations are able to simultaneously eliminate more balance rows. The core of this contribution is the introduction of the reduction matrix and the associated theorems on the equivalent linear programs (original and reduced). The numerical experiments with this method of simplification proved this approach to be beneficial for a large class of LP problems.This research work was done while the first author was at Duisburg University, Mess-, Steuer und Regelungstechnik, Germany, under the greatly appreciated financial assistance given by the Alexander-von-Humboldt Foundation.     

Improved modeling and solution methods for the multi-resource routing problem

This paper presents modeling and solution method improvements for the Multi-Resource Routing Problem (MRRP) with flexible tasks. The MRRP with flexible tasks is used to model routing and scheduling problems for intermodal drayage operations in which two resources (tractors and trailers) perform tasks to transport loaded and empty equipment. Tasks may be either well defined, in which both the origin and the destination of a movement are given, or flexible, in which the origin or the destination is chosen by the model. This paper proposes methods to effectively manage the number of options considered for flexible tasks (either feasible origins for a known destination or feasible destinations for a known origin). This modeling change generates sufficient options to allow for low-cost solutions while maintaining reasonable computational effort. We also propose a new solution method that uses randomized route generation. Computational results from test cases show that these changes improve the quality of solutions by at least 5% in the test cases as compared to methods from previous studies.     

An efficient,scalable approach to hydrolyze flavonoid glucuronides via activation of glycoside bond

Hydrolyzing flavonoid glucuronides into corresponding aglycones posed some significant challenges. To improve acid-catalyzed hydrolysis process of flavonoid glucuronide, structures of glucuronide, hydrolysis parameters and post-processing were optimized. The optimized condition was performed by hydrolysis flavonoid glycoside methyl ester in a mixed solvent consisting of 2 mol/L H₂SO₄/EtOH/H₂O (1/8/1, v/v/v) at 95 °C for 7 h and resulted in up to 90% aglycone yields, minimal byproduct formations and milder hydrolysis conditions. Furthermore, the optimized method avoids tedious purification steps and is easily conducted on a relatively large-scale using economical and commercially available reagents.     

A note on “A LP-based heuristic for a time-constrained routing problem”

In their paper, Avella et al. (2006) investigate a time-constrained routing problem. The core of the proposed solution approach is a large-scale linear program that grows both row- and column-wise when new variables are introduced. Thus, a column-and-row generation algorithm is proposed to solve this linear program optimally, and an optimality condition is presented to terminate the column-and-row generation algorithm. We demonstrate by using Lagrangian duality that this optimality condition is incorrect and may lead to a suboptimal solution at termination.     

单原子分散的Ir-N-C燃料电池阳极抗中毒催化剂

燃料电池的阳极抗中毒研究是重要课题,探索具有超高质量活性和抗CO毒化的阳极催化剂具有显著的科学意义和应用价值。本文成功制备了Ir原子级别分散在N掺杂碳的载体上的新催化剂,并且发现该Ir-N-C对甲酸具有良好的电催化氧化性能,其质量比活性为商业Pd/C的48倍。组装了燃料电池单电池进行测试,结果显示,Ir-N-C催化剂在单电池中的质量比功率密度高达281 mW/mg,较商业Pd/C催化剂提升了3倍。同时,Ir-N-C对CO毒化的耐受性大大增强,经过14000 s的长期测试后,其活性仅衰减68%,优于商业Pd/C催化剂（衰减85%）。并且,该催化剂能够简单有效的大批量制备,为单原子催化剂的大批量制备提供了新思路。     

Non-linear couplings,from the early to the late time universe

Deciphering the mechanisms at play in the formation and evolution of the large-scale structure of the universe is part of the scientific goals of many projects of observational cosmology. In particular, large-scale structure observations can be used to infer mode-coupling effects, whether they come from the physics of the early universe or from its late time evolution. Specificities of such couplings are presented, noting that in principle they can be directly detected through bispectra of the cosmic microwave background temperature anisotropies or density in the local universe. The existence of such couplings have however more far-reaching consequences for the growth of the structure. Those are sketched as well as their possible observational impacts.     

A bump triangular dynamic factorization algorithm for the simplex method

A dynamic factorization algorithm is developed which algebraically partitions the basis inverse in such a manner so that the simplex method can be executed from a series of small inverses and the basis itself. This partition is maintained dynamically so that the additional memory required to represent the basis inverse reduces to this series of small inverses for in-core implementations.The algorithm is intended for use in solving general large-scale linear programming problems. This new method of basis representation should permit rather large problems to be solved completely in-core.Preliminary computational experience is presented and comparisons are made with Reid's sparsity-exploiting variant of the Bartels—Golub decomposition for linear programming bases. The computational experience indicated that a significant reduction in memory requirements can usually be obtained using the dynamic factorization approach with only a slight (up to about 20%) degradation of execution time.This research was supported in part by the Air Force Office of Scientific Research, Air Force System Command, USAF, under AFOSR Contract/Grant Number AFOSR-74-2715.     

POPMUSIC for the point feature label placement problem

Point feature label placement is the problem of placing text labels adjacent to point features on a map so as to maximize legibility. The goal is to choose positions for the labels that do not give rise to label overlaps and that minimize obscuration of features. A practical goal is to minimize the number of overlaps while considering cartographic preferences. This article proposes a new heuristic for solving the point feature label placement problem based on the application of the POPMUSIC frame. Computational experiments show that the proposed heuristic outperformed other recent metaheuristics approaches in the literature. Experiments with problem instances involving up to 10 million points show that the computational time of the proposed heuristic increases almost linearly with the problem size. New problem instances based on real data with more than 13,000 labels are proposed.     

Aggregation and stability analysis of nonlinear complex systems

The problem of stability of large-scale systems in critical cases is investigated. New form of aggregation for essentially nonlinear complex systems is suggested. With the help of this form the sufficient conditions of asymptotic stability are determined. The results obtained are used for the stability analysis of complex systems by the nonlinear approximation and for the investigation of absolute stability conditions for a certain class of nonlinear systems.