15 papers · ranked by Valyu relevance
Arash Raeisi Gahrouei, Mehdi Ghatee
Graphics Processing Units (GPUs) with high computational capabilities used as modern parallel platforms to deal with complex computational problems. We use this platform to solve large-scale linear programing problems by revised simplex algorithm. To implement this algorithm, we propose some new memory management…
Q. Huangfu, J. A. J. Hall
This paper introduces the design and implementation of two parallel dual simplex solvers for general large scale sparse linear programming problems. One approach, called PAMI, extends a relatively unknown pivoting strategy called suboptimization and exploits parallelism across multiple iterations. The other, called…
Evgeny Shindin, Michael Masin, Gideon Weiss, Alexander Zadorojniy
—We describe an efficient implementation of a recent simplex-type algorithm for the exact solution of separated continuous linear programs, and compare it with linear programming approximation of these problems obtained via discretization of the time horizon. The implementation overcomes many numerical pitfalls often…
Basilis Mamalis, Marios Perlitis
—The simplex algorithm has been successfully used for many years in solving linear programming (LP) problems. Due to the intensive computations required (especially for the solution of large LP problems), parallel approaches have also extensively been studied. The computational power provided by the modern GPUs as well…
Carsten Gottschlich, Dominic Schuhmacher, Haipeng Peng
Finding solutions to the classical transportation problem is of great importance, since this optimization problem arises in various guises in many real world and theoretical situations. They occur as subproblems in larger problems, e.g. the warehouse location problem or the traveling salesperson problem and also in a…
Syed Inayatullah, Nasir Touheed, Muhammad Imtiaz, Cheng-Yi Xia
This paper proposes a streamlined form of simplex method which provides some great benefits over traditional simplex method. For instance, it does not need any kind of artificial variables or artificial constraints; it could start with any feasible or infeasible basis of an LP. This method follows the same pivoting…
Demétrios Araújo Magalhães Coutinho, Samuel Xavier‐de‐Souza, Daniel Aloise
'Daniel Aloise'] The Simplex tableau has been broadly used and investigated in the industry and academia. With the advent of the big data era, ever larger problems are posed to be solved in ever larger machines whose architecture type did not exist in the conception of this algorithm. In this paper, we present a…
Denis Kleverov, Ekaterina Aladyeva, Alexey Serdyukov, Maxim N. Artyomov
Non-negative matrix factorization (NMF) is one of the most powerful linear algebra tools, which has found application in various areas of data analysis, including computational biology. Despite numerous optimization methods devised for NMF, our comprehension of the inherent topological structure within factorizable…
Hassan Musafer, Emre Tokgoz, Ausif Mahmood, Jingbo Wang
This article provides a new tool for examining the efficiency and robustness of derivative-free optimization algorithms based on high-dimensional normalized data profiles that test a variety of performance metrics. Unlike the traditional data profiles that examine a single dimension, the proposed data profiles require…
Zlatko Pavić
In this study, the simplex whose vertices are barycenters of the given simplex facets plays an essential role. The article provides an extension of the Hermite-Hadamard inequality from the simplex barycenter to any point of the inscribed simplex except its vertices. A two-sided refinement of the generalized inequality…
Colin Lynch, Kaitlin Baudier, Douglas Montgomery, Meghan Barrett
Animal nutritionists seek to understand how animals regulate the intake and balance of multiple nutrients, yet the design and analysis of such experiments are often limited by how nutrient spaces are represented. The geometric framework for nutrition (GFN) provides a powerful means to visualize nutrient interactions…
Lily Cassandra Paulick, Helia Relaño-Iborra, Torsten Dau
This study introduces a revised version of the computational auditory signal processing and perception (CASP) model (15), which has undergone substantial updates and refinements aimed at enhancing its accuracy and usability across various applications. A primary motivation for the revision was the integration of a more…
Pablo Quijano Velasco, Kedar Hippalgaonkar, Balamurugan Ramalingam
The discovery of optimal conditions of chemical reactions is a labor-intensive, time-consuming task that requires exploring a high-dimensional parametric space. Historically the optimization of chemical reactions has been performed by manual experimentation guided by human intuition and Design of Experiments where one…
Dasheng Bi
Sleep spindles are characteristic events in EEG signals during non-REM sleep, and are known to be important biological markers. Manually labeling spindles by visual inspection, however, proves to be a tedious task. Here, a novel system of “Selection-Revision” is introduced to aid in efficient detection of spindles. By…
Kobi Felton, Jan Rittig, Alexei Lapkin
In the fine chemicals industry, reaction screening and optimisation are essential to development of new products. However, this screening can be extremely time and labor intensive, especially when intuition is used. Machine learning offers a solution through iterative suggestions of new experiments based on past…