21 papers · ranked by Valyu relevance
Daniel Dadush, Friedrich Eisenbrand, Thomas Rothvoß
Approximate integer programming is the following: For a given convex body K ⊆ R n , either determine whether K ∩Z n is empty, or find an integer point in the convex body 2·(K −c)+c which is K, scaled by 2 from its center of gravity c. Approximate integer programming can be solved in time 2O(n) while the fastest known…
Daniel Dadush, Friedrich Eisenbrand, Thomas Rothvoss
Approximate integer programming is the following: For a given convex body $K \subseteq{\mathbb{R}}^n$, either determine whether $K \cap{\mathbb{Z}}^n$ is empty, or find an integer point in the convex body $2\cdot K - c +c$ which is K, scaled by 2 from its center of gravity c. Approximate integer programming can be…
Robert Nieuwenhuis, Albert Oliveras, Enric Rodríguez-Carbonell
State-of-the-art SAT solvers are nowadays able to handle huge real-world instances. The key to this success is the so-called Conflict-Driven Clause-Learning (CDCL) scheme, which encompasses a number of techniques that exploit the conflicts that are encountered during the search for a solution. In this article we extend…
Marcin Briański, Martin Koutecký, Daniel Král’, Kristýna Pekárková + 1 more
An intensive line of research on fixed parameter tractability of integer programming is focused on exploiting the relation between the sparsity of a constraint matrix A and the norm of the elements of its Graver basis. In particular, integer programming is fixed parameter tractable when parameterized by the primal…
Pravesh Koirala, Mel Krusniak, Forrest Laine
Integer programming games (IPGs) are -person games with integer strategy spaces. These games are used to model non-cooperative combinatorial decision-making and are used in domains such as cybersecurity and transportation. The prevalent solution concept for IPGs, Nash equilibrium, is difficult to compute and even…
Martin Gonzalez, Jose J. López-Espín, Juan Aparicio, El-Ghazali Talbi + 1 more
'El-Ghazali Talbi' 'Nicholas Higham'] Mixed Integer Linear Programs (MILPs) are usually NP-hard mathematical programming problems, which present difficulties to obtain optimal solutions in a reasonable time for large scale models. Nowadays, metaheuristics are one of the potential tools for solving this type of problems…
Virgile Andreani, Eric J. South, Mary J. Dunlop
Dense arrangements of binding sites within nucleotide sequences can collectively influence downstream transcription rates or initiate biomolecular interactions. For example, natural promoter regions can harbor many overlapping transcription factor binding sites that influence the rate of transcription initiation.…
Xiang He, Peng Lin, Shaowei Cai
Integer Quadratic Programming (IQP) is an important problem in operations research. Local search is a powerful method for solving hard problems, but the research on local search algorithms for IQP solving is still on its early stage. This paper develops an efficient local search solver for solving general IQP, called…
Authors not listed
We present a vector-based method to balance chemical reactions. The algorithm builds candidates in a deterministic way, removes duplicates, and always prints coefficients in the lowest whole-number form. For redox cases, electrons and protons/hydroxide are treated explicitly, so both mass and charge are balanced. We…
Jamie Fravel, Robert Hildebrand
An integer program is called ideal if its continuous relaxation coincides with its convex hull allowing the problem to be solved as a continuous program and offering substantial computational advantages. Proving idealness analytically can be extraordinarily tedious—even for small formulations—such proofs often span…
Elisabeth Gaar, Markus Sinnl
The discrete -neighbor -center problem (d--CP) is an emerging variant of the classical -center problem which recently got attention in literature. In this problem, we are given a discrete set of points and we need to locate facilities on these points in such a way that the maximum distance between each point where no…
Pouya Ahadi, Balabhaskar Balasundaram, Juan S. Borrero, Charles Chen
In this study, we address the mate selection problem in the hybridization stage of a breeding pipeline, which constitutes the multi-objective breeding goal key to the performance of a variety development program. The solution framework we formulate seeks to ensure that individuals with the most desirable genomic…
Ghanshyam Chandra, Md Helal Hossen, Stephan Scholz, Alexander T Dilthey + 2 more
Affordable genotyping methods are essential in genomics. Commonly used genotyping methods primarily support single nucleotide variants and short indels but neglect structural variants. Additionally, accuracy of read alignments to a reference genome is unreliable in highly polymorphic and repetitive regions, further…
Conor F. Hayes, Steven A. Magana-Zook, Andre Gonçalves, Ahmet Can Solak + 2 more
We propose a novel approach for antibody library design that combines deep learning and multi-objective linear programming with diversity constraints. Our method leverages recent advances in sequence and structure-based deep learning for protein engineering to predict the effects of mutations on antibody properties.…
Ahmad Abdi, Gérard Cornuéjols, Bertrand Guenin, Levent Tunçel
A rational number is dyadic if it has a finite binary representation $p/2^k$, where p is an integer and k is a nonnegative integer. Dyadic rationals are important for numerical computations because they have an exact representation in floating-point arithmetic on a computer. A vector is dyadic if all its entries are…
Henri Schmidt, Benjamin J. Raphael
Reconstructing unobserved ancestral states of a phylogenetic tree provides insight into the history of evolving systems and is one of the fundamental problems in phylogenetics. For a fixed phylogenetic tree, the most parsimonious ancestral reconstruction – a solution to the small parsimony problem – can be efficiently…
Daniel Molina-Pérez, Edgar Alfredo Portilla-Flores, Efrén Mezura-Montes, Eduardo Vega-Alvarado + 2 more
'Efrén Mezura-Montes' 'Eduardo Vega-Alvarado' 'María Bárbara Calva-Yañez' 'Thomas Stützle'] Mixed integer nonlinear programming (MINLP) addresses optimization problems that involve continuous and discrete/integer decision variables, as well as nonlinear functions. These problems often exhibit multiple discontinuous…
Lionel Zoubritzky, François-Xavier Coudert
We present here an open-source Julia library for the topological identification of crystalline materials, with algorithmic and computational improvements over the previously available software in the field, resulting in a speed increase of one order of magnitude. This new algorithm and implementation can therefore be…
Authors not listed
Automated chemistry platforms hold the potential to enable large-scale organic synthesis campaigns, such as producing a library of compounds for biological evaluation. The efficiency of such platforms will depend on the schedule according to which the synthesis operations are executed. In this work, we study the…
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Experimental design plays an important role in efficiently acquiring informative data for system characterization and deriving robust conclusions under resource limitations. Recent advancements in high-throughput experimentation coupled with machine learning have notably improved experimental procedures. While Bayesian…
Leon Eifler, Jules Nicolas-Thouvenin, Ambros Gleixner
This article studies a combination of the two state-of-the-art algorithms for the exact solution of linear programs (LPs) over the rational numbers, i.e., without any roundoff errors or numerical tolerances. By integrating the method of precision boosting inside an LP iterative refinement loop, the combined algorithm…