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arXiv 2024年

作者： Bolusani, Suresh Besançon, Mathieu Bestuzheva, Ksenia Chmiela, Antonia Dionísio, João Donkiewicz, Tim van Doornmalen, Jasper Eifler, Leon Ghannam, Mohammed Gleixner, Ambros Graczyk, Christoph Halbig, Katrin Hedtke, Ivo Hoen, Alexander Hojny, Christopher van der Hulst, Rolf Kamp, Dominik Koch, Thorsten Kofler, Kevin Lentz, Jurgen Manns, Julian Mexi, Gioni Mühmer, Erik Pfetsch, Marc E. Schlösser, Franziska Serrano, Felipe Shinano, Yuji Turner, Mark Vigerske, Stefan Weninger, Dieter Xu, Liding Gaul, Oliver Zuse Institute Berlin Department AIS2T Takustr. 7 Berlin14195 Germany Université Grenoble Alpes Inria LIG Grenoble38000 France CMUP Department of Computer Science Faculty of Sciences University of Porto R Campo Alegre Porto4169-007 Portugal RWTH Aachen University Lehrstuhl für Operations Research Kackertstr. 7 Aachen52072 Germany Eindhoven University of Technology Department of Mathematics and Computer Science P.O. Box 513 Eindhoven5600 MB Netherlands Friedrich-Alexander Universität Erlangen-Nürnberg Department of Data Science Cauerstr. 11 Erlangen91058 Germany Schenker AG Global Data & AI Kruppstr. 4 Essen45128 Germany University of Twente Department of Discrete Mathematics and Mathematical Programming P.O. Box 217 Enschede7500 AE Netherlands University of Bayreuth Universitaetsstr. 30 Bayreuth95440 Germany Technische Universität Berlin Straße des 17. Juni 135 Berlin10623 Germany Zuse Institute Berlin Department A2IM Takustr. 7 Berlin14195 Germany DAGOPT Optimization Technologies GmbH Austria Technische Universität Darmstadt Fachbereich Mathematik Dolivostr. 15 Darmstadt64293 Germany Fair Isaac Germany GmbH Takustr. 7 Berlin14195 Germany COPT GmbH Berlin Germany GAMS Software GmbH c/o Zuse Institute Berlin Department AIS2T Takustr. 7 Berlin14195 Germany Friedrich-Alexander Universität Erlangen-Nürnberg Department of Mathematics Cauerstr. 11 Erlangen91058 Germany École polytechnique LIX CNRR Rue Honoré d’Estienne d’Orves. 1 Palaiseau9120 France

MSC Codes 90C05, 90C10, 90C11, 90C30, 90C90, 65Y05The SCIP Optimization Suite provides a collection of software packages for mathematical optimization, centered around the constraint integer programming (CIP) framework SCIP. This report discusses the enhancements and extensions included in SCIP Optimization Suite 9.0. The updates in SCIP 9.0 include improved symmetry handling, additions and improvements of nonlinear handlers and primal heuristics, a new cut generator and two new cut selection schemes, a new branching rule, a new LP interface, and several bugfixes. SCIP Optimization Suite 9.0 also features new Rust and C++ interfaces for SCIP, new Python interface for SoPlex, along with enhancements to existing interfaces. SCIP Optimization Suite 9.0 also includes new and improved features in the LP solver SoPlex, the presolving library PaPILO, the parallel framework UG, the decomposition framework GCG, and the SCIP extension SCIP-SDP. These additions and enhancements have resulted in an overall performance improvement of SCIP in terms of solving time, number of nodes in the branch-and-bound tree, as well as the reliability of the solver. Copyright © 2024, The Authors. All rights reserved.

关键词： Mixed-integer linear programming

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Preface

Communications in Computer and Information Science

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Communications in computer and Information Science 2019年 1007卷 V-VIII页

作者： Ermolayev, Vadim Suárez-Figueroa, Mari Carmen Yakovyna, Vitaliy Mayr, Heinrich C. Nikitchenko, Mykola Spivakovsky, Aleksander Zaporizhzhya National University Zaporizhzhia Ukraine Universidad Politecnica de Madrid Boadilla del MonteMadrid Spain Lviv Polytechnic National University Lviv Ukraine Faculty of Mathematics and Computer Science University of Warmia and Mazury in Olsztyn Olsztyn Poland Institute of Applied Informatics Alpen-Adria-Universität Klagenfurt Klagenfurt Austria Department of Theory and Technology of Programming Taras Shevchenko National University of Kyiv Kyiv Ukraine Kherson State University Kherson Ukraine

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Enabling Research through the SCIP Optimization Suite 8.0

arXiv

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arXiv 2023年

作者： Bestuzheva, Ksenia Besançon, Mathieu Chen, Wei-Kun Chmiela, Antonia Donkiewicz, Tim van Doornmalen, Jasper Eifler, Leon Gaul, Oliver Gamrath, Gerald Gleixner, Ambros Gottwald, Leona Graczyk, Christoph Halbig, Katrin Hoen, Alexander Hojny, Christopher van der Hulst, Rolf Koch, Thorsten Lübbecke, Marco Maher, Stephen J. Matter, Frederic Mühmer, Erik Müller, Benjamin Pfetsch, Marc E. Rehfeldt, Daniel Schlein, Steffan Schlösser, Franziska Serrano, Felipe Shinano, Yuji Sofranac, Boro Turner, Mark Vigerske, Stefan Wegscheider, Fabian Wellner, Philipp Weninger, Dieter Witzig, Jakob Zuse Institute Berlin Department AIS2T Takustr. 7 Berlin14195 Germany ZIB-AIS2T Germany School of Mathematics and Statistics Beijing Institute of Technology Beijing100081 China RWTH Aachen University Lehrstuhl für Operations Research Kackertstr. 7 Aachen52072 Germany Eindhoven University of Technology Department of Mathematics and Computer Science Netherlands ZIB-AIS2T I2DAMO GmbH Englerallee 19 Berlin14195 Germany ZIB-AIS2T HTW Berlin Germany Friedrich-Alexander Universität Erlangen-Nürnberg Department of Data Science Cauerstr. 11 Erlangen91058 Germany University of Twente Department of Discrete Mathematics and Mathematical Programming P.O. Box 217 Enschede7500 AE Netherlands Technische Universität Berlin Software and Algorithms for Discrete Optimization Straße des 17. Juni 135 Berlin10623 Germany ZIB Department A2IM Takustr. 7 Berlin14195 Germany RWTH Aachen-Lehrstuhl für OR Germany University of Exeter College of Engineering Mathematics and Physical Sciences Exeter United Kingdom Technische Universität Darmstadt Fachbereich Mathematik Dolivostr. 15 Darmstadt64293 Germany TU Darmstadt Fachbereich Mathematik Germany ZIB-A2IM Germany TU Berlin Germany ZIB-A2IM Software and Algorithms for Discrete Optimization Institute of Mathematics TU Berlin Germany GAMS Software GmbH c/o ZIB-AIS2T Germany

The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. The focus of this paper is on the role of the SCIP Optimization Suite in supporting research. SCIP's main design principles are discussed, followed by a presentation of the latest performance improvements and developments in version 8.0, which serve both as examples of SCIP's application as a research tool and as a platform for further developments. Further, the paper gives an overview of interfaces to other programming and modeling languages, new features that expand the possibilities for user interaction with the framework, and the latest developments in several extensions built upon *** Codes 90C05, 90C10, 90C11, 90C30, 90C90, 65Y05 Copyright © 2023, The Authors. All rights reserved.

关键词： Integer programming

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The SCIP optimization suite 8.0

arXiv

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arXiv 2021年

作者： Bestuzheva, Ksenia Besançon, Mathieu Chen, Wei-Kun Chmiela, Antonia Donkiewicz, Tim Van Doornmalen, Jasper Eifler, Leon Gaul, Oliver Gamrath, Gerald Gleixner, Ambros Gottwald, Leona Graczyk, Christoph Halbig, Katrin Hoen, Alexander Hojny, Christopher Van Der Hulst, Rolf Koch, Thorsten Lübbecke, Marco Maher, Stephen J. Matter, Frederic Mühmer, Erik Müller, Benjamin Pfetsch, Marc E. Rehfeldt, Daniel Schlein, Steffan Schlösser, Franziska Serrano, Felipe Shinano, Yuji Sofranac, Boro Turner, Mark Vigerske, Stefan Wegscheider, Fabian Wellner, Philipp Weninger, Dieter Witzig, Jakob Zuse Institute Berlin Department AIS2T Takustr. 7 Berlin14195 Germany School of Mathematics and Statistics Beijing Institute of Technology Beijing100081 China RWTH Aachen University Lehrstuhl für Operations Research Kackertstr. 7 Aachen52072 Germany Technische Universiteit Eindhoven Department of Mathematics and Computer Science P.O. Box 513 Eindhoven5600 MB Netherlands I2DAMO GmbH Englerallee 19 Berlin14195 Germany Friedrich-Alexander Universität Erlangen-Nürnberg Department of Data Science Cauerstr. 11 Erlangen91058 Germany University of Twente Department of Discrete Mathematics and Mathematical Programming P.O. Box 217 Enschede7500 AE Netherlands Technische Universität Berlin Software and Algorithms for Discrete Optimization Straße des 17. Juni 135 Berlin10623 Germany Zuse Institute Berlin Department A2IM Takustr. 7 Berlin14195 Germany University of Exeter College of Engineering Mathematics and Physical Sciences Exeter United Kingdom Technische Universität Darmstadt Fachbereich Mathematik Dolivostr. 15 Darmstadt64293 Germany Technische Universität Berlin Straße des 17. Juni 135 Berlin10623 Germany Software and Algorithms for Discrete Optimization Institute of Mathematics Technische Universität Berlin Straße des 17. Juni 135 Berlin10623 Germany GAMS Software GmbH C/o Zuse Institute Berlin Department AIS2T Takustr. 7 Berlin14195 Germany

The SCIP Optimization Suite provides a collection of software packages for mathematical optimization centered around the constraint integer programming framework SCIP. This paper discusses enhancements and extensions contained in version 8.0 of the SCIP Optimization Suite. Major updates in SCIP include improvements in symmetry handling and decomposition algorithms, new cutting planes, a new plugin type for cut selection, and a complete rework of the way nonlinear constraints are handled. Additionally, SCIP 8.0 now supports interfaces for Julia as well as Matlab. Further, UG now includes a unified framework to parallelize all solvers, a utility to analyze computational experiments has been added to GCG, dual solutions can be postsolved by PaPILO, new heuristics and presolving methods were added to SCIP-SDP, and additional problem classes and major performance improvements are available in *** Codes 90C05, 90C10, 90C11, 90C30, 90C90, 65Y05 Copyright © 2021, The Authors. All rights reserved.

关键词： Integer programming

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Correction to: A new cognitive clock matching phenotypic and epigenetic ages

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Translational psychiatry 2022年第1期12卷 452页

作者： M I Krivonosov E V Kondakova N A Bulanov S A Polevaya C Franceschi M V Ivanchenko M V Vedunova Institute of Biology and Biomedicine Department of Neurotechnology N. I. Lobachevsky State University Nizhny Novgorod Russia. krivonosov@itmm.unn.ru. Institute of Information Technology Mathematics and Mechanics Department of Applied Mathematics N. I. Lobachevsky State University Nizhny Novgorod Russia. krivonosov@itmm.unn.ru. Research Center for Trusted Artificial Intelligence The Ivannikov Institute for System Programming of the Russian Academy of Sciences Moscow 109004 Russia. krivonosov@itmm.unn.ru. Research Center for Trusted Artificial Intelligence The Ivannikov Institute for System Programming of the Russian Academy of Sciences Moscow 109004 Russia. Institute of Biology and Biomedicine Department of Basic and Medical Genetics N. I. Lobachevsky State University Nizhny Novgorod Russia. Faculty of Computer Science School of Data Analysis and Artificial Intelligence HSE University Moscow Russia. Faculty of Social Sciences Department of Psychophysiology N. I. Lobachevsky State University Nizhny Novgorod Russia. Institute of Information Technology Mathematics and Mechanics Department of Applied Mathematics N. I. Lobachevsky State University Nizhny Novgorod Russia. Department of Experimental Diagnostic and Specialty Medicine (DIMES) University of Bologna Bologna Italy.

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CLEER - AN AI-SYSTEM DEVELOPED TO ASSIST EQUIPMENT ARRANGEMENTS ON WARSHIPS

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NAVAL ENGINEERS JOURNAL 1989年第3期101卷 127-137页

作者： ZHOU, HH SILVERMAN, BG SIMKOL, J Dr. H. Harry Zhou:is a research professor at the Institute for Artificial Intelligence of The George Washington University. Dr. Zhou received his master's degree and Ph.D. in computer science from Vanderbilt University in 1984 and 1987 respectively. He did his dissertation in the fields of artificial intelligence analogical reasoning and machine learning. His research interests include: classifier systems genetic algorithms learning by analogy inductive learning adaptive expert systems automated knowledge acquisition and adaption. He is also interested in data base design programming languages mental modeling and software engineering. Dr. Barry G. Silverman:is director of the Institute for Artificial Intelligence and a professor at the Engineering Administration Department of The George Washington University. He is also president of IntelliTek Inc. an AI consulting firm. Dr. Silverman received the B.S.E. M.S.E. and Ph.D. degrees from the University of Pennsylvania. He has been a principal developer of four generic AI products as well as eight AI applications. Since 1979 he has written over 100 papers and reports on these AI efforts. Joel Simkol:is a research scientist currently engaged in designing expert system architectures to support electronic warfare vulnerability analyses threat assessments shipboard topside antenna arrangements and C3countermeasures employment. Mr. Simkol's work in applying expert systems technology to electromagnetic interference and to spectrum management has generated increased interest and participation from all branches of government agencies.

This paper describes a modularized AI system being built to help improve electromagnetic compatibility (EMC) among shipboard topside equipment and their associated systems. CLEER is intended to act as an easy to use integrator of existing expert knowledge and pre-existing data bases and large scale analytical models. Due to these interfaces; to the need for portability of the software; and to artificial intelligence related design requirements (such as the need for spatial reasoning, expert data base management, model base management, track-based reasoning, and analogical (similar ship) reasoning) it was realized that traditional expert system shells would be inappropriate, although relatively off-the-shelf AI technology could be incorporated. In the same vein, the rapid prototyping approach to expert system design and knowledge engineering was not pursued in favor of a rigorous systems engineering methodology. The critical design decisions affecting CLEER's development are summarized in this paper along with lessons learned to date all in terms of “how,” “why,” and “when” specific features are being developed.

关键词： Artificial Intelligence

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ROLE OF SIMULATION IN RAPID PROTOTYPING FOR CONCEPT DEVELOPMENT

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NAVAL ENGINEERS JOURNAL 1991年第3期103卷 204-211页

作者： KING, JF BARTON, DE J. Fred King:is the manager of the Advanced Technology Department for Unisys in Reston Virginia. He earned his Ph.D. in mathematics from the University of Houston in 1977. He has been principal investigator of research projects in knowledge engineering pattern recognition and heuristic problem-solving. Efforts include the development of a multi-temporal multispectral classifier for identifying graincrops using LANDSAT satellite imagery data for NASA. Also as a member of the research team for a NCI study with Baylor College of Medicine and NASA he helped develop techniques for detection of carcinoma using multispectral microphotometer scans of lung tissue. He established and became technical director of the AI Laboratory for Ford Aerospace where he developed expert scheduling modeling and knowledge acquisition systems for NASA. Since joining Unisys in 1985 he has led the development of object-oriented programming environments blackboard architectures data fusion techniques using neural networks and intelligent data base systems. Douglas E. Barton:is manager of Logistics Information Systems for Unisys in Reston Virginia. He earned his B.A. degree in computer science from the College of William and Mary in 1978 and did postgraduate work in London as a Drapers Company scholar. Since joining Unisys in 1981 his work has concentrated on program management and software engineering of large scale data base management systems and design and implementation of knowledge-based systems in planning and logistics. As chairman of the Logistics Data Subcommittee of the National Security Industrial Association (NSIA) he led an industry initiative which examined concepts in knowledge-based systems in military logistics. His responsibilities also include evaluation development and tailoring of software engineering standards and procedures for data base and knowledge-based systems. He is currently program manager of the Navigation Information Management System which provides support to the Fleet Ballistic Missile Progr

A valuable technique during concept development is rapid prototyping of software for key design components. This approach is particularly useful when the optimum design approach is not readily apparent or several known alternatives need to be rapidly evaluated. A problem inherent in rapid prototyping is the lack of a "target system" with which to interface. Some alternatives are to develop test driver libraries, integrate the prototype with an existing working simulator, or build one for the specific problem. This paper presents a unique approach to concept development using rapid prototyping for concept development and scenario-based simulation for concept verification. The rapid prototyping environment, derived from artificial intelligence technology, is based on a blackboard architecture. The rapid prototype simulation capability is provided through an object-oriented modeling environment. It is shown how both simulation and blackboard technologies are used collectively to rapidly gain insight into a tenacious problem. A specific example will be discussed where this approach was used to evolve the logic of a mission controller for an autonomous underwater vehicle.

关键词： Military Engineering

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Publisher Correction: Re-analysis of public genetic data reveals a rare X-chromosomal variant associated with type 2 diabetes

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Nature communications 2018年第1期9卷 2162页

作者： Sílvia Bonàs-Guarch Marta Guindo-Martínez Irene Miguel-Escalada Niels Grarup David Sebastian Elias Rodriguez-Fos Friman Sánchez Mercè Planas-Fèlix Paula Cortes-Sánchez Santi González Pascal Timshel Tune H Pers Claire C Morgan Ignasi Moran Goutham Atla Juan R González Montserrat Puiggros Jonathan Martí Ehm A Andersson Carlos Díaz Rosa M Badia Miriam Udler Aaron Leong Varindepal Kaur Jason Flannick Torben Jørgensen Allan Linneberg Marit E Jørgensen Daniel R Witte Cramer Christensen Ivan Brandslund Emil V Appel Robert A Scott Jian'an Luan Claudia Langenberg Nicholas J Wareham Oluf Pedersen Antonio Zorzano Jose C Florez Torben Hansen Jorge Ferrer Josep Maria Mercader David Torrents Barcelona Supercomputing Center (BSC) Joint BSC-CRG-IRB Research Program in Computational Biology 08034 Barcelona Spain. Genomic Programming of Beta-cells Laboratory Institut d'Investigacions August Pi i Sunyer (IDIBAPS) 08036 Barcelona Spain. Instituto de Salud Carlos III Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM) 28029 Madrid Spain. Section of Epigenomics and Disease Department of Medicine Imperial College London London W12 0NN UK. The Novo Nordisk Foundation Center for Basic Metabolic Research Section for Metabolic Genetics Faculty of Health and Medical Sciences University of Copenhagen 2100 Copenhagen Denmark. Institute for Research in Biomedicine (IRB Barcelona) The Barcelona Institute of Science and Technology Baldiri Reixac 10-12 08028 Barcelona Spain. Departament de Bioquímica i Biomedicina Molecular Facultat de Biologia Universitat de Barcelona 08028 Barcelona Spain. Computer Sciences Department Barcelona Supercomputing Center (BSC-CNS) 08034 Barcelona Spain. Department of Epidemiology Research Statens Serum Institut 2300 Copenhagen Denmark. Division of Endocrinology and Center for Basic and Translational Obesity Research Boston Children's Hospital Boston MA 02116 USA. Medical and Population Genetics Program Broad Institute of MIT and Harvard Cambridge MA 02142 USA. ISGlobal Centre for Research in Environmental Epidemiology (CREAL) 08003 Barcelona Spain. CIBER Epidemiología y Salud Pública (CIBERESP) 28029 Madrid Spain. Universitat Pompeu Fabra (UPF) 08003 Barcelona Spain. Artificial Intelligence Research Institute (IIIA) Spanish Council for Scientific Research (CSIC) 28006 Madrid Spain. Programs in Metabolism and Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA 02142 USA. Diabetes Unit and Center for Genomic Medicine Massachusetts General Hospital Boston MA 02114 USA. Division of General Internal Medicine Massachusetts General Hospital Bost

In the originally published version of this Article, the affiliation details for Santi González, Jian'an Luan and Claudia Langenberg were inadvertently omitted. Santi González should have been affiliated with 'Barcelona Supercomputing Center (BSC), Joint BSC-CRG-IRB Research Program in Computational Biology, 08034 Barcelona, Spain', and Jian'an Luan and Claudia Langenberg should have been affiliated with 'MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK'. Furthermore, the abstract contained an error in the SNP ID for the rare variant in chromosome Xq23, which was incorrectly given as rs146662057 and should have been rs146662075. These errors have now been corrected in both the PDF and HTML versions of the Article.

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