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A reusable iterative optimization software library to solve combinatorial problems with approximate reasoning [article]

Andreas Raggl, Wolfgang Slany
1998 arXiv   pre-print
We present a combination of approximate reasoning based constraints and iterative optimization based heuristics that help to model and solve such problems in a framework of C++ software libraries called  ...  Real world combinatorial optimization problems such as scheduling are typically too complex to solve with exact methods.  ...  combinatorial problems with approximate reasoning methods is well suited for the problem at hand.  ... 
arXiv:cs/9812017v1 fatcat:2iwouuxeencrhlqr7xczaazcle

A reusable iterative optimization software library to solve combinatorial problems with approximate reasoning

Andreas Raggl, Wolfgang Slany
1998 International Journal of Approximate Reasoning  
We present a combination of approximate reasoning based constraints and iterative optimization based heuristics that help to model and solve such problems in a framework of C++ software libraries called  ...  Real world combinatorial optimization problems such as scheduling are typically too complex to solve with exact methods.  ...  combinatorial problems with approximate reasoning methods is well suited for the problem at hand.  ... 
doi:10.1016/s0888-613x(98)10002-6 fatcat:qxbuyl2edrfmjpepjycvanwrcm

Properties of Realistic Feature Models Make Combinatorial Testing of Product Lines Feasible [chapter]

Martin Fagereng Johansen, Øystein Haugen, Franck Fleurey
2011 Lecture Notes in Computer Science  
For example, satisfying propositional formulas, which translates into finding a valid product for a given feature model, is an NP-hard problem, which has no fast, optimal solution.  ...  Feature models and associated feature diagrams allow modeling and visualizing the constraints leading to the valid products of a product line.  ...  VERDE is a project within the ITEA 2 -Eureka framework.  ... 
doi:10.1007/978-3-642-24485-8_47 fatcat:jyrhtuonnjcije6uy3azsk4m2u

Cognification of Program Synthesis—A Systematic Feature-Oriented Analysis and Future Direction

Ahmad F. Subahi
2020 Computers  
With this advancement, there is a need to gain greater benefits from these approaches to cognify synthesis processes for next-generation model-driven engineering (MDE) framework.  ...  Program synthesis is defined as a software development step aims at achieving an automatic process of code generation that is satisfactory given high-level specifications.  ...  (solving) problem, the machine approximation problem, the combinatorial optimization problem, and the learning (statistical) problem ( Figure 11 ).  ... 
doi:10.3390/computers9020027 fatcat:4t25hhuh4fcsrjzhfriggo5vra

A software framework based on a conceptual unified model for evolutionary multiobjective optimization: ParadisEO-MOEO

Arnaud Liefooghe, Laetitia Jourdan, El-Ghazali Talbi
2011 European Journal of Operational Research  
framework dedicated to the design and the implementation of evolutionary multiobjective optimization techniques: ParadisEO-MOEO.  ...  Please cite this article in press as: Liefooghe, A., et al. A software framework based on a conceptual unified model for evolutionary multiobjective optimization: ParadisEO-MOEO.  ...  and Nouredine Melab for their work on the preliminary version of the ParadisEO-MOEO software framework presented in this paper.  ... 
doi:10.1016/j.ejor.2010.07.023 fatcat:zrunuizuerfmhckhowaic5j43a

Using Anytime Algorithms in Intelligent Systems

Shlomo Zilberstein
1996 The AI Magazine  
This article surveys the main control problems that arise when a system is composed of several anytime algorithms. These problems relate to optimal management of uncertainty and precision.  ...  After a brief introduction to anytime computation, I outline a wide range of existing solutions to the metalevel control problem and describe current work that is aimed at increasing the applicability  ...  For example, when solving a combinatorial optimization problem (such as path planning), the quality of a result depends on how close it is to the optimal answer.  ... 
doi:10.1609/aimag.v17i3.1232 dblp:journals/aim/Zilberstein96 fatcat:632lal5pmbcw3jnvd6aktmmrve

Approaching the Dilemma between Plan and Value in Computer Aided Engineering of Production Machines

Denis Özdemir, Werner Herfs, Christian Brecher
2016 Procedia CIRP  
Modern mathematical optimization methods support the systematic search for a combination of system components and parameters with regards to the defined quality criteria.  ...  This paper presents a methodology to simplify the optimization of machine components, such as feed drives, while taking dynamic quality criteria into account.  ...  Acknowledgement The authors would like to thank the German research Foundation DFG for the kind support within the project "Optimierung des Systementwurfs von Maschinen und Anlagen auf Basis komponentenorientierter  ... 
doi:10.1016/j.procir.2016.01.017 fatcat:ji44xjmzkrhh3pkbqkzt4ggjvq

The Conception of the New Agent-Based Platform for Modeling and Implementation of Parallel Evolutionary Algorithms

Sara Sabba, Salim Chikhi
2014 International Journal of Intelligent Systems and Applications  
Nowadays, EAs have proven their ability and effectiveness to solve combinatorial problems. However, these methods require a considerable time of calculation.  ...  In this paper, we present a new parallel agent-based EC framework for solving numerical optimization problems in order to optimize computation time and solutions quality.  ...  Conclusion Combinatorial optimization methods are in the most cases the stochastic algorithms that take a considerable time to find a reasonable solution to the NP-hard problems.  ... 
doi:10.5815/ijisa.2014.04.02 fatcat:vgsehsc6vvg25k74p3hpxkkhae

MASA : a library for verification using manufactured and analytical solutions

Nicholas Malaya, Kemelli C. Estacio-Hiroms, Roy H. Stogner, Karl W. Schulz, Paul T. Bauman, Graham F. Carey
2012 Engineering with Computers  
In this paper we introduce the Manufactured Analytical Solution Abstraction (MASA) library for applying the method of manufactured solutions to the verification of software used for solving a large class  ...  solutions over a diverse range of problems.  ...  Professor Carey was a mentor and advisor to the authors of this paper and will be greatly missed.  ... 
doi:10.1007/s00366-012-0267-9 fatcat:xm4b3l5245glbdmk2dfbjfmrfy

BCAT: A framework for analyzing the complexity of algorithms

Zoltan Adam Mann, Tamas Szep
2010 IEEE 8th International Symposium on Intelligent Systems and Informatics  
BCAT supports the implementation of computational problems, algorithms to solve the problems, and analyzers to analyze the problems.  ...  This paper presents BCAT (Budapest Complexity Analysis Toolkit), a software package to facilitate research on algorithms and computational complexity.  ...  There are also some commercial software packages with several implemented optimization routines, e.g. the NAG Libraries (http://www.nag.co.uk/numeric/numerical_libraries.asp) or the IMSL Numerical Libraries  ... 
doi:10.1109/sisy.2010.5647446 fatcat:jmw2bhfk7vdinlczjlbd356f7y

Metaheuristics "In the Large" [article]

Jerry Swan, Steven Adriaensen, Alexander E. I. Brownlee, Kevin Hammond, Colin G. Johnson, Ahmed Kheiri, Faustyna Krawiec, J. J. Merelo, Leandro L. Minku, Ender Özcan, Gisele L. Pappa, Pablo García-Sánchez (+4 others)
2021 arXiv   pre-print
However, in order for research in metaheuristics to avoid fragmentation and a lack of reproducibility, there is a pressing need for stronger scientific and computational infrastructure to support the development  ...  Following decades of sustained improvement, metaheuristics are one of the great success stories of optimization research.  ...  Scalability is also an issue when solving ever larger problem instances: despite the increase in computing power, it is hard to solve large instances of many practical optimization problems.  ... 
arXiv:2011.09821v4 fatcat:7rmva4ri6fbx7gijsgkhlercry

Software Tools Supporting Integration [chapter]

Tallys Yunes
2010 Hybrid Optimization  
This chapter provides a brief survey of existing software tools that enable, facilitate and/or support the integration of different optimization techniques.  ...  We focus on tools that have achieved a reasonable level of maturity and whose published results have demonstrated their effectiveness.  ...  Acknowledgments The author would like to thank Timo Berthold, Stefan Heinz, Susanne Heipcke, Katya Krasilnikova, Michela Milano, Philippe Refalo, Nick Sahinidis, Kish Shen, Helmut Simonis, Peter Stuckey  ... 
doi:10.1007/978-1-4419-1644-0_12 fatcat:4nwki37zszdt7kswhu7idd2nme

A GPU-based iterated tabu search for solving the quadratic 3-dimensional assignment problem

The Van Luong, Lakhdar Loukil, Nouredine Melab, El-Ghazali Talbi
2010 ACS/IEEE International Conference on Computer Systems and Applications - AICCSA 2010  
It has been proved to be one of the most difficult combinatorial optimization problems.  ...  Local search (LS) algorithms are a class of heuristics which have been successfully applied to solve such hard optimization problem.  ...  Tabu search (TS) method is a deterministic local search metaheuristic used to solve combinatorial optimization problems.  ... 
doi:10.1109/aiccsa.2010.5587019 dblp:conf/aiccsa/LuongLMT10 fatcat:qy6jioewz5eateaeg3g3xy4x2u

14th International Symposium on Mathematical Programming

1990 Mathematical programming  
If we use a decomposition approach in order to solve a minimization problem we often get an objective function in such a w a y that its domain dom 6 = n is not given explicitely to us.  ...  to the well known serious steps und null steps of bundle methods a third type of steps is used to generate the model of dom .  ...  cases any reasonable objective function cannot be given for modelling and solving a compound optimization problem.  ... 
doi:10.1007/bf01580875 fatcat:3jtclwmntzgjxkqs5uecombdaa

Randomized Algorithms for Scientific Computing (RASC) [article]

Aydin Buluc, Tamara G. Kolda, Stefan M. Wild, Mihai Anitescu, Anthony DeGennaro, John Jakeman, Chandrika Kamath, Ramakrishnan Kannan, Miles E. Lopes, Per-Gunnar Martinsson, Kary Myers, Jelani Nelson (+7 others)
2021 arXiv   pre-print
Randomized algorithms have propelled advances in artificial intelligence and represent a foundational research area in advancing AI for Science.  ...  A specific technique is randomized rounding for stylized combinatorial optimization problems.  ...  Randomized algorithms for solving well-defined problems on networks Randomized algorithms are used to provide approximate solutions to many subgraph counting problems with errors diminishing with sample  ... 
arXiv:2104.11079v2 fatcat:qwwowtufzvbfjaiotx733eexxe
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