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Статті в журналах з теми "Algorithmes Branch-And-Cut"
Fragoso, Felipe C., Gilberto F. de Sousa Filho, and Fábio Protti. "Declawing a graph: polyhedra and Branch-and-Cut algorithms." Journal of Combinatorial Optimization 42, no. 1 (April 19, 2021): 85–124. http://dx.doi.org/10.1007/s10878-021-00736-y.
Повний текст джерелаCosta, Luciano, Claudio Contardo, and Guy Desaulniers. "Exact Branch-Price-and-Cut Algorithms for Vehicle Routing." Transportation Science 53, no. 4 (July 2019): 946–85. http://dx.doi.org/10.1287/trsc.2018.0878.
Повний текст джерелаPereira, Dilson Lucas, Michel Gendreau, and Alexandre Salles da Cunha. "Branch-and-cut and Branch-and-cut-and-price algorithms for the adjacent only quadratic minimum spanning tree problem." Networks 65, no. 4 (February 2, 2015): 367–79. http://dx.doi.org/10.1002/net.21580.
Повний текст джерелаFouilhoux, Pierre, A. Ridha Mahjoub, Alain Quilliot, and Hélène Toussaint. "Branch-and-Cut-and-Price algorithms for the preemptive RCPSP." RAIRO - Operations Research 52, no. 2 (April 2018): 513–28. http://dx.doi.org/10.1051/ro/2018031.
Повний текст джерелаCalvete, Herminia I., Concepción Domínguez, Carmen Galé, Martine Labbé, and Alfredo Marín. "The rank pricing problem: Models and branch-and-cut algorithms." Computers & Operations Research 105 (May 2019): 12–31. http://dx.doi.org/10.1016/j.cor.2018.12.011.
Повний текст джерелаLi, Xiangyong, and Y. P. Aneja. "Regenerator location problem: Polyhedral study and effective branch-and-cut algorithms." European Journal of Operational Research 257, no. 1 (February 2017): 25–40. http://dx.doi.org/10.1016/j.ejor.2016.07.032.
Повний текст джерелаDuchenne, Éric, Gilbert Laporte, and Frédéric Semet. "Branch-and-cut algorithms for the undirected m-Peripatetic Salesman Problem." European Journal of Operational Research 162, no. 3 (May 2005): 700–712. http://dx.doi.org/10.1016/j.ejor.2003.09.024.
Повний текст джерелаArchetti, Claudia, Nicola Bianchessi, and M. Grazia Speranza. "Branch-and-cut algorithms for the split delivery vehicle routing problem." European Journal of Operational Research 238, no. 3 (November 2014): 685–98. http://dx.doi.org/10.1016/j.ejor.2014.04.026.
Повний текст джерелаDesaulniers, Guy, Diego Pecin, and Claudio Contardo. "Selective pricing in branch-price-and-cut algorithms for vehicle routing." EURO Journal on Transportation and Logistics 8, no. 2 (June 2019): 147–68. http://dx.doi.org/10.1007/s13676-017-0112-9.
Повний текст джерелаDi Summa, Marco, Andrea Grosso, and Marco Locatelli. "Branch and cut algorithms for detecting critical nodes in undirected graphs." Computational Optimization and Applications 53, no. 3 (February 9, 2012): 649–80. http://dx.doi.org/10.1007/s10589-012-9458-y.
Повний текст джерелаДисертації з теми "Algorithmes Branch-And-Cut"
Ndiaye, Ndèye Fatma. "Algorithmes d'optimisation pour la résolution du problème de stockage de conteneurs dans un terminal portuaire." Thesis, Le Havre, 2015. http://www.theses.fr/2015LEHA0002/document.
Повний текст джерелаAIn this thesis, we trait the container storage problem at port terminal. Initially, we present a state of the art in which the work that have been previously made in this filed are analyzed. After that, we present an analytical study. Thed we propose a mathematical modelling and some methods of resolution including effective algorithms. We propose a demonstration of the complexity of the problem by considering different cases of storage. This problme is "Np_difficult, so not always easy to solve by using the optimization software "ILOG CPLEX”. This is why we propose a branch-and-cut algorithm, wich is an optimal resolution algorithm and wich enables to go beyong the limits of "ILOG CPLEX". We also proposed meta-heuristic algorithms and hybridizations wich provide satisfactory resulys and wich required less calculation times
Hassan, Abdeljabbar Hassan Mohammed Albarra. "Parallel Scheduling in the Cloud Systems : Approximate and Exact Methods." Thesis, Université de Lorraine, 2016. http://www.theses.fr/2016LORR0223/document.
Повний текст джерелаThe Cloud Computing appears as a strong concept to share costs and resources related to the use of end-users. As a consequence, several related models exist and are widely used (IaaS, PaaS, SaaS. . .). In this context, our research focused on the design of new methodologies and algorithms to optimize performances using the scheduling and combinatorial theories. We were interested in the performance optimization of a Cloud Computing environment where the resources are heterogeneous (operators, machines, processors...) but limited. Several scheduling problems have been addressed in this thesis. Our objective was to build advanced algorithms by taking into account all these additional specificities of such an environment and by ensuring the performance of solutions. Generally, the scheduling function consists in organizing activities in a specific system imposing some rules to respect. The scheduling problems are essential in the management of projects, but also for a wide set of real systems (telecommunication, computer science, transportation, production...). More generally, solving a scheduling problem can be reduced to the organization and the synchronization of a set of activities (jobs or tasks) by exploiting the available capacities (resources). This execution has to respect different technical rules (constraints) and to provide the maximum of effectiveness (according to a set of criteria). Most of these problems belong to the NP-Hard problems class for which the majority of computer scientists do not expect the existence of a polynomial exact algorithm unless P=NP. Thus, the study of these problems is particularly interesting at the scientific level in addition to their high practical relevance. In particular, we aimed to build new efficient combinatorial methods for solving parallel-machine scheduling problems where resources have different speeds and tasks are linked by precedence constraints. In our work we studied two methodological approaches to solve the problem under the consideration : exact and meta-heuristic methods. We studied three scheduling problems, where the problem of task scheduling in cloud environment can be generalized as unrelated parallel machines, and open shop scheduling problem with different constraints. For solving the problem of unrelated parallel machines with precedence constraints, we proposed a novel genetic-based task scheduling algorithms in order to minimize maximum completion time (makespan). These algorithms combined the genetic algorithm approach with different techniques and batching rules such as list scheduling (LS) and earliest completion time (ECT). We reviewed, evaluated and compared the proposed algorithms against one of the well-known genetic algorithms available in the literature, which has been proposed for the task scheduling problem on heterogeneous computing systems. Moreover, this comparison has been extended to an existing greedy search method, and to an exact formulation based on basic integer linear programming. The proposed genetic algorithms show a good performance dominating the evaluated methods in terms of problems' sizes and time complexity for large benchmark sets of instances. We also extended three existing mathematical formulations to derive an exact solution for this problem. These mathematical formulations were validated and compared to each other by extensive computational experiments. Moreover, we proposed an integer linear programming formulations for solving unrelated parallel machine scheduling with precedence/disjunctive constraints, this model based on the intervaland m-clique free graphs with an exponential number of constraints. We developed a Branch-and-Cut algorithm, where the separation problems are based on graph algorithms. [...]
Mkadem, Mohamed Amine. "Flow-shop with time delays, linear modeling and exact solution approaches." Thesis, Compiègne, 2017. http://www.theses.fr/2017COMP2390/document.
Повний текст джерелаIn this thesis, we study the two-machine flow-shop problem with time delays in order to minimize the makespan. First, we propose a set of Mixed Integer Programming (MIP) formulations for the problem. In particular, we introduce a new compact mathematical formulation for the case where operations are identical per machine. The proposed mathematical formulations are then used to develop lower bounds and a branch-and-cut method. A set of valid inequalities is proposed in order to improve the linear relaxation of the MIPs. These inequalities are based on proposing new dominance rules and computing optimal solutions of polynomial-time-solvable sub-instances. These sub-instances are extracted by computing all maximal cliques on a particular Interval graph. In addition to the valid inequalities, the branch-and-cut method includes the consideration of a heuristic method and a node pruning procedure. Finally, we propose a branch-and-bound method. For which, we introduce a local search-based heuristic and dominance rules. Experiments were conducted on a variety of classes of instances including both literature and new proposed ones. These experiments show the efficiency of our approaches that outperform the leading methods published in the research literature
Yuan, Yuan. "Modèles et Algorithmes pour les Problèmes de Livraison du Dernier Kilomètre avec Plusieurs Options d'Expédition." Thesis, Ecole centrale de Lille, 2019. http://www.theses.fr/2019ECLI0011.
Повний текст джерелаIn this thesis, we study routing problems that arise in the context of last mile delivery when multiple delivery options are proposed to the customers. The most common option to deliver packages is home/workplace delivery. Besides, the delivery can be made to pick-up points such as dedicated lockers or stores. In recent years, a new concept called trunk/in-car delivery has been proposed. Here, customers' packages can be delivered to the trunks of cars. Our goal is to model and develop efficient solution approaches for routing problems in this context, in which each customer can have multiple shipping locations. First, we survey non-Hamiltonian routing problems. Then, we study the single-vehicle case in the considered context, which is modeled as a Generalized Traveling Salesman Problem with Time Windows (GTSPTW). Four mixed integer linear programming formulations and an efficient branch-and-cut algorithm are proposed. Finally, we study the multi-vehicle case which is denoted Generalized Vehicle Routing Problem with Time Windows (GVRPTW). An efficient column generation based heuristic is proposed to solve it
Vo, Thi Quynh Trang. "Algorithms and Machine Learning for fair and classical combinatorial optimization." Electronic Thesis or Diss., Université Clermont Auvergne (2021-...), 2024. http://www.theses.fr/2024UCFA0035.
Повний текст джерелаCombinatorial optimization is a field of mathematics that searches for an optimal solution in a finite set of objects. It has crucial applications in many fields, including applied mathematics, software engineering, theoretical computer science, and machine learning. extit{Branch-and-cut} is one of the most widely-used algorithms for solving combinatorial optimization problems exactly. In this thesis, we focus on the computational aspects of branch-and-cut when studying two critical dimensions of combinatorial optimization: extit{the fairness of solutions} and extit{the integration of machine learning}.In Partef{part:1} (Chaptersef{chap:bnc-btsp} andef{chap:owa}), we study two common approaches to deal with the issue of fairness in combinatorial optimization, which has gained significant attention in the past decades. The first approach is extit{balanced combinatorial optimization}, which finds a fair solution by minimizing the difference between the largest and smallest components used. Due to the difficulties in bounding these components, to the best of our knowledge, no general exact framework based on mixed-integer linear programming (MILP) has been proposed for balanced combinatorial optimization. To address this gap, in Chapteref{chap:bnc-btsp}, we present a branch-and-cut algorithm and a novel class of local cutting planes tailored for balanced combinatorial optimization problems. We demonstrate the effectiveness of the proposed framework in the Balanced Traveling Salesman Problem. Additionally, we introduce bounding algorithms and mechanisms to fix variables to accelerate performance further.The second approach to handling the issue of fairness is extit{Ordered Weighted Average (OWA) combinatorial optimization}, which integrates the OWA operator into the objective function. Due to the ordering operator, OWA combinatorial optimization is nonlinear, even if its original constraints are linear. Two MILP formulations of different sizes have been introduced in the literature to linearize the OWA operator. However, which formulation performs best for OWA combinatorial optimization remains uncertain, as integrating the linearization methods may introduce additional difficulties. In Chapteref{chap:owa}, we provide theoretical and empirical comparisons of the two MILP formulations for OWA combinatorial optimization. In particular, we prove that the formulations are equivalent in terms of the linear programming relaxation. We empirically show that for OWA combinatorial optimization problems, the formulation with more variables can be solved faster with branch-and-cut.In Partef{part:2} (Chapteref{chap:mlbnc}), we develop methods for applying machine learning to enhance fundamental decision problems in branch-and-cut, with a focus on cut generation. Cut generation refers to the decision of whether to generate cuts or to branch at each node of the search tree. We empirically demonstrate that this decision significantly impacts branch-and-cut performance, especially for combinatorial cuts that exploit the facial structure of the convex hull of feasible solutions. We then propose a general framework combining supervised and reinforcement learning to learn effective strategies for generating combinatorial cuts in branch-and-cut. Our framework has two components: a cut detector to predict cut existence and a cut evaluator to choose between generating cuts and branching. Finally, we provide experimental results showing that the proposed method outperforms commonly used strategies for cut generation, even on instances larger than those used for training
Taktak, Raouia. "Survavibility in Multilayer Networks : models and Polyhedra." Thesis, Paris 9, 2013. http://www.theses.fr/2013PA090076/document.
Повний текст джерелаThis thesis deals with a problem related to survivability issues in multilayer IP-over-WDM networks. Given a set of traffic demands for which we know a survivable logical routing in the IP layer, the aim is determine the corresponding survivable topology in the WDM layer. We show that the problem is NP-hard even for a single demand. Moreover, we propose four integer linear programming formulations for the problem. The first one is based on the so-called cut inequalities. We consider the polyhedron associated with the formulation. We identify several families of valid inequalities and discuss their facial aspect. We also develop separation routines. Using this, we devise a Branch-and-Cut algorithm and present experimental results. The second formulation uses paths between terminals of the underlying graph as variables. We devise a Branch-and-Price algorithm based on that formulation. In addition, we investigate a natural formulation for the problem which uses only the design variables. Finally, we propose an extended compact formulation which, in addition to the design variables, uses routing variables. We show that this formulation provides a tighter bound for the problem
Naghmouchi, Mohamed yassine. "Gestion de la sécurité dans les systèmes de télécommunications : modèles, polyèdre et algorithmes." Thesis, Paris Sciences et Lettres (ComUE), 2019. http://www.theses.fr/2019PSLED008.
Повний текст джерелаIn this thesis, we propose a new risk management framework for telecommunication networks. This is based on theconcept of Risk Assessment Graphs (RAGs). These graphs contain two types of nodes: access point nodes, or startingpoints for attackers, and asset-vulnerability nodes. The latter have to be secured. An arc in the RAG represents apotential propagation of an attacker from a node to another. A positive weight, representing the propagation difficulty ofan attacker, is associated to each arc. First, we propose a quantitative risk evaluation approach based on the shortestpaths between the access points and the asset-vulnerability nodes. Then, we consider a risk treatment problem, calledProactive Countermeasure Selection Problem (PCSP). Given a propagation difficulty threshold for each pair of accesspoint and asset-vulnerability node, and a set of countermeasures that can be placed on the asset vulnerability nodes, thePCSP consists in selecting the minimum cost subset of countermeasures so that the length of each shortest path froman access point to an asset vulnerability node is greater than or equal to the propagation difficulty threshold.We show that the PCSP is NP-Complete even when the graph is reduced to an arc. Then, we give a formulation of theproblem as a bilevel programming model for which we propose two single-level reformulations: a compact formulationbased on LP-duality, and a path formulation with an exponential number of constraints, obtained by projection. Moreover,we study the path formulation from a polyhedral point of view. We introduce several classes of valid inequalities. Wediscuss when the basic and valid inequalities define facets. We also devise separation routines for these inequalities.Using this, we develop a Branch-and-Cut algorithm for the PCSP along with an extensive computational study. Thenumerical tests show the efficiency of the polyhedral results from an algorithmic point of view.Our framework applies to a wide set of real cases in the telecommunication industry. We illustrate this in several practicaluse cases including Internet of Things (IoT), Software Defined Network (SDN) and Local Area Networks (LANs). We alsoshow the integration of our approach in a web application
Hassan, Abdeljabbar Hassan Mohammed Albarra. "Parallel Scheduling in the Cloud Systems : Approximate and Exact Methods." Electronic Thesis or Diss., Université de Lorraine, 2016. http://www.theses.fr/2016LORR0223.
Повний текст джерелаThe Cloud Computing appears as a strong concept to share costs and resources related to the use of end-users. As a consequence, several related models exist and are widely used (IaaS, PaaS, SaaS. . .). In this context, our research focused on the design of new methodologies and algorithms to optimize performances using the scheduling and combinatorial theories. We were interested in the performance optimization of a Cloud Computing environment where the resources are heterogeneous (operators, machines, processors...) but limited. Several scheduling problems have been addressed in this thesis. Our objective was to build advanced algorithms by taking into account all these additional specificities of such an environment and by ensuring the performance of solutions. Generally, the scheduling function consists in organizing activities in a specific system imposing some rules to respect. The scheduling problems are essential in the management of projects, but also for a wide set of real systems (telecommunication, computer science, transportation, production...). More generally, solving a scheduling problem can be reduced to the organization and the synchronization of a set of activities (jobs or tasks) by exploiting the available capacities (resources). This execution has to respect different technical rules (constraints) and to provide the maximum of effectiveness (according to a set of criteria). Most of these problems belong to the NP-Hard problems class for which the majority of computer scientists do not expect the existence of a polynomial exact algorithm unless P=NP. Thus, the study of these problems is particularly interesting at the scientific level in addition to their high practical relevance. In particular, we aimed to build new efficient combinatorial methods for solving parallel-machine scheduling problems where resources have different speeds and tasks are linked by precedence constraints. In our work we studied two methodological approaches to solve the problem under the consideration : exact and meta-heuristic methods. We studied three scheduling problems, where the problem of task scheduling in cloud environment can be generalized as unrelated parallel machines, and open shop scheduling problem with different constraints. For solving the problem of unrelated parallel machines with precedence constraints, we proposed a novel genetic-based task scheduling algorithms in order to minimize maximum completion time (makespan). These algorithms combined the genetic algorithm approach with different techniques and batching rules such as list scheduling (LS) and earliest completion time (ECT). We reviewed, evaluated and compared the proposed algorithms against one of the well-known genetic algorithms available in the literature, which has been proposed for the task scheduling problem on heterogeneous computing systems. Moreover, this comparison has been extended to an existing greedy search method, and to an exact formulation based on basic integer linear programming. The proposed genetic algorithms show a good performance dominating the evaluated methods in terms of problems' sizes and time complexity for large benchmark sets of instances. We also extended three existing mathematical formulations to derive an exact solution for this problem. These mathematical formulations were validated and compared to each other by extensive computational experiments. Moreover, we proposed an integer linear programming formulations for solving unrelated parallel machine scheduling with precedence/disjunctive constraints, this model based on the intervaland m-clique free graphs with an exponential number of constraints. We developed a Branch-and-Cut algorithm, where the separation problems are based on graph algorithms. [...]
Ahr, Dino. "Multiple postmen problems fundamentals and new algorithms." Saarbrücken VDM Verlag Dr. Müller, 2004. http://d-nb.info/986348074/04.
Повний текст джерелаHunsaker, Braden K. "Measuring facets of polyhedra to predict usefulness in branch-and-cut algorithms." Diss., Available online, Georgia Institute of Technology, 2004:, 2003. http://etd.gatech.edu/theses/available/etd-04082004-180242/unrestricted/hunsaker%5Fbraden%5Fk%5F200312%5Fphd.pdf.
Повний текст джерелаЧастини книг з теми "Algorithmes Branch-And-Cut"
Nowak, Ivo. "Branch-Cut-and-Price Algorithms." In International Series of Numerical Mathematics, 155–79. Basel: Birkhäuser Basel, 2005. http://dx.doi.org/10.1007/3-7643-7374-1_13.
Повний текст джерелаFortz, Bernard. "A Branch-and-Cut Algorithm." In Network Theory and Applications, 91–114. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4669-6_6.
Повний текст джерелаSalazar-González, Juan-José. "Branch-and-Cut versus Cut-and-Branch Algorithms for Cell Suppression." In Privacy in Statistical Databases, 29–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15838-4_3.
Повний текст джерелаBecker, Bernd, Markus Behle, Friedrich Eisenbrand, and Ralf Wimmer. "BDDs in a Branch and Cut Framework." In Experimental and Efficient Algorithms, 452–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11427186_39.
Повний текст джерелаKyoda, Yoshiaki, Keiko Imai, Fumihiko Takeuchi, and Akira Tajima. "A branch-and-cut approach for minimum weight triangulation." In Algorithms and Computation, 384–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63890-3_41.
Повний текст джерелаMartinelli, Rafael, Diego Pecin, Marcus Poggi, and Humberto Longo. "A Branch-Cut-and-Price Algorithm for the Capacitated Arc Routing Problem." In Experimental Algorithms, 315–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20662-7_27.
Повний текст джерелаBergner, Martin, Marco E. Lübbecke, and Jonas T. Witt. "A Branch-Price-and-Cut Algorithm for Packing Cuts in Undirected Graphs." In Experimental Algorithms, 34–45. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07959-2_4.
Повний текст джерелаAbeledo, Hernán, Ricardo Fukasawa, Artur Pessoa, and Eduardo Uchoa. "The Time Dependent Traveling Salesman Problem: Polyhedra and Branch-Cut-and-Price Algorithm." In Experimental Algorithms, 202–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13193-6_18.
Повний текст джерелаAnjos, Miguel F., Frauke Liers, Gregor Pardella, and Andreas Schmutzer. "Engineering Branch-and-Cut Algorithms for the Equicut Problem." In Discrete Geometry and Optimization, 17–32. Heidelberg: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00200-2_2.
Повний текст джерелаBomze, Immanuel, Markus Chimani, Michael Jünger, Ivana Ljubić, Petra Mutzel, and Bernd Zey. "Solving Two-Stage Stochastic Steiner Tree Problems by Two-Stage Branch-and-Cut." In Algorithms and Computation, 427–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17517-6_38.
Повний текст джерелаТези доповідей конференцій з теми "Algorithmes Branch-And-Cut"
Wang, Zicheng, and Zehui Shao. "A Branch and Cut Algorithm for DNA Encoding." In 2007 Second International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA). IEEE, 2007. http://dx.doi.org/10.1109/bicta.2007.4806461.
Повний текст джерелаReinert, K., H. P. Lenhof, P. Mutzel, K. Mehlhorn, and J. D. Kececioglu. "A branch-and-cut algorithm for multiple sequence alignment." In the first annual international conference. New York, New York, USA: ACM Press, 1997. http://dx.doi.org/10.1145/267521.267845.
Повний текст джерелаMittal, Adhyan Vijeta, Animisha Sharanappa, Konish Bagchi, Senthil Prabu Ramalingam, and Prabhakar Karthikeyan Shanmugam. "Electric Vehicle Charging Scheduling using Branch and Cut Algorithm." In 2023 3rd International Conference on Advanced Research in Computing (ICARC). IEEE, 2023. http://dx.doi.org/10.1109/icarc57651.2023.10145685.
Повний текст джерелаLam, Edward, Pierre Le Bodic, Daniel D. Harabor, and Peter J. Stuckey. "Branch-and-Cut-and-Price for Multi-Agent Pathfinding." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/179.
Повний текст джерелаUematsu, Naoya, Shunji Umetani, and Yoshinobu Kawahara. "An Efficient Branch-and-Cut Algorithm for Approximately Submodular Function Maximization." In 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC). IEEE, 2019. http://dx.doi.org/10.1109/smc.2019.8913989.
Повний текст джерелаSarubbi, J., G. Miranda, H. P. Luna, and G. Mateus. "A Cut-and-Branch algorithm for the Multicommodity Traveling Salesman Problem." In 2008 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI). IEEE, 2008. http://dx.doi.org/10.1109/soli.2008.4682823.
Повний текст джерелаPeng Wang, Yang Wang, and Qing Xia. "Fast bounding technique for branch-and-cut algorithm based monthly SCUC." In 2012 IEEE Power & Energy Society General Meeting. New Energy Horizons - Opportunities and Challenges. IEEE, 2012. http://dx.doi.org/10.1109/pesgm.2012.6345349.
Повний текст джерелаLiangliang Sun, P. B. Luh, Shian-Ching Chiou, Shi-Chung Chang, Jen-Hsuan Ho, Hsin Yuan Chen, Ji-Lun Chen, Joey Chang, and Sam Hsu. "Efficient dual-armed cluster tool performance via branch and cut optimization algorithm." In 2011 9th World Congress on Intelligent Control and Automation (WCICA 2011). IEEE, 2011. http://dx.doi.org/10.1109/wcica.2011.5970651.
Повний текст джерелаZhuozan, Gan. "Combining Deep Learning and Branch-and-Cut Algorithm for Transmission-constrained Unit Commitment." In 2024 9th Asia Conference on Power and Electrical Engineering (ACPEE). IEEE, 2024. http://dx.doi.org/10.1109/acpee60788.2024.10532275.
Повний текст джерелаDjeddi, Saoussen, Tarek Bentahar, Atef Bentahar, Riad Saidi, and Hanane Djellab. "A Comparative Analysis of Branch-Cut and Quality-Guided Algorithms For inSAR Interferogram." In 2024 8th International Conference on Image and Signal Processing and their Applications (ISPA). IEEE, 2024. http://dx.doi.org/10.1109/ispa59904.2024.10536705.
Повний текст джерелаЗвіти організацій з теми "Algorithmes Branch-And-Cut"
CARR, ROBERT D., GIUSEPPE LANCIA, and SORIN ISTRAIL. Branch-and-Cut Algorithms for Independent Set Problems: Integrality Gap and An Application to Protein Structure Alignment. Office of Scientific and Technical Information (OSTI), September 2000. http://dx.doi.org/10.2172/764804.
Повний текст джерела