Literatura académica sobre el tema "Greedy heuristic algorithms"
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Artículos de revistas sobre el tema "Greedy heuristic algorithms"
Wilt, Christopher y Wheeler Ruml. "Building a Heuristic for Greedy Search". Proceedings of the International Symposium on Combinatorial Search 6, n.º 1 (1 de septiembre de 2021): 131–40. http://dx.doi.org/10.1609/socs.v6i1.18352.
Texto completoWilt, Christopher y Wheeler Ruml. "Effective Heuristics for Suboptimal Best-First Search". Journal of Artificial Intelligence Research 57 (31 de octubre de 2016): 273–306. http://dx.doi.org/10.1613/jair.5036.
Texto completoHignasari, L. Virginayoga. "Komparasi Algoritma Cheapest Insertion Heuristic (CIH) Dan Greedy Dalam Optimasi Rute Pendistribusian Barang". Jurnal Ilmiah Vastuwidya 2, n.º 2 (16 de junio de 2020): 31–39. http://dx.doi.org/10.47532/jiv.v2i2.87.
Texto completoTian, Heng, Fuhai Duan, Yong Sang y Liang Fan. "Novel algorithms for sequential fault diagnosis based on greedy method". Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 234, n.º 6 (2 de mayo de 2020): 779–92. http://dx.doi.org/10.1177/1748006x20914498.
Texto completoPanggabean, Jonas Franky R. "Hybrid Ant Colony Optimization-Genetics Algorithm to Minimize Makespan Flow Shop Scheduling". International Journal of Engineering & Technology 7, n.º 2.2 (5 de marzo de 2018): 40. http://dx.doi.org/10.14419/ijet.v7i2.2.11868.
Texto completoSeeja, K. R. "HybridHAM: A Novel Hybrid Heuristic for Finding Hamiltonian Cycle". Journal of Optimization 2018 (16 de octubre de 2018): 1–10. http://dx.doi.org/10.1155/2018/9328103.
Texto completoSelvi, V. "Clustering Analysis of Greedy Heuristic Method in Zero_One Knapsack Problem". International Journal of Emerging Research in Management and Technology 6, n.º 7 (29 de junio de 2018): 39. http://dx.doi.org/10.23956/ijermt.v6i7.181.
Texto completoSilva Arantes, Jesimar da, Márcio da Silva Arantes, Claudio Fabiano Motta Toledo, Onofre Trindade Júnior y Brian Charles Williams. "Heuristic and Genetic Algorithm Approaches for UAV Path Planning under Critical Situation". International Journal on Artificial Intelligence Tools 26, n.º 01 (febrero de 2017): 1760008. http://dx.doi.org/10.1142/s0218213017600089.
Texto completoK, Gayathri Devi. "A Hybrid Firefly Algorithm Approach for Job Shop Scheduling Problem". International Journal for Research in Applied Science and Engineering Technology 9, n.º 12 (31 de diciembre de 2021): 1436–44. http://dx.doi.org/10.22214/ijraset.2021.39536.
Texto completoKazakovtsev, Lev, Dmitry Stashkov, Mikhail Gudyma y Vladimir Kazakovtsev. "Algorithms with greedy heuristic procedures for mixture probability distribution separation". Yugoslav Journal of Operations Research 29, n.º 1 (2019): 51–67. http://dx.doi.org/10.2298/yjor171107030k.
Texto completoTesis sobre el tema "Greedy heuristic algorithms"
Mathirajan, M. "Heuristic Scheduling Algorithms For Parallel Heterogeneous Batch Processors". Thesis, Indian Institute of Science, 2000. http://hdl.handle.net/2005/196.
Texto completoTurlapaty, Sandhya. "Implementation and Performance Comparison of Some Heuristic Algorithms for Block Sorting". UNF Digital Commons, 2018. https://digitalcommons.unf.edu/etd/816.
Texto completoNeas, Charles Bennett. "A Greedy Search Algorithm for Maneuver-Based Motion Planning of Agile Vehicles". Thesis, Virginia Tech, 2010. http://hdl.handle.net/10919/36213.
Texto completoMaster of Science
TAKADA, Hiroaki, Hiroyuki TOMIYAMA, Gang ZENG y Tetsuo YOKOYAMA. "Static Task Scheduling Algorithms Based on Greedy Heuristics for Battery-Powered DVS Systems". Institute of Electronics, Information and Communication Engineers, 2010. http://hdl.handle.net/2237/15037.
Texto completoHossain, Mohammad Forhad. "Spanning Tree Approach On The Snow Cleaning Problem". Thesis, Högskolan Dalarna, Datateknik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:du-4847.
Texto completoAlthoby, Haeder Younis Ghawi. "Theoritical and numerical studies on the graph partitioning problem". Thesis, Normandie, 2017. http://www.theses.fr/2017NORMC233/document.
Texto completoGiven G=(V,E) a connected undirected graph and a positive integer β(n), where n is number ofvertices, the vertex separator problem (VSP) is to find a partition of V into three classes A,B and Csuch that there is no edge between A and B, max{|A|,|B|}less than or equal β(n), and |C| isminimum. In this thesis, we consider aninteger programming formulation for this problem. Wedescribe some valid inequalties and using these results to develop algorithms based onneighborhood scheme.We also study st-connected vertex separator problem. Let s and tbe two disjoint vertices of V, notadjacent. A st-connected separator in the graph G is a subset S of V\{s,t} such that there are no morepaths between sand tin G[G\S] and the graph G[S] is connected . The st-connected vertex speratorproblem consists in finding such subset with minimum cardinality. We propose three formulationsfor this problem and give some valid inequalities for the polyhedron associated with this problem.We develop also an efficient heuristic to solve this problem
Berger, Karl-Eduard. "Placement de graphes de tâches de grande taille sur architectures massivement multicoeurs". Thesis, Université Paris-Saclay (ComUE), 2015. http://www.theses.fr/2015SACLV026/document.
Texto completoThis Ph.D thesis is devoted to the study of the mapping problem related to massively parallel embedded architectures. This problem arises from industrial needs like energy savings, performance demands for synchronous dataflow applications. This problem has to be solved considering three criteria: heuristics should be able to deal with applications with various sizes, they must meet the constraints of capacities of processors and they have to take into account the target architecture topologies. In this thesis, tasks are organized in communication networks, modeled as graphs. In order to determine a way of evaluating the efficiency of the developed heuristics, mappings, obtained by the heuristics, are compared to a random mapping. This comparison is used as an evaluation metric throughout this thesis. The existence of this metric is motivated by the fact that no comparative heuristics can be found in the literature at the time of writing of this thesis. In order to address this problem, two heuristics are proposed. They are able to solve a dataflow process network mapping problem, where a network of communicating tasks is placed into a set of processors with limited resource capacities, while minimizing the overall communication bandwidth between processors. They are applied on task graphs where weights of tasks and edges are unitary set. The first heuristic, denoted as Task-wise Placement, places tasks one after another using a notion of task affinities. The second algorithm, named Subgraph-wise Placement, gathers tasks in small groups then place the different groups on processors using a notion of affinities between groups and processors. These algorithms are tested on tasks graphs with grid or logic gates network topologies. Obtained results are then compared to an algorithm present in the literature. This algorithm maps task graphs with moderated size on massively parallel architectures. In addition, the random based mapping metric is used in order to evaluate results of both heuristics. Then, in a will to address problems that can be found in industrial cases, application cases are widen to tasks graphs with tasks and edges weights values similar to those that can be found in the industry. A progressive construction heuristic named Regret Based Approach, based on game theory, is proposed. This heuristic maps tasks one after another. The costs of mapping tasks according to already mapped tasks are computed. The process of task selection is based on a notion of regret, present in game theory. The task with the highest value of regret for not placing it, is pointed out and is placed in priority. In order to check the strength of the algorithm, many types of task graphs (grids, logic gates networks, series-parallel, random, sparse matrices) with various size are generated. Tasks and edges weights are randomly chosen using a bimodal law parameterized in order to have similar values than industrial applications. Obtained results are compared to the Task Wise placement, especially adapted for non-unitary values. Moreover, results are evaluated using the metric defined above
Lundquist, Josefin y Linnéa O'Hara. "An optimization model using the Assignment Problem to manage the location of parts : Master Thesis at the engine assembly at Scania CV AB". Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-137825.
Texto completoCombier, Camille. "Mesures de similarité pour cartes généralisées". Phd thesis, Université Claude Bernard - Lyon I, 2012. http://tel.archives-ouvertes.fr/tel-00995382.
Texto completoDe, Souza Bento Da Silva Pedro Paulo. "On the mapping of distributed applications onto multiple Clouds". Thesis, Lyon, 2017. http://www.theses.fr/2017LYSEN089/document.
Texto completoThe Cloud has become a very popular platform for deploying distributed applications. Today, virtually any credit card holder can have access to Cloud services. There are many different ways of offering Cloud services to customers. In this thesis we especially focus on theInfrastructure as a Service (IaaS), a model that, usually, proposes virtualized computing resources to costumers in the form of virtual machines (VMs). Thanks to its attractive pay-as-you-use cost model, it is easier for customers, specially small and medium companies, to outsource hosting infrastructures and benefit of savings related to upfront investments and maintenance costs. Also, customers can have access to features such as scalability, availability, and reliability, which previously were almost exclusive for large companies. To deploy a distributed application, a Cloud customer must first consider the mapping between her application (or its parts) to the target infrastructure. She needs to take into consideration cost, resource, and communication constraints to select the most suitable set of VMs, from private and public Cloud providers. However, defining a mapping manually may be a challenge in large-scale or time constrained scenarios since the number of possible configuration explodes. Furthermore, when automating this process, scalability issues must be taken into account given that this mapping problem is a generalization of the graph homomorphism problem, which is NP-complete.In this thesis we address the problem of calculating initial and reconfiguration placements for distributed applications over possibly multiple Clouds. Our objective is to minimize renting and migration costs while satisfying applications' resource and communication constraints. We concentrate on the mapping between applications and Cloud infrastructure. Using an incremental approach, we split the problem into three different parts and propose efficient heuristics that can compute good quality placements very quickly for small and large scenarios. These heuristics are based on graph partition and vector packing heuristics and have been extensively evaluated against state of the art approaches such as MIP solvers and meta-heuristics. We show through simulations that the proposed heuristics manage to compute solutions in a few seconds that would take many hours or days for other approaches to compute
Capítulos de libros sobre el tema "Greedy heuristic algorithms"
Ma, Fuhua, Qianqian Ren y Jun Li. "A Greedy Heuristic Based Beacons Selection for Localization". En Algorithms and Architectures for Parallel Processing, 710–18. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60245-1_48.
Texto completoDietzfelbinger, Martin, Hendrik Peilke y Michael Rink. "A More Reliable Greedy Heuristic for Maximum Matchings in Sparse Random Graphs". En Experimental Algorithms, 148–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30850-5_14.
Texto completoTaillard, Éric D. "Constructive Methods". En Design of Heuristic Algorithms for Hard Optimization, 85–101. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13714-3_4.
Texto completoYang, Weiming. "Non-Greedy Heuristic Web Spiders Search Algorithm". En Lecture Notes in Electrical Engineering, 1728–33. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2386-6_236.
Texto completoPranzo, Marco, Carlo Meloni y Dario Pacciarelli. "A New Class of Greedy Heuristics for Job Shop Scheduling Problems". En Experimental and Efficient Algorithms, 223–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44867-5_19.
Texto completoXu, Thomas Canhao, Pasi Liljeberg y Hannu Tenhunen. "A Greedy Heuristic Approximation Scheduling Algorithm for 3D Multicore Processors". En Euro-Par 2011: Parallel Processing Workshops, 281–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29737-3_32.
Texto completoBarus, A. C., T. Y. Chen, D. Grant, F. C. Kuo y M. F. Lau. "Testing of Heuristic Methods: A Case Study of Greedy Algorithm". En Software Engineering Techniques, 246–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22386-0_19.
Texto completoGutin, Gregory, Boris Goldengorin y Jing Huang. "Worst Case Analysis of Max-Regret, Greedy and Other Heuristics for Multidimensional Assignment and Traveling Salesman Problems". En Approximation and Online Algorithms, 214–25. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/11970125_17.
Texto completoBrahmachary, Shuvayan, Ganesh Natarajan, Vinayak Kulkarni, Niranjan Sahoo y Soumya Ranjan Nanda. "Application of Greedy and Heuristic Algorithm-Based Optimisation Methods Towards Aerodynamic Shape Optimisation". En Advances in Intelligent Systems and Computing, 937–48. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1592-3_75.
Texto completoPotvin, Jean-Yves y François Guertin. "Coupling a Greedy Route Construction Heuristic with a Genetic Algorithm for the Vehicle Routing Problem with Time Windows". En Operations Research/Computer Science Interfaces Series, 423–42. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-4102-8_19.
Texto completoActas de conferencias sobre el tema "Greedy heuristic algorithms"
Guo, Changjie, Zhe Xiang, Zhun Zhong y Yuzhuo Zhong. "Greedy heuristic placement algorithms in distributed cooperative proxy system". En Electronic Imaging 2002, editado por C. C. Jay Kuo. SPIE, 2002. http://dx.doi.org/10.1117/12.453064.
Texto completoWan, Guihong y Haim Schweitzer. "Heuristic Search for Approximating One Matrix in Terms of Another Matrix". En Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/221.
Texto completoWang, Ziyuan, Baowen Xu y Changhai Nie. "Greedy Heuristic Algorithms to Generate Variable Strength Combinatorial Test Suite". En Eighth International Conference on Quality Software. QSIC 2008. IEEE, 2008. http://dx.doi.org/10.1109/qsic.2008.52.
Texto completoCohen, Eldan, Richard Valenzano y Sheila McIlraith. "Type-WA*: Using Exploration in Bounded Suboptimal Planning". En Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/557.
Texto completoRuichun Tang, Shuangle Guo, Hongying Ji y Cunqun Gong. "A Heuristic Optimization algorithm for Geographic Greedy Hole-Bypassing routing algorithms in WMSNs". En Multimedia Technology (IC-BNMT 2010). IEEE, 2010. http://dx.doi.org/10.1109/icbnmt.2010.5705148.
Texto completoJoneja, Ajay, Zhu Shaoming y Yuan-Shin Lee. "Greedy Tool Heuristic for Rough Milling of Complex Pockets". En ASME 2001 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/detc2001/dfm-21179.
Texto completoYang, Puyi y Hamidreza Najafi. "Wind Farm Layout Optimization: A Multi-Stage Approach". En ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-71892.
Texto completoThanh, Pham Dinh, Huynh Thi Thanh Binh, Do Dinh Dac, Nguyen Binh Long y Le Minh Hai Phong. "A Heuristic Based on Randomized Greedy Algorithms for the Clustered Shortest-Path Tree Problem". En 2019 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2019. http://dx.doi.org/10.1109/cec.2019.8790070.
Texto completoHeusner, Manuel, Thomas Keller y Malte Helmert. "Search Progress and Potentially Expanded States in Greedy Best-First Search". En Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/735.
Texto completoMandros, Panagiotis, Mario Boley y Jilles Vreeken. "Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms". En 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.2019/864.
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