Relevant bibliographies by topics / Euclidean combinatorial optimization

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Euclidean combinatorial optimization'

Author: Grafiati
Published: 28 May 2022
Last updated: 31 July 2025

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Journal articles on the topic "Euclidean combinatorial optimization"

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Steele, J. Michael. "Probability and Problems in Euclidean Combinatorial Optimization." Statistical Science 8, no. 1 (1993): 48–56. http://dx.doi.org/10.1214/ss/1177011083.

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Michael Steele, J. "Efficacy of spacefilling heuristics in Euclidean combinatorial optimization." Operations Research Letters 8, no. 5 (1989): 237–39. http://dx.doi.org/10.1016/0167-6377(89)90046-1.

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Moraglio, Alberto, Cecilia Di Chio, Julian Togelius, and Riccardo Poli. "Geometric Particle Swarm Optimization." Journal of Artificial Evolution and Applications 2008 (February 21, 2008): 1–14. http://dx.doi.org/10.1155/2008/143624.

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Using a geometric framework for the interpretation of crossover of recent introduction, we show an intimate connection between particle swarm optimisation (PSO) and evolutionary algorithms. This connection enables us to generalise PSO to virtually any solution representation in a natural and straightforward way. The new Geometric PSO (GPSO) applies naturally to both continuous and combinatorial spaces. We demonstrate this for the cases of Euclidean, Manhattan and Hamming spaces and report extensive experimental results. We also demonstrate the applicability of GPSO to more challenging combinat
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Barbolina, Tetiana. "Estimates of objective function minimum for solving linear fractional unconstrained combinatorial optimization problems on arrangements." Physico-mathematical modelling and informational technologies, no. 32 (July 6, 2021): 32–36. http://dx.doi.org/10.15407/fmmit2021.32.055.

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The paper is devoted to the study of one class of Euclidean combinatorial optimization problems — combinatorial optimization problems on the general set of arrangements with linear fractional objective function and without additional (non-combinatorial) constraints. The paper substantiates the improvement of the polynomial algorithm for solving the specified class of problems. This algorithm foresees solving a finite sequence of linear unconstrained problems of combinatorial optimization on arrangements. The modification of the algorithm is based on the use of estimates of the objective functi
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Jaillet, Patrick. "Analysis of Probabilistic Combinatorial Optimization Problems in Euclidean Spaces." Mathematics of Operations Research 18, no. 1 (1993): 51–70. http://dx.doi.org/10.1287/moor.18.1.51.

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Barbolina, T. M. "Properties of Euclidean Problems of Lexicographic Combinatorial Optimization on Arrangements." Mathematical and computer modelling. Series: Physical and mathematical sciences, no. 19 (June 25, 2019): 5–11. http://dx.doi.org/10.32626/2308-5878.2019-19.5-11.

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Wang, Hongjian, Abdelkhalek Mansouri, and Jean-Charles Créput. "Cellular matrix model for parallel combinatorial optimization algorithms in Euclidean plane." Applied Soft Computing 61 (December 2017): 642–60. http://dx.doi.org/10.1016/j.asoc.2017.08.015.

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U., Tormosov, Stoyan E., and Yakushenko E. "THE PROBLEM OF MINIMIZING THE SUMMARY AREA OF MOBILE INTERRUPTIONS AT A LINEAR PLACEMENT OF GEOMETRIC OBJECTS." PROGRESSIVE TECHNIQUE AND TECHNOLOGIES OF FOOD PRODUCTION ENTERPRISES, CATERING BUSINESS AND TRADE 1(29) (June 30, 2019): 239–47. https://doi.org/10.5281/zenodo.3263757.

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<em>The high computational complexity of the combinatorial optimization methods, the difference of the combinatorial properties of the sets which form the ranges of admissible solutions, are the reasons for the lack of unified approach to combinatorial optimization problems solving. The basic idea of the combinatorial methods consists in the transition from complete enumeration of finite set of solutions to reduced one. The impossibility of exact solution of combinatorial optimization problems of large dimension and specific limitations cause the development of approximate methods, but these m
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Michalak, Krzysztof. "Low-Dimensional Euclidean Embedding for Visualization of Search Spaces in Combinatorial Optimization." IEEE Transactions on Evolutionary Computation 23, no. 2 (2019): 232–46. http://dx.doi.org/10.1109/tevc.2018.2846636.

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Nallaperuma, Samadhi, Frank Neumann, and Dirk Sudholt. "Expected Fitness Gains of Randomized Search Heuristics for the Traveling Salesperson Problem." Evolutionary Computation 25, no. 4 (2017): 673–705. http://dx.doi.org/10.1162/evco_a_00199.

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Randomized search heuristics are frequently applied to NP-hard combinatorial optimization problems. The runtime analysis of randomized search heuristics has contributed tremendously to our theoretical understanding. Recently, randomized search heuristics have been examined regarding their achievable progress within a fixed-time budget. We follow this approach and present a fixed-budget analysis for an NP-hard combinatorial optimization problem. We consider the well-known Traveling Salesperson Problem (TSP) and analyze the fitness increase that randomized search heuristics are able to achieve w
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Dissertations / Theses on the topic "Euclidean combinatorial optimization"

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DI, GIOACCHINO ANDREA. "EUCLIDEAN CORRELATIONS IN COMBINATORIAL OPTIMIZATION PROBLEMS: A STATISTICAL PHYSICS APPROACH." Doctoral thesis, Università degli Studi di Milano, 2019. http://hdl.handle.net/2434/693073.

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In this thesis I discuss combinatorial optimization problems, from the statistical physics perspective. The starting point are the motivations which brought physicists together with computer scientists and mathematicians to work on this beautiful and deep topic. I give some elements of complexity theory, and I motivate why the point of view of statistical physics, although different from the one adopted in standard complexity theory, leads to many interesting results, as well as new questions. I discuss the connection between combinatorial optimization problems and spin glasses. Finally, I bri
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Jaillet, Patrick. "Cube versus Torus Models for Combinatorial Optimization Problems and the Euclidean Minimum Spanning Tree Constant." Massachusetts Institute of Technology, Operations Research Center, 1990. http://hdl.handle.net/1721.1/5196.

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For a sample of points drawn uniformly from either the d-dimensional torus or the d-cube, d > 2, we define a class of random processes with the property of being asymptotically equivalent in expectation in the two models. Examples include the traveling salesman problem (TSP), the minimum spanning tree problem (MST), etc. Application of this result helps closing down one open question: We prove that the analytical expression recently obtained by Avram and Bertsimas for the MST constant in the d-torus model is in fact valid for the traditional d-cube model. For the MST, we also extend our result
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Nilsson, Mikael. "On the Complexity of Finding Spanner Paths." Linköpings universitet, Artificiell intelligens och integrerad datorsystem, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-93332.

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We study the complexity of finding so called spanner paths between arbitrary nodes in Euclidean graphs. We study both general Euclidean graphs and a special type of graphs called Integer Graphs. The problem is proven NP-complete for general Euclidean graphs with non-constant stretches (e.g. (2n)^(3/2) where n denotes the number of nodes in the graph). An algorithm solving the problem in O(2^(0.822n)) is presented. Integer graphs are simpler and for these special cases a better algorithm is presented. By using a partial order of so called Images the algorithm solves the spanner path problem usi
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ZHANG, Naiyu. "Cellular GPU Models to Euclidean Optimization Problems : Applications from Stereo Matching to Structured Adaptive Meshing and Traveling Salesman Problem." Phd thesis, Université de Technologie de Belfort-Montbeliard, 2013. http://tel.archives-ouvertes.fr/tel-00982405.

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The work presented in this PhD studies and proposes cellular computation parallel models able to address different types of NP-hard optimization problems defined in the Euclidean space, and their implementation on the Graphics Processing Unit (GPU) platform. The goal is to allow both dealing with large size problems and provide substantial acceleration factors by massive parallelism. The field of applications concerns vehicle embedded systems for stereovision as well as transportation problems in the plane, as vehicle routing problems. The main characteristic of the cellular model is that it d
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Zhang, Naiyu. "Cellular GPU Models to Euclidean Optimization Problems : Applications from Stereo Matching to Structured Adaptive Meshing and Traveling Salesman Problem." Thesis, Belfort-Montbéliard, 2013. http://www.theses.fr/2013BELF0215/document.

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Le travail présenté dans ce mémoire étudie et propose des modèles de calcul parallèles de type cellulaire pour traiter différents problèmes d’optimisation NP-durs définis dans l’espace euclidien, et leur implantation sur des processeurs graphiques multi-fonction (Graphics Processing Unit; GPU). Le but est de pouvoir traiter des problèmes de grande taille tout en permettant des facteurs d’accélération substantiels à l’aide du parallélisme massif. Les champs d’application visés concernent les systèmes embarqués pour la stéréovision de même que les problèmes de transports définis dans le plan, te
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Iemets, O. O., O. O. Yemets`, and I. M. Polyakov. "About the Simplex Form of the Polyhedron of Arrangements." Thesis, Sumy State University, 2017. http://essuir.sumdu.edu.ua/handle/123456789/55771.

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The simplex form of the general polyhedron of arrangements, which is used in linear programming problems in combinatorial cutting methods is obtained and it increases the efficiency of cutting methods.
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Krislock, Nathan. "Semidefinite Facial Reduction for Low-Rank Euclidean Distance Matrix Completion." Thesis, 2010. http://hdl.handle.net/10012/5093.

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The main result of this thesis is the development of a theory of semidefinite facial reduction for the Euclidean distance matrix completion problem. Our key result shows a close connection between cliques in the graph of the partial Euclidean distance matrix and faces of the semidefinite cone containing the feasible set of the semidefinite relaxation. We show how using semidefinite facial reduction allows us to dramatically reduce the number of variables and constraints required to represent the semidefinite feasible set. We have used this theory to develop a highly efficient algorithm capa
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Books on the topic "Euclidean combinatorial optimization"

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Yukich, Joseph. Probability theory of classical Euclidean optimization problems. Springer, 1998.

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Book chapters on the topic "Euclidean combinatorial optimization"

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Winter, Pawel. "Euclidean Steiner Minimal Trees with Obstacles and Steiner Visibility Graphs." In Combinatorial Optimization. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-77489-8_34.

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Yang, Boting. "Euclidean Chains and Their Shortcuts." In Combinatorial Optimization and Applications. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22616-8_12.

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Hwang, Frank K. "A Proposed Experiment on Soap Film Solutions of Planar Euclidean Steiner Trees." In Combinatorial Optimization. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4613-0255-1_8.

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Dumitrescu, Adrian, Anirban Ghosh, and Csaba D. Tóth. "Online Unit Covering in Euclidean Space." In Combinatorial Optimization and Applications. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04651-4_41.

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Nagarajan, Viswanath, Baruch Schieber, and Hadas Shachnai. "The Euclidean k-Supplier Problem." In Integer Programming and Combinatorial Optimization. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36694-9_25.

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Song, Liang, Hejiao Huang, and Hongwei Du. "A Quasi-polynomial Time Approximation Scheme for Euclidean CVRPTW." In Combinatorial Optimization and Applications. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12691-3_6.

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Song, Liang, and Hejiao Huang. "The Euclidean Vehicle Routing Problem with Multiple Depots and Time Windows." In Combinatorial Optimization and Applications. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-71147-8_31.

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Khachay, Michael, and Helen Zaytseva. "Polynomial Time Approximation Scheme for Single-Depot Euclidean Capacitated Vehicle Routing Problem." In Combinatorial Optimization and Applications. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26626-8_14.

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Vu, Ky, Pierre-Louis Poirion, Claudia D’Ambrosio, and Leo Liberti. "Random Projections for Quadratic Programs over a Euclidean Ball." In Integer Programming and Combinatorial Optimization. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17953-3_33.

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Binder, Ilia, and Mark Braverman. "Derandomization of Euclidean Random Walks." In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74208-1_26.

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Conference papers on the topic "Euclidean combinatorial optimization"

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Michalak, Krzysztof. "Low-Dimensional euclidean embedding for visualization of search spaces in combinatorial optimization." In GECCO '19: Genetic and Evolutionary Computation Conference. ACM, 2019. http://dx.doi.org/10.1145/3319619.3326761.

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Yokoyama, Soichiro, Ikuo Suzuki, Masahito Yamamoto, and Masashi Furukawa. "A New Heuristic for Traveling Salesman Problem Based on LCO." In ASME/ISCIE 2012 International Symposium on Flexible Automation. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/isfa2012-7227.

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The Traveling Salesman Problem (TSP) is one of the most well known combinatorial optimization problem and has wide range of application. Since the TSP is NP-hard, many heuristics for the TSP have been developed. This study proposes a new heuristic for the TSP based on one of these heuristics named Local Clustering Optimization (LCO). LCO is a metaheuristic proposed by Furukawa at el. to give an accurate solution for large scale problems in a reasonable time. However, conventional LCO-based heuristics for the TSP is not suited to solving asymmetric instances. The proposed method iteratively ado
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