Gotowe bibliografie tematyczne / Local search

Gotowa bibliografia na temat „Local search”

Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 22 czerwca 2024

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Artykuły w czasopismach na temat "Local search"

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HASEGAWA, Manabu. "Potentially Local Search in Local Search Heuristics". Proceedings of The Computational Mechanics Conference 2004.17 (2004): 403–4. http://dx.doi.org/10.1299/jsmecmd.2004.17.403.

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Ishtaiwi, Abdelraouf, Ghassan Issa, Wael Hadi i Nawaf Ali. "Weight Resets in Local Search for SAT". International Journal of Machine Learning and Computing 9, nr 6 (grudzień 2019): 874–79. http://dx.doi.org/10.18178/ijmlc.2019.9.6.886.

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Verhoeven, M. G. A., i E. H. L. Aarts. "Parallel local search". Journal of Heuristics 1, nr 1 (wrzesień 1995): 43–65. http://dx.doi.org/10.1007/bf02430365.

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Lancia, Giuseppe, Franca Rinaldi i Paolo Serafini. "Local search inequalities". Discrete Optimization 16 (maj 2015): 76–89. http://dx.doi.org/10.1016/j.disopt.2015.02.003.

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Choi, Changkyu, i Ju-Jang Lee. "Chaotic local search algorithm". Artificial Life and Robotics 2, nr 1 (marzec 1998): 41–47. http://dx.doi.org/10.1007/bf02471151.

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Vaessens, R. J. M., E. H. L. Aarts i J. K. Lenstra. "A local search template". Computers & Operations Research 25, nr 11 (listopad 1998): 969–79. http://dx.doi.org/10.1016/s0305-0548(97)00093-2.

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Oliveira, Leonardo D., Fernando Ciriaco, Taufik Abrão i Paul Jean E. Jeszensky. "Local search multiuser detection". AEU - International Journal of Electronics and Communications 63, nr 4 (kwiecień 2009): 259–70. http://dx.doi.org/10.1016/j.aeue.2008.01.009.

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Whitley, Darrell, i Jonathan Rowe. "Subthreshold-seeking local search". Theoretical Computer Science 361, nr 1 (sierpień 2006): 2–17. http://dx.doi.org/10.1016/j.tcs.2006.04.008.

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Dubois-Lacoste, Jérémie, Manuel López-Ibáñez i Thomas Stützle. "Anytime Pareto local search". European Journal of Operational Research 243, nr 2 (czerwiec 2015): 369–85. http://dx.doi.org/10.1016/j.ejor.2014.10.062.

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Anderson, E. J. "Mechanisms for local search". European Journal of Operational Research 88, nr 1 (styczeń 1996): 139–51. http://dx.doi.org/10.1016/0377-2217(94)00164-2.

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Rozprawy doktorskie na temat "Local search"

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Brueggemann, Tobias. "Efficiency of local search". Enschede : University of Twente [Host], 2006. http://doc.utwente.nl/57144.

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Tairan, Nasser. "Cooperative guided local search". Thesis, University of Essex, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.573069.

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Over the past few decades, meta-heuristic algorithms (MHs) have proven to be powerful tools for dealing with difficult combinational optimization problems (COPs). These techniques can obtain high quality solutions within reasonable computational time for many hard ,.' A' problems. Among these methods, guided local search (GLS) is p'femising one. The proximate optimality principle (POP), an underlying assumption in most meta-heuristics, assumes that good solutions have similar structures. Structures which are common to good solutions are more likely to be part of the best solution. In this thesis we discuss how the performance of the GLS can be further enhanced through designing a cooperative mechanism based on the proximate optimality principle (POP). The approach that we took was to search for solutions using multiple agents, each of which running a copy of GLS. These agents benefit from each other through the exchange of information based on POP. We suggest based on POP that common features that appear in many locally optimal solutions of GLS agents are more likely to be parts of the globally optimal solution. Thus, this property should be taken into consideration during the search. We call this framework Population-based GLS (P-GLS). P-GLS shows its efficiency and effectiveness to converge quickly to promising regions of the search space in an intelligent manner. Four P-GLS versions are proposed which enhance the performance of P-GLS. These algorithms are extensively studied and tested on Traveling salesman problem (TSP), Multidimensional Knapsack Problem (MKP) and Field Workforce Scheduling Problem (FWSP). Computational results confirm the effectiveness of P-GLS compared to original GLS and other well known MHs.
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So, D. G. "Local search and simulation". Thesis, Swansea University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.639084.

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Simulation has long been recognised as a powerful technique for analysing complex systems which are mathematically intractable. The objectives of simulation experiments are essentially of two types, namely for investigative and optimisation purposes. As far as the latter is concerned, analysts essentially aim to find the combination of input parameters to the system being investigated so as to optimise some performance measures. The discovery of a 'good' combination of input parameters frequently involves a long and tedious trial and error process which is often computationally demanding. This thesis concerns the automation of the process. In particular, various search algorithms are developed within the framework of local search. These algorithms are used to automatically search for 'promising', or even optimal, parameter settings where the function to be optimised is the output of a simulation model. An important distinction between the work described in this thesis and the more conventional use of local search lies in the nature of the cost function. While the conventional application of local search mainly focuses on problems with a deterministic cost function, this work considers problems in which the cost function is subject to some stochastic infrastructure. To ensure a successful implementation of local search to such problems, it is crucial that the stochastic variation in the cost function is explicitly taken into account. Various strategies to achieve this end are identified and ways in which they can be incorporated into the standard acceptance criteria of local search algorithms are described.
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Ågren, Magnus. "Set Constraints for Local Search". Doctoral thesis, Uppsala universitet, Avdelningen för datalogi, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-8373.

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Combinatorial problems are ubiquitous in our society and solving such problems efficiently is often crucial. One technique for solving combinatorial problems is constraint-based local search. Its compositional nature together with its efficiency on large problem instances have made this technique particularly attractive. In this thesis we contribute to simplifying the solving of combinatorial problems using constraint-based local search. To provide higher-level modelling options, we introduce set variables and set constraints in local search by extending relevant local search concepts. We also propose a general scheme to follow in order to define what we call natural and balanced constraint measures, and accordingly define such measures for over a dozen set constraints. However, defining such measures for a new constraint is time-consuming and error-prone. To relieve the user from this, we provide generic measures for any set constraint modelled in monadic existential second-order logic. We also theoretically relate these measures to our proposed general scheme, and discuss implementation issues such as incremental algorithms and their worst-case complexities. To enable higher-level search algorithms, we introduce constraint-directed neighbourhoods in local search by proposing new constraint primitives for representing such neighbourhoods. Based on a constraint, possibly modelled in monadic existential second-order logic, these primitives return neighbourhoods with moves that are known in advance to achieve a decrease (or preservation, or increase) of the constraint measures, without the need to iterate over any other moves. We also present a framework for constraint-based local search where one can model and solve combinatorial problems with set variables and set constraints, use any set constraint modelled in monadic existential second-order logic, as well as use constraint-directed neighbourhoods. Experimental results on three real-life problems show the usefulness in practice of our theoretical results: our running times are comparable to the current state-of-the-art approaches to solving the considered problems.
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Southey, Finnegan. "Augmenting Local Search for Satisfiability". Thesis, University of Waterloo, 2004. http://hdl.handle.net/10012/1075.

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This dissertation explores approaches to the satisfiability problem, focusing on local search methods. The research endeavours to better understand how and why some local search methods are effective. At the root of this understanding are a set of metrics that characterize the behaviour of local search methods. Based on this understanding, two new local search methods are proposed and tested, the first, SDF, demonstrating the value of the insights drawn from the metrics, and the second, ESG, achieving state-of-the-art performance and generalizing the approach to arbitrary 0-1 integer linear programming problems. This generality is demonstrated by applying ESG to combinatorial auction winner determination. Further augmentations to local search are proposed and examined, exploring hybrids that incorporate aspects of backtrack search methods.
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Ågren, Magnus. "Set constraints for local search /". Uppsala : Acta Universitatis Upsaliensis, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-8373.

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Mills, P. H. "Extensions to Guided Local Search". Thesis, University of Essex, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.391658.

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Magnusson, Jesper. "Guiding Local Search using Approximations". Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-372074.

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Proving that a program is correct can be done by translating it into a first-order formula and trying to prove that it is valid. Programs often contain data structures such as Floating-point numbers, for which current solvers struggle because of the computational complexity of these theories. By using approximations, the precision of the floating-point numbers can be reduced to lower the complexity making it easier for the solvers. If a solution to the approximate formula can be found, it is often close to a solution of the original formula. A reconstruction of this solution can be made by modifying it in different ways as an attempt to reconstruct it into a solution of the original formula. In this thesis a local-search algorithm is implemented as a reconstruction. By continuously keeping a candidate solution, starting with the approximate one it is possible to iteratively make small modifications to search for nearby candidates and eventually find a solution to the original formula. Three different configurations are implemented, evaluated against each other and also against existing reconstructions. Tests shows that a local-search reconstruction can be viable and opens up for further testing of different configurations.
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Martinsson, Roy. "Software Vulnerability Assessment : local search methods". Thesis, Blekinge Tekniska Högskola, Avdelningen för programvarusystem, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-4270.

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In this thesis, we analyse different ways of detecting application vulnerabilities on installed software. Based on this research, a prototype will be developed that will validate these findings. The prototype will analyse only known vulnerabilities collected from a database and matched with locally collected data.
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Ågren, Magnus. "High-level modelling and local search". Licentiate thesis, Uppsala universitet, Avdelningen för datalogi, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-86352.

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Combinatorial optimisation problems are ubiquitous in our society and appear in such varied guises as DNA sequencing, scheduling, configuration, airline-crew and nurse rostering, combinatorial auctions, vehicle routing, and financial portfolio design. Their efficient solution is crucial to many people and has been the target for much research during the last decades. One successful area of research for solving such problems is constraint programming. Yet, current-generation constraint programming languages are considered by many, especially in industry, to be too low-level, difficult, and large. In this thesis, we argue that solver-independent, high-level relational constraint modelling leads to a simpler and smaller language, to more concise, intuitive, and analysable models, as well as to more efficient and effective model formulation, maintenance, reformulation, and verification. All this can be achieved without sacrificing the possibility of efficient solving, so that even time-pressed modellers can be well assisted. Towards this, we propose the ESRA relational constraint modelling language, showcase its elegance on some real-life problems, and outline a compilation philosophy for such languages. In order to compile high-level languages such as ESRA to current generation constraint programming languages, it is essential that as much support as possible is available in these languages. This is already the case in the constructive search area of constraint programming where, e.g., different kinds of domain variables, such as integer variables and set variables, and expressive global constraints are readily available. However, in the local search area of constraint programming, this is not yet the case and, until now, set variables were for example not available. This thesis introduces set variables and set constraints in the local search area of constraint programming and, by doing this, considerably improves the possibilities for using local search. This is true both for modelling and solving problems using constraint-based local search, as well as for using it as a possible target for the compilation of ESRA models. Indeed, many combinatorial optimisation problems have natural models based on set variables and set constraints, three of which are successfully solved in this thesis. When a new set constraint is introduced in local search, much effort must be spent on the design and implementation of an appropriate incremental penalty function for the constraint. This thesis introduces a scheme that, from a high-level description of a set constraint in existential second-order logic with counting, automatically synthesises an incremental penalty function for that constraint. The performance of this scheme is demonstrated by solving real-life instances of a financial portfolio design problem that seem unsolvable in reasonable time by constructive search.
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Książki na temat "Local search"

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Laurent, Michel, red. Constraint-based local search. Cambridge, Ma: MIT Press, 2005.

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Walser, Joachim Paul, red. Integer Optimization by Local Search. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48369-1.

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L, Aarts E. H., i Lenstra J. K, red. Local search in combinatorial optimization. Princeton: Princeton University Press, 2003.

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L, Aarts E. H., i Lenstra J. K, red. Local search in combinatorial optimization. Chichester [England]: Wiley, 1997.

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Nareyek, Alexander, red. Local Search for Planning and Scheduling. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45612-0.

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Thomas, Stützle, red. Stochastic local search: Foundations and applications. San Francisco, CA: Morgan Kaufmann Publishers, 2005.

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Braziunas, Darius. Stochastic local search for POMDP controllers. Ottawa: National Library of Canada, 2003.

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Institute of Social Sciences (New Delhi, India), red. Local governance: Search for new path. New Delhi: Published for Institute of Social Sciences by Concept Pub. Co., 2011.

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Young, Ken. In search of community identity. York: Joseph Rowntree Foundation, 1996.

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Vaessens, Robert Johannes Maria. Generalized job scheduling: Complexity and local search. Eindhoven: Eindhoven University of Technology, 1995.

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Części książek na temat "Local search"

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de Oca, Marco A. Montes, Carlos Cotta i Ferrante Neri. "Local Search". W Handbook of Memetic Algorithms, 29–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-23247-3_3.

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Bánhelyi, Balázs, Tibor Csendes, Balázs Lévai, László Pál i Dániel Zombori. "Local Search". W SpringerBriefs in Optimization, 7–25. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02375-1_2.

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Cortez, Paulo. "Local Search". W Use R!, 45–61. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08263-9_4.

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Taillard, Éric D. "Local Search". W Design of Heuristic Algorithms for Hard Optimization, 103–29. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13714-3_5.

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AbstractImprovement methods constitute the backbone of most metaheuristics. These methods repeatedly perform slight, local modifications on a current solution to the problem. Hence, for any solution, a set of neighbor solutions must be defined. Clearly, the definition of this set depends on the problem modeling. However, a natural neighborhood may turn out to be either too small to lead to quality solutions or too large, inducing prohibitive calculation times. Various approaches have been proposed to enlarge the neighborhood, such as the filter and fan method or the ejection chains. For reducing the neighborhood size, typical strategies are the granular search and the candidate list.
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Katila, Riitta, i Sruthi Thatchenkery. "Local Search". W The Palgrave Encyclopedia of Strategic Management, 910–12. London: Palgrave Macmillan UK, 2018. http://dx.doi.org/10.1057/978-1-137-00772-8_320.

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Katila, Riitta, i Sruthi Thatchenkery. "Local Search". W The Palgrave Encyclopedia of Strategic Management, 1–3. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/978-1-349-94848-2_320-1.

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Cortez, Paulo. "Local Search". W Use R!, 59–87. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72819-9_4.

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Resende, Mauricio G. C., i Celso C. Ribeiro. "Local search". W Optimization by GRASP, 63–93. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-6530-4_4.

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Kramer, Oliver. "Iterated Local Search". W A Brief Introduction to Continuous Evolutionary Optimization, 45–54. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-03422-5_5.

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Voudouris, Christos, Edward P. K. Tsang i Abdullah Alsheddy. "Guided Local Search". W Handbook of Metaheuristics, 321–61. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-1665-5_11.

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Streszczenia konferencji na temat "Local search"

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Daskalakis, Constantinos, i Christos Papadimitriou. "Continuous Local Search". W Proceedings of the Twenty-Second Annual ACM-SIAM Symposium on Discrete Algorithms. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2011. http://dx.doi.org/10.1137/1.9781611973082.62.

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Amin, S. "Dynamic local search". W Second International Conference on Genetic Algorithms in Engineering Systems. IEE, 1997. http://dx.doi.org/10.1049/cp:19971168.

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Datha, Naren, Tanuja Joshi, Joseph Joy i Vibhuti Sengar. "Custom local search". W the 17th ACM SIGSPATIAL International Conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1653771.1653835.

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Jia, Rui-min, i Deng-xu He. "Complex valued cuckoo search with local search". W 2013 9th International Conference on Natural Computation (ICNC). IEEE, 2013. http://dx.doi.org/10.1109/icnc.2013.6818276.

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Audemard, Gilles, Jean-Marie Lagniez, Bertrand Mazure i Lakhdar Saïs. "Learning in Local Search". W 2009 21st IEEE International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2009. http://dx.doi.org/10.1109/ictai.2009.71.

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Ozaki, Yoshihiko, Shintaro Takenaga i Masaki Onishi. "Global Search versus Local Search in Hyperparameter Optimization". W 2022 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2022. http://dx.doi.org/10.1109/cec55065.2022.9870287.

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Magaji, Amina Sambo, Ines Arana i Hatem Ahriz. "Local Search for DisCSPs with Complex Local Problems". W 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT). IEEE, 2014. http://dx.doi.org/10.1109/wi-iat.2014.150.

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Huitema, Pedro, i Perry Fizzano. "A Crawler for Local Search". W 2010 Fourth International Conference on the Digital Society (ICDS). IEEE, 2010. http://dx.doi.org/10.1109/icds.2010.23.

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Bian, Jiang, i Yi Chang. "A taxonomy of local search". W the 20th ACM international conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2063576.2063983.

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Johnson, David S., Christos H. Papadimitriou i Mihalis Yannakakis. "How easy is local search?" W 26th Annual Symposium on Foundations of Computer Science (sfcs 1985). IEEE, 1985. http://dx.doi.org/10.1109/sfcs.1985.31.

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Raporty organizacyjne na temat "Local search"

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Keefe, K. Local search strategies for equational satisfiability. Office of Scientific and Technical Information (OSTI), wrzesień 2004. http://dx.doi.org/10.2172/834713.

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Gonzales, Antonio, i Nicholas Paul Blazier. Enhanced Approximate Nearest Neighbor via Local Area Focused Search. Office of Scientific and Technical Information (OSTI), luty 2017. http://dx.doi.org/10.2172/1367491.

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Beveridge, J. R., Christopher Graves i Christopher E. Lesher. Local Search as a Tool for Horizon Line Matching. Fort Belvoir, VA: Defense Technical Information Center, grudzień 1995. http://dx.doi.org/10.21236/ada308540.

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Jacobson, Sheldon H. Finite-Time Performance of Local Search Algorithms: Theory and Application. Fort Belvoir, VA: Defense Technical Information Center, czerwiec 2010. http://dx.doi.org/10.21236/ada522073.

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Mager, Astrid, red. Glocal Search. Search technology at the intersection of global capitalism and local socio-political cultures - FINAL REPORT. Vienna: self, 2016. http://dx.doi.org/10.1553/ita-pb-a64.

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Todd, Petra, i Weilong Zhang. Distributional Effects of Local Minimum Wages: A Spatial Job Search Approach. Cambridge, MA: National Bureau of Economic Research, listopad 2022. http://dx.doi.org/10.3386/w30668.

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William Rodi, Craig A. Schultz, Gardar Johannesson i Stephen C. Myers. Grid-Search Location Methods for Ground-Truth Collection From Local and Regional Seismic Networks. Office of Scientific and Technical Information (OSTI), maj 2005. http://dx.doi.org/10.2172/840064.

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öhman, Björn, i Jens Frank. Probability of police dogs detecting missing people in search sectors. Department of Ecology, Swedish University of Agricultural Sciences, 2023. http://dx.doi.org/10.54612/a.3tvad4e09k.

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Searching for missing persons is an important task for police dog teams. The purpose of this study was to investigate what proportion of missing persons are found during sector searches. The study was conducted as an exercise within the framework of the local weekly training structure (L406) for police patrol dogs in Police Region South during the winter and spring of 2022/2023. A total of 23 dog teams participated over six weeks from December 2022 to April 2023. During the searches, 25 out of 26 (96%) of the deployed decoys were found, which means that a missing person is very likely to be found by the police dog teams also during real search and rescue missions. Interestingly, the dog teams that have used a total search-time below average have found decoys to the same extent as the teams that have used more total search-time. The group that has used less than 119 minutes and where the dog has travelled an average of 9.5 km has thus been sufficient to find the missing persons. This means that the teams that have searched longer than the average and where the dog has travelled a longer distance, have used more time than actually needed. A total search-time of 119 minutes on average and a distance travelled by the dog of 9.5 km was sufficient to find all the decoys in an area of 25 hectares. A shorter search-time and shorter distance travelled would likely have been sufficient to find the same number of decoys, but based on the results of this study we cannot determine what time or distance would have been sufficient. This is however interesting to investigate further in future studies as it suggests that there is a possibility to cover larger areas in less time but with the same probability of detecting missing persons.
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Mager, Astrid, red. Internet governance as joint effort - (Re)Ordering search engines at the intersection of global and local cultures. Vienna: self, 2018. http://dx.doi.org/10.1553/ita-pa-am-2018.

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Denys. L52230 SCC In Areas of Local Deformation. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), marzec 2005. http://dx.doi.org/10.55274/r0010927.

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In Task 1, a questionnaire was sent to the PRCI member companies to query them on their experience with SCC at areas of local deformation. Follow-up telephone contacts were made with those companies that have had significant experience with this problem or did not respond to the survey. In addition, CC Technologies has performed a number of failure investigations over the past several years in which local deformation played a role in SCC. Some of these failures have been with non-PRCI member companies. CC Technologies contacted these companies to obtain permission to release the information for use in the survey. Relevant data was included in this report on a confidential basis. In Task 2, the open literature was surveyed for information for different SCC types, characteristics of stresses at pipeline dents, and modeling of SCC and mechanical damage. The literature search included on-line computer databases, symposium and conference proceedings and CC Technologies' in-house library. Relevant papers were reviewed to assess the extent of and identify the probable contributing factors to the problem of SCC at local areas of deformation. In Task 3, some limited FEA modeling was performed to evaluate the stress fields associated with the typical instances of areas of local deformation on pipelines. This approach was used to evaluate the primary and secondary stresses associated with typical dent geometries.
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