Relevant bibliographies by topics / Simulated annealing

Academic literature on the topic 'Simulated annealing'

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Published: 4 June 2021
Last updated: 6 September 2023

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Journal articles on the topic "Simulated annealing"

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Fabian, V. "Simulated annealing simulated." Computers & Mathematics with Applications 33, no. 1-2 (January 1997): 81–94. http://dx.doi.org/10.1016/s0898-1221(96)00221-0.

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Tovey, Craig A. "Simulated Simulated Annealing." American Journal of Mathematical and Management Sciences 8, no. 3-4 (February 1988): 389–407. http://dx.doi.org/10.1080/01966324.1988.10737246.

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Bonilla-Petriciolet, Adrián, Juan Carlos Tapia-Picazo, Carlos Soto-Becerra, and Javier Gerson Zapiain-Salinas. "Perfiles de comportamiento numérico de los métodos estocásticos simulated annealing y very fast simulated annealing en cálculos termodinámicos." Ingeniería, investigación y tecnología 12, no. 1 (January 1, 2011): 51–62. http://dx.doi.org/10.22201/fi.25940732e.2011.12n1.006.

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KITA, Hajime. "Simulated Annealing." Journal of Japan Society for Fuzzy Theory and Systems 9, no. 6 (1997): 870–75. http://dx.doi.org/10.3156/jfuzzy.9.6_870.

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Bertsimas, Dimitris, and John Tsitsiklis. "Simulated Annealing." Statistical Science 8, no. 1 (February 1993): 10–15. http://dx.doi.org/10.1214/ss/1177011077.

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Johnson, Mark E. "Simulated Annealing." American Journal of Mathematical and Management Sciences 8, no. 3-4 (February 1988): 205–7. http://dx.doi.org/10.1080/01966324.1988.10737241.

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Bhattacharya, Arijit, Sayantan Ghatak, Rajib Das, and Satrajit Ghosh. "Simulated Annealing Approach onto VLSI Circuit Partitioning." Mathematical Journal of Interdisciplinary Sciences 2, no. 2 (March 3, 2014): 133–39. http://dx.doi.org/10.15415/mjis.2014.22010.

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Hamma, Beidi, Sami Viitanen, and Aimo Törn. "Parallel continuous simulated annealing for global optimization simulated annealing∗." Optimization Methods and Software 13, no. 2 (January 2000): 95–116. http://dx.doi.org/10.1080/10556780008805777.

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O. H. Abdelwahed, O. H. Abdelwahed, and M. El-Sayed Wahed. "Optimizing Single Layer Cellular Neural Network Simulator using Simulated Annealing Technique with Neural Networks." Indian Journal of Applied Research 3, no. 6 (October 1, 2011): 91–94. http://dx.doi.org/10.15373/2249555x/june2013/31.

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Kallab, Chadi, Samir Haddad, Jinane Sayah, and Mohamad Chakroun. "Generic Simulated Annealing." Open Journal of Applied Sciences 12, no. 06 (2022): 1011–25. http://dx.doi.org/10.4236/ojapps.2022.126069.

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Dissertations / Theses on the topic "Simulated annealing"

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Araujo, Haroldo Alexandre de. "Algoritmo Simulated Annealing." Florianópolis, SC, 2001. http://repositorio.ufsc.br/xmlui/handle/123456789/80386.

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Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Ciência da Computação.
Made available in DSpace on 2012-10-18T13:35:55Z (GMT). No. of bitstreams: 1 225675.pdf: 796704 bytes, checksum: 892abc8468e4e7c6715b6c3f2de50e51 (MD5)
A busca por soluções de problemas por meio do computador é o tema central da ciência da computação, relevante para grande parte da ciência e de suas aplicações tecnológicas. Essa busca, certamente, vai na direção de algoritmos eficientes e exatos mas que nem sempre boas soluções podem ser encontradas para muitos problemas de ordem prática, principalmente, no que diz respeito a tempo de execução. Existem problemas, dentre estes, os de otimização combinatorial que apresentam uma peculiaridade com relação aos outros, que é a grande dificuldade de se obter soluções exatas num tempo computacional aceitável. Atualmente, as novas técnicas, especialmente as metaheurísticas, tais como: Tabu Search, Simulated Annealing, Algoritmos Genéticos e Redes Neurais, vêm conseguindo sucesso na solução de problemas de otimização combinatorial, que mesmo não apresentando soluções exatas têm mostrado bastante eficiência com suas soluções aproximadas. Este trabalho propõe um novo método baseado no algoritmo Simulated Annealing (SA) através de mudanças bruscas nos valores da temperatura que são retiradas de múltiplas faixas, ao contrário do SA básico, onde esses valores são obtidos de uma faixa única, ou seja, num SA básico, os valores assumidos pela temperatura saem de um intervalo, partindo de um valor inicial, e vão diminuindo até um valor final. Tais mudanças bruscas acontecem exatamente no momento da mudança de faixa, pois o valor da temperatura que no final de uma faixa é pequeno, assume um valor correspondente a temperatura inicial da faixa seguinte, normalmente, bem maior. Posto a prova, com instâncias euclidianas do Problema Caixeiro Viajante, que é um problema de otimização combinatorial de difícil solução, o método apresenta resultados bastante satisfatórios quando comparado com o SA básico.
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Sakhavat, Tamim, Haithem Grissa, and Ziyad Abdalrahman. "Simulated Annealing : Simulated Annealing for Large Scale Optimization in Wireless Communications." Thesis, Linnéuniversitetet, Institutionen för datavetenskap, fysik och matematik, DFM, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-24606.

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In this thesis a simulated annealing algorithm is employed as an optimization tool for a large scale optimization problem in wireless communication. In this application, we have 100 places for transition antennas and 100 places for receivers, and also a channel between each position in both areas. Our aim is to nd, say the best 3 positions there, in a way that the channel capacity is maximized. The number of possible combinations is huge. Hence, nding the best channel will take a very long time using an exhaustive search. To solve this problem, we use a simulated annealing algorithm and estimate the best answer. The simulated annealing algorithm chooses a random element, and then from the local search algorithm, compares the selected element with its neighbourhood. If the selected element is the maximum among its neighbours, it is a local maximum. The strength of the simulated annealing algorithm is its ability to escape from local maximum by using a random mechanism that mimics the Boltzmann statistic.
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Thompson, J. M. "Examination scheduling using simulated annealing." Thesis, Swansea University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.639229.

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Recent increases, both in student numbers and choice of subjects, have made the problem of producing university examination timetables increasingly difficult. Additionally, there is pressure to give students free periods between exams to aid their revision. Many other constraints may also be imposed on the timetable. The aim of this research is to investigate the usefulness of simulated annealing, as a basis of an efficient solution method, for this problem. The examination timetabling problem is shown to be equivalent to the graph colouring problem, with side constraints. This model allows several of the constraints to be included directly, thereby simplifying the problem. The colouring problem is solved in two phases, with the first obtaining a feasible colouring and the second optimising further objectives while maintaining feasibility. Simulated annealing is used to solve each phase and computational experience demonstrates that this results in high quality solutions. In phase two, only feasible solutions, that is those which satisfy the binding constraints, are considered. This may result in the solution space being disconnected or sparsely connected, possibly reducing solution quality. To overcome this problem, three means of reconnecting the solution space have been developed. The first widens the neighbourhood to include more diverse solutions. The second attempts to search disjoint components of the solution space individually, using a diversification function to guide the search. The final method reintroduces solutions that break the binding constraints to the solution space while penalising them in the cost function. Extending the neighbourhood using a graph theoretic entity called a Kempe chain significantly increases solution quality. Several explanations have been investigated. This research shows that a combination of a phased approach and Kempe chains forms the basis of an effective and flexible simulated annealing based examination timetabling system, which has been implemented successfully at a U.K. university.
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Neil, John Paul. "Simulated annealing based datapath synthesis." Thesis, University of Edinburgh, 1994. http://hdl.handle.net/1842/12715.

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The behavioural synthesis procedure aims to produce optimised register-transfer level datapath descriptions from an algorithmic problem definition, normally expressed in a high-level programming language. The procedure can be partitioned into a number of subtasks linked by a serial synthesis flow. Graph theoretic algorithms can be used to provide solutions to these subtasks. Many of these techniques, however, belong to a class of algorithm for which there is no exact solution computable in polynomial time. To overcome this problem, heuristics are used to constrain the solution space. The introduction of heuristics can cause the algorithm to terminate in a local cost minimum. This thesis supports a global formulation of the behavioural synthesis problem. An algorithm which can avoid local minima, simulated annealing forms the basis of the synthesis system reported. A modular software system is presented in support of this approach. A novel data structure enables multiple degrees of optimisation freedom within the datapath solution space. Synthesis primitives, tightly coupled to a solution costing mechanism directed towards the prevalent datapath implementation technologies, form the core of the system. The software is exercised over small and large-scale synthesis benchmarks. The synthesis paradigm is extended by the provision of optimisation routines capable of supporting the generation of functional pipelines.
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Cevikbas, Safak Burak. "Visibility Based Prefetching With Simulated Annealing." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609324/index.pdf.

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Complex urban scene rendering is not feasible without culling invisible geometry before the rendering actually takes place. Visibility culling can be performed on predefined regions of scene where for each region a potential visible set of scene geometry is computed. Rendering cost is reduced since instead of a bigger set only a single PVS which is associated with the region of the viewer is rendered. However, when the viewer leaves a region and enters one of its neighbors, disposing currently loaded PVS and loading the new PVS causes stalls. Prefetching policies are utilized to overcome stalls by loading PVS of a region before the viewer enters it. This study presents a prefetching method for interactive urban walkthroughs. Regions and transitions among them are represented as a graph where the regions are the nodes and transitions are the edges. Groups of nodes are formed according to statistical data of transitions and used as the prefetching policy. Some heuristics for constructing groups of nodes are developed and Simulated Annealing is utilized for constructing optimized groups based on developed heuristics. The proposed method and underlying application of Simulated Annealing are customized for minimizing average transition cost.
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Färm, Petra. "Integrated Logic Synthesis Using Simulated Annealing." Doctoral thesis, KTH, Mikroelektronik och Informationsteknik, IMIT, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4257.

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A conventional logic synthesis flow is composed of three separate phases: technologyindependent optimization, technology mapping, and technology dependentoptimization. A fundamental problem with such a three-phased approach is thatthe global logic structure is decided during the first phase without any knowledge ofthe actual technology parameters considered during later phases. Although technologydependent optimization algorithms perform some limited logic restructuring,they cannot recover from fundamental mistakes made during the first phase, whichoften results in non-satisfiable solutions.We present a global optimization approach combining technology independentoptimization steps with technology dependent objectives in an annealing-basedframework. We prove that, for the presented move set and selection distribution, detailedbalance is satisfied and thus the annealing process asymptotically convergesto an optimal solution. Furthermore, we show that the presented approach cansmoothly trade-off complex, multiple-dimensional objective functions and achievecompetitive results. The combination of technology independent and technologydependent objectives is handled through dynamic weighting. Dynamic weightingreflects the sensitivity of the local graph structures with respect to the actual technologyparameters such as gate sizes, delays, and power levels. The results showthat, on average, the presented advanced annealing approach can improve the areaand delay of circuits optimized using the Boolean optimization technique providedby SIS with 11.2% and 32.5% respectively.Furthermore, we demonstrate how the developed logic synthesis framework canbe applied to two emerging technologies, chemically assembled nanotechnology andmolecule cascades. New technologies are emerging because a number of physicaland economic factors threaten the continued scaling of CMOS devices. Alternativesto silicon VLSI have been proposed, including techniques based on molecularelectronics, quantum mechanics, and biological processes. We are hoping that ourresearch in how to apply our developed logic synthesis framework to two of theemerging technologies might provide useful information for other designers movingin this direction.
QC 20100709
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Allred, Kory J. "Horizontal alignment optimization using simulated annealing /." Available to subscribers only, 2006. http://proquest.umi.com/pqdweb?did=1240703751&sid=3&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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Faassen, Johannes [Verfasser]. "Voll datenparalleles Simulated Annealing / Johannes Faassen." Aachen : Shaker, 2003. http://d-nb.info/1179034473/34.

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Wade, A. S. C. "Developments of the simulated annealing algorithm." Thesis, University of East Anglia, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.300076.

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Zhou, Guobiao. "Finite time performance of simulated annealing." Thesis, Glasgow Caledonian University, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.358284.

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Books on the topic "Simulated annealing"

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Vidal, René V. V., ed. Applied Simulated Annealing. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-46787-5.

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Valqui, Vidal René Victor, ed. Applied simulated annealing. Berlin: Springer-Verlag, 1993.

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Robert, Azencott, ed. Simulated annealing: Parallelization techniques. New York: Wiley, 1992.

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Jerrum, Mark. Simulated annealing for graph bisection. Edinburgh: LFCS, Dept. of Computer Science, University of Edinburgh, 1993.

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L, Aarts E. H., ed. Simulated annealing: Theory and applications. Dordrecht: D. Reidel, 1987.

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van Laarhoven, Peter J. M., and Emile H. L. Aarts. Simulated Annealing: Theory and Applications. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-015-7744-1.

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Wong, D. F., H. W. Leong, and C. L. Liu. Simulated Annealing for VLSI Design. Boston, MA: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4613-1677-0.

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Laarhoven, Peter J. M. Simulated Annealing: Theory and Applications. Dordrecht: Springer Netherlands, 1987.

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Lawrence, Davis, ed. Genetic algorithms and simulated annealing. London: Pitman, 1987.

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Wong, D. F. Simulated annealing for VLSI design. Boston: Kluwer Academic, 1988.

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Book chapters on the topic "Simulated annealing"

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Du, Ke-Lin, and M. N. S. Swamy. "Simulated Annealing." In Search and Optimization by Metaheuristics, 29–36. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41192-7_2.

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Čepin, Marko. "Simulated Annealing." In Assessment of Power System Reliability, 271–75. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-688-7_19.

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Aarts, Emile, Jan Korst, and Wil Michiels. "Simulated Annealing." In Search Methodologies, 265–85. Boston, MA: Springer US, 2013. http://dx.doi.org/10.1007/978-1-4614-6940-7_10.

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Nikolaev, Alexander G., and Sheldon H. Jacobson. "Simulated Annealing." In Handbook of Metaheuristics, 1–39. Boston, MA: Springer US, 2010. http://dx.doi.org/10.1007/978-1-4419-1665-5_1.

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Dowsland, Kathryn A., and Jonathan M. Thompson. "Simulated Annealing." In Handbook of Natural Computing, 1623–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-540-92910-9_49.

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Aarts, E., P. van der Horn, J. Korst, W. Michiels, and H. Sontrop. "Simulated Annealing." In Metaheuristic Procedures for Training Neutral Networks, 37–52. Boston, MA: Springer US, 2006. http://dx.doi.org/10.1007/0-387-33416-5_2.

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Awange, Joseph L., Béla Paláncz, Robert H. Lewis, and Lajos Völgyesi. "Simulated Annealing." In Mathematical Geosciences, 113–36. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-67371-4_4.

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Wang, Sun-Chong. "Simulated Annealing." In Interdisciplinary Computing in Java Programming, 59–79. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0377-4_4.

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Siarry, Patrick. "Simulated Annealing." In Metaheuristics, 19–50. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45403-0_2.

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van Laarhoven, Peter J. M., and Emile H. L. Aarts. "Simulated annealing." In Simulated Annealing: Theory and Applications, 7–15. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-015-7744-1_2.

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Conference papers on the topic "Simulated annealing"

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Fleischer, Mark. "Simulated annealing." In the 27th conference. New York, New York, USA: ACM Press, 1995. http://dx.doi.org/10.1145/224401.224457.

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Carvalho, Vinícius Nunes, and Sezimária de Fátima Pereira Saramago. "IMPROVED SIMULATED ANNEALING." In Congresso Nacional de Matemática Aplicada à Indústria. São Paulo: Editora Edgard Blücher, 2015. http://dx.doi.org/10.5151/mathpro-cnmai-0041.

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Szu, Harold. "Fast simulated annealing." In AIP Conference Proceedings Volume 151. AIP, 1986. http://dx.doi.org/10.1063/1.36250.

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Singh, Nishant, and Bahniman Ghosh. "Simulated annealing Vs. Genetic Simulated Annealing for automatic transistor sizing." In 2012 10th IEEE International Conference on Semiconductor Electronics (ICSE). IEEE, 2012. http://dx.doi.org/10.1109/smelec.2012.6417190.

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Crosson, Elizabeth, and Aram W. Harrow. "Simulated Quantum Annealing Can Be Exponentially Faster Than Classical Simulated Annealing." In 2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS). IEEE, 2016. http://dx.doi.org/10.1109/focs.2016.81.

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Kerrache, Said, and Hafida Benhidour. "Topology-Aware Simulated Annealing." In 2014 2nd International Conference on Artificial Intelligence, Modelling & Simulation (AIMS). IEEE, 2014. http://dx.doi.org/10.1109/aims.2014.49.

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Nahar, Surendra, Sartaj Sahni, and Eugene Shragowitz. "Experiments with simulated annealing." In the 22nd ACM/IEEE conference. New York, New York, USA: ACM Press, 1985. http://dx.doi.org/10.1145/317825.317977.

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Nahar, S., S. Sahni, and E. Shragowitz. "Experiments with Simulated Annealing." In 22nd ACM/IEEE Design Automation Conference. IEEE, 1985. http://dx.doi.org/10.1109/dac.1985.1586028.

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Cook, Rod, Ian McConnell, David Stewart, and Christopher J. Oliver. "Segmentation and simulated annealing." In Satellite Remote Sensing III, edited by Giorgio Franceschetti, Christopher J. Oliver, Franco S. Rubertone, and Shahram Tajbakhsh. SPIE, 1996. http://dx.doi.org/10.1117/12.262709.

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Esmailzadeh, A., and S. Rahnamayan. "Center-point-based Simulated Annealing." In 2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE). IEEE, 2012. http://dx.doi.org/10.1109/ccece.2012.6334976.

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Reports on the topic "Simulated annealing"

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Bandyopadhyay, S., S. K. Pal, and C. A. Murthy. Simulated Annealing Based Pattern Classification. Fort Belvoir, VA: Defense Technical Information Center, May 1998. http://dx.doi.org/10.21236/ada358039.

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Cole, James B., and David H. Gerstman. Image Recovery by Simulated Annealing. Fort Belvoir, VA: Defense Technical Information Center, November 1990. http://dx.doi.org/10.21236/ada230655.

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Rose, Jonathan, Wolfgang Klebsch, and Juergen Wolf. Temperature Measurement of Simulated Annealing Placements. Fort Belvoir, VA: Defense Technical Information Center, January 1987. http://dx.doi.org/10.21236/ada207229.

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Gelfand, Saul B., and Sanjoy K. Mitter. Analysis of Simulated Annealing for Optimization. Fort Belvoir, VA: Defense Technical Information Center, September 1985. http://dx.doi.org/10.21236/ada170174.

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Gelfand, Saul B., and Sanjoy K. Mitter. Simulated Annealing Type Algorithms for Multivariate Optimization. Fort Belvoir, VA: Defense Technical Information Center, January 1989. http://dx.doi.org/10.21236/ada460156.

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Fleischer, Mark, and Sheldon Jacobson. Scale Invariance Properties in the Simulated Annealing Algorithm. Fort Belvoir, VA: Defense Technical Information Center, January 2002. http://dx.doi.org/10.21236/ada442644.

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Tsitsiklis, John N. Markov Chains with Rare Transitions and Simulated Annealing. Fort Belvoir, VA: Defense Technical Information Center, September 1985. http://dx.doi.org/10.21236/ada161598.

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Rose, Jonathan, Wolfgang Klebsch, and Juergen Wolf. Temperature Measurement and Equilibrium Dynamics of Simulated Annealing Placements. Fort Belvoir, VA: Defense Technical Information Center, January 1987. http://dx.doi.org/10.21236/ada207230.

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Nakao, Shinsuke, J. Najita, and Kenzi Karasaki. Sensitivity study on hydraulic well testing inversion using simulated annealing. Office of Scientific and Technical Information (OSTI), November 1997. http://dx.doi.org/10.2172/658166.

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Yildirim, Cem, Jon T. Butler, and Chyan Yang. Multiple-Valued PLA Minimization by Concurrent Multiple and Mixed Simulated Annealing. Fort Belvoir, VA: Defense Technical Information Center, May 1993. http://dx.doi.org/10.21236/ada605412.

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