Relevant bibliographies by topics / Mathematics Heuristic

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  2. Dissertations / Theses
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Academic literature on the topic 'Mathematics Heuristic'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 February 2022

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Journal articles on the topic "Mathematics Heuristic"

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BOUZY, BRUNO. "HISTORY AND TERRITORY HEURISTICS FOR MONTE CARLO GO." New Mathematics and Natural Computation 02, no. 02 (2006): 139–46. http://dx.doi.org/10.1142/s1793005706000427.

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Recently, the Monte Carlo approach has been applied to computer go with promising success. INDIGO uses such an approach which can be enhanced with specific heuristics. This paper assesses two heuristics within the 19 × 19 Monte Carlo go framework of INDIGO: the territory heuristic and the history heuristic, both in their internal and external versions. The external territory heuristic is more effective, leading to a 40-point improvement on 19 × 19 boards. The external history heuristic brings about a 10-point improvement. The internal territory heuristic yields a few points improvement, and th
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Lucas, J. F. "Heuristic Thinking and Mathematics." Humanistic Mathematics Network Journal 1, no. 5 (1990): 9–12. http://dx.doi.org/10.5642/hmnj.199001.05.05.

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Drake, John H., Ender Özcan, and Edmund K. Burke. "A Case Study of Controlling Crossover in a Selection Hyper-heuristic Framework Using the Multidimensional Knapsack Problem." Evolutionary Computation 24, no. 1 (2016): 113–41. http://dx.doi.org/10.1162/evco_a_00145.

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Hyper-heuristics are high-level methodologies for solving complex problems that operate on a search space of heuristics. In a selection hyper-heuristic framework, a heuristic is chosen from an existing set of low-level heuristics and applied to the current solution to produce a new solution at each point in the search. The use of crossover low-level heuristics is possible in an increasing number of general-purpose hyper-heuristic tools such as HyFlex and Hyperion. However, little work has been undertaken to assess how best to utilise it. Since a single-point search hyper-heuristic operates on
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Hart, Emma, and Kevin Sim. "A Hyper-Heuristic Ensemble Method for Static Job-Shop Scheduling." Evolutionary Computation 24, no. 4 (2016): 609–35. http://dx.doi.org/10.1162/evco_a_00183.

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We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conquer approach in which each heuristic solves a unique subset of the instance set considered. NELLI-GP extends an existing ensemble method called NELLI by introducing a novel heuristic generator that evolves heuristics composed of linear sequences of dispatching rules: each rule is represented using a tree structure and is itself evolved. Following a training period, the ensemble is shown to outperform both existing dispatc
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Ren, Zhilei, He Jiang, Jifeng Xuan, and Zhongxuan Luo. "Hyper-Heuristics with Low Level Parameter Adaptation." Evolutionary Computation 20, no. 2 (2012): 189–227. http://dx.doi.org/10.1162/evco_a_00063.

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Recent years have witnessed the great success of hyper-heuristics applying to numerous real-world applications. Hyper-heuristics raise the generality of search methodologies by manipulating a set of low level heuristics (LLHs) to solve problems, and aim to automate the algorithm design process. However, those LLHs are usually parameterized, which may contradict the domain independent motivation of hyper-heuristics. In this paper, we show how to automatically maintain low level parameters (LLPs) using a hyper-heuristic with LLP adaptation (AD-HH), and exemplify the feasibility of AD-HH by adapt
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Hoon, Teoh Sian, Kor Liew Kee, and Parmjit Singh. "Learning Mathematics Using Heuristic Approach." Procedia - Social and Behavioral Sciences 90 (October 2013): 862–69. http://dx.doi.org/10.1016/j.sbspro.2013.07.162.

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Зацепина, Ю. А., та Е. Е. Кирьянова. "Методика применения эвристических подходов при решении математических задач". ТЕНДЕНЦИИ РАЗВИТИЯ НАУКИ И ОБРАЗОВАНИЯ 70, № 2 (2021): 56–60. http://dx.doi.org/10.18411/lj-02-2021-53.

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Taking into account the development of science and technology, the use of heuristic methods in the learning process is becoming popular for the development of thinking and logic. Heuristic methods in mathematics are not only something entertaining and fascinating, but also an effective tool for mastering the material and developing students ' logical thinking. The considered heuristic methods will simplify the solution of mathematical problems in the school mathematics course.
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Skafa, E. I. "Organization of project-heuristic activity of future mathematics teachers in creating multimedia teaching tools." Informatics and education, no. 5 (July 16, 2021): 59–64. http://dx.doi.org/10.32517/0234-0453-2021-36-5-59-64.

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Now we can see a widespread introduction of modern digital technologies into the educational process in mathematics. These technologies can make learning more visual and accessible, implement an individual approach in teaching and manage the educationalcognitive heuristic activity of schoolchildren. The organization of project-heuristic activities in a higher pedagogical school can help prepare a future teacher for the development of computer-related tools. We refer to the means of digitalization of modern education as heuristic-didactic constructions in the form of computer programs for “non-
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Burke, Edmund K., Matthew R. Hyde, Graham Kendall, and John Woodward. "Automating the Packing Heuristic Design Process with Genetic Programming." Evolutionary Computation 20, no. 1 (2012): 63–89. http://dx.doi.org/10.1162/evco_a_00044.

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The literature shows that one-, two-, and three-dimensional bin packing and knapsack packing are difficult problems in operational research. Many techniques, including exact, heuristic, and metaheuristic approaches, have been investigated to solve these problems and it is often not clear which method to use when presented with a new instance. This paper presents an approach which is motivated by the goal of building computer systems which can design heuristic methods. The overall aim is to explore the possibilities for automating the heuristic design process. We present a genetic programming s
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SWAN, JERRY, GABRIELA OCHOA, GRAHAM KENDALL, and MARTIN EDJVET. "FITNESS LANDSCAPES AND THE ANDREWS–CURTIS CONJECTURE." International Journal of Algebra and Computation 22, no. 02 (2012): 1250009. http://dx.doi.org/10.1142/s0218196711006753.

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Attempts have been made to eliminate some potential counterexamples to the Andrews–Curtis conjecture using the combinatorial optimization methods of blind-search and the genetic algorithms meta-heuristic. Breadth-first search with secondary storage is currently the most successful method, which raises questions regarding the inferior performance of heuristic search. In order to understand the underlying reasons we obtain fitness landscape metrics for a number of balanced presentations and draw conclusions regarding the likely effectiveness of other meta-heuristics.
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Dissertations / Theses on the topic "Mathematics Heuristic"

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Pair, Jeffrey David. "The Nature of Mathematics| A Heuristic Inquiry." Thesis, Middle Tennessee State University, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10287185.

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<p> What is mathematics? What does it mean to be a mathematician? What should students understand about the nature of mathematical knowledge and inquiry? Research in the field of mathematics education has found that students often have na&iuml;ve views about the nature of mathematics. Some believe that mathematics is a body of unchanging knowledge, a collection of arbitrary rules and procedures that must be memorized. Mathematics is seen as an impersonal and uncreative subject. To combat the na&iuml;ve view, we need a humanistic vision and explicit goals for what we hope students understand ab
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Henry, Obit Joe. "Developing novel meta-heuristic, hyper-heuristic and cooperative search for course timetabling problems." Thesis, University of Nottingham, 2010. http://eprints.nottingham.ac.uk/13581/.

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The research presented in this PhD thesis focuses on the problem of university course timetabling, and examines the various ways in which metaheuristics, hyperheuristics and cooperative heuristic search techniques might be applied to this sort of problem. The university course timetabling problem is an NP-hard and also highly constrained combinatorial problem. Various techniques have been developed in the literature to tackle this problem. The research work presented in this thesis approaches this problem in two stages. For the first stage, the construction of initial solutions or timetables,
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Padungwech, Wasin. "Heuristic algorithms for dynamic capacitated arc routing." Thesis, Cardiff University, 2018. http://orca.cf.ac.uk/111021/.

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This thesis concerns the capacitated arc routing problem (CARP), which can be used as a model of various real-life scenarios such as rubbish collection, snow ploughing, and other situations where an emphasis is placed on providing a certain service along streets. The goal of the CARP is to find a minimum-cost set of routes such that (i) each route starts and ends at the depot, (ii) each task is serviced in one of the routes, and (iii) the total demand in each route does not exceed the capacity. Until recently, the study of the CARP is concentrated on its "static" version, that is, it is assume
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Morgan, G. G. "A computational model of heuristic learning from mathematics text books." Thesis, University of Sheffield, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.242278.

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Elson, E. C. "Heuristic optimisation and parameter estimation methods for modern cosmological surveys." Master's thesis, University of Cape Town, 2006. http://hdl.handle.net/11427/4882.

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Kadhem, Dhia. "Heuristic solution approaches to the solid assignment problem." Thesis, University of Essex, 2017. http://repository.essex.ac.uk/20907/.

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The 3-dimensional assignment problem, also known as the Solid Assignment Problem (SAP), is a challenging problem in combinatorial optimisation. While the ordinary or 2-dimensional assignment problem is in the P-class, SAP which is an extension of it, is NP-hard. SAP is the problem of allocating n jobs to n machines in n factories such that exactly one job is allocated to one machine in one factory. The objective is to minimise the total cost of getting these n jobs done. The problem is commonly solved using exact methods of integer programming such as Branch-and-Bound B&B. As it is intractable
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Whitelaw, Louise A. Reisman Fredricka K. "An evaluative study of teacher creativity, use of the heuristic diagnostic teaching process and student mathematics performance /." Philadelphia, Pa. : Drexel University, 2007. http://hdl.handle.net/1860/1870.

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Alrajhi, Khaled. "Heuristic algorithms for static and dynamic frequency assignment problems." Thesis, Cardiff University, 2016. http://orca.cf.ac.uk/94194/.

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This thesis considers the frequency assignment problem (FAP), which is a real world problem of assigning frequencies to wireless communication connections (also known as requests) while satisfying a set of constraints in order to prevent a loss of signal quality. This problem has many different applications such as mobile phones, TV broadcasting, radio and military operations. In this thesis, two variants of the FAP are considered, namely the static and the dynamic FAPs. The static FAP does not change over time, while the dynamic FAP changes over time as new requests gradually be-come known an
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Wong, Man-on. "The effect of heuristics on mathematical problem solving." [Hong Kong : University of Hong Kong], 1994. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13834265.

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Mohmad, Kahar Mohd Nizam. "Heuristic approaches for real world examination timetabling problems." Thesis, University of Nottingham, 2013. http://eprints.nottingham.ac.uk/27677/.

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The examination timetabling (exam-timeslot-room assignment) problem involves assigning exams to a specific or limited number of timeslots and rooms, with the aim of satisfying the hard constraints and the soft constraints as much as possible. Most of the techniques reported in the literature have been applied to solve simplified examination benchmark datasets, available within the scientific literature. In this research we bridge the gap between research and practice by investigating a problem taken from the Universiti Malaysia Pahang (UMP), a real world capacitated examination timetabling pro
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Books on the topic "Mathematics Heuristic"

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Roos, N. TUD Faculty of Technical Mathematics and Informatics: Heuristic reasoning. National Aerospace Laboratory, 1988.

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Katsifarakis, K. L. Hydrology, hydraulics and water resources management: A heuristic optimization approach. WIT Press, 2012.

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Engineering optimization: An introduction with metaheuristic applications. Wiley, 2010.

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Mockus, Jonas. Bayesian Heuristic Approach to Discrete and Global Optimization: Algorithms, Visualization, Software, and Applications. Springer US, 1997.

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Gerhard, Reinelt, and SpringerLink (Online service), eds. The Linear Ordering Problem: Exact and Heuristic Methods in Combinatorial Optimization. Springer-Verlag Berlin Heidelberg, 2011.

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Stützle, Thomas, Vittorio Maniezzo, and Stefan Voss. Matheuristics: Hybridizing metaheuristics and mathematical programming. Springer, 2009.

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Heuristics and metaheuristics for heavily constrained hybrid flowshop problems. IOS Press, 2011.

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Birattari, Mauro. Tuning Metaheuristics: A Machine Learning Perspective. Springer Berlin Heidelberg, 2009.

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library, Wiley online, ed. Engineering optimization: An introduction with metaheuristic applications. John Wiley, 2010.

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Biswas, R. Load balancing sequences of unstructured adaptive grids. Research Institute for Advanced Computer Science, NASA Ames Research Center, 1997.

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Book chapters on the topic "Mathematics Heuristic"

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Lang, Reinhard. "The general heuristic picture." In Lecture Notes in Mathematics. Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/bfb0093932.

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Pedemonte, Martín, Pablo Ezzatti, and Álvaro Martín. "Accelerating the Min-Min Heuristic." In Parallel Processing and Applied Mathematics. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32152-3_10.

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Friedman, Avner. "Analytical and heuristic modeling of distributed algorithms." In Mathematics in Industrial Problems. Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4613-9177-7_6.

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Bychkov, Ilya, Mikhail Batsyn, Pavel Sukhov, and Panos M. Pardalos. "Heuristic Algorithm for the Cell Formation Problem." In Springer Proceedings in Mathematics & Statistics. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8588-9_4.

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Toporkov, Victor, Dmitry Yemelyanov, and Anna Toporkova. "Fair Scheduling in Grid VOs with Anticipation Heuristic." In Parallel Processing and Applied Mathematics. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78054-2_14.

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Manna, Apurba, Samir Maity, and Arindam Roy. "A Heuristic Approach for Cluster TSP." In Recent Advances in Intelligent Information Systems and Applied Mathematics. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-34152-7_4.

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Dodgson, Neil A. "An Heuristic Analysis of the Classification of Bivariate Subdivision Schemes." In Mathematics of Surfaces XI. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11537908_10.

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Thuerck, Daniel, Sven Widmer, Arjan Kuijper, and Michael Goesele. "Efficient Heuristic Adaptive Quadrature on GPUs: Design and Evaluation." In Parallel Processing and Applied Mathematics. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-55224-3_61.

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Gravemeijer, Koeno, and Michelle Stephan. "Emergent Models as an Instructional Design Heuristic." In Symbolizing, Modeling and Tool Use in Mathematics Education. Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-017-3194-2_10.

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Friedman, Avner. "Mathematical models for thermal imaging-an heuristic approach." In The IMA Volumes in Mathematics and Its Applications. Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4615-7402-6_7.

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Conference papers on the topic "Mathematics Heuristic"

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Ma, Yu-Ming. "Heuristic Teaching Method of Discrete Mathematics based on the Mathematical Games." In 2017 2nd International Conference on Humanities and Social Science (HSS 2017). Atlantis Press, 2017. http://dx.doi.org/10.2991/hss-17.2017.27.

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Sze, San-Nah, Jeeu-Fong Sze, and Kang-Leng Chiew. "A manpower scheduling heuristic for aircraft maintenance application." In NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2012: International Conference of Numerical Analysis and Applied Mathematics. AIP, 2012. http://dx.doi.org/10.1063/1.4756352.

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Fatima, Iqra, Nadeem Javaid, Sundas Shafiq, Sikandar Asif, Muhammad Hassan Rahim, and Sheraz Aslam. "Comparative study of meta-heuristic approaches towards utilization of home energy management: Comparative meta-heuristic approaches." In 2018 International Conference on Computing, Mathematics and Engineering Technologies (iCoMET). IEEE, 2018. http://dx.doi.org/10.1109/icomet.2018.8346436.

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Suma, T., and R. Murugesan. "Mathematical model and heuristic based subtask scheduling algorithm for order scheduling." In SECOND INTERNATIONAL CONFERENCE OF MATHEMATICS (SICME2019). Author(s), 2019. http://dx.doi.org/10.1063/1.5097537.

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Nazri, Engku Muhammad, and Stanley Murairwa. "Classification of heuristic techniques for performance comparisons." In 2016 12th International Conference on Mathematics, Statistics, and Their Application (ICMSA). IEEE, 2016. http://dx.doi.org/10.1109/icmsa.2016.7954300.

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Masran, Hafiz, Mohammad Fadzli, Wan Zuki Azman Wan Muhamad, and Wan Nor Munirah. "Modification heuristic method in solid waste collection within Perlis, Malaysia." In INTERNATIONAL CONFERENCE ON MATHEMATICS, ENGINEERING AND INDUSTRIAL APPLICATIONS 2016 (ICoMEIA2016): Proceedings of the 2nd International Conference on Mathematics, Engineering and Industrial Applications 2016. Author(s), 2016. http://dx.doi.org/10.1063/1.4965155.

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Soma, Ken-ichiro, Ryota Mori, Ryuichi Sato, et al. "A Heuristic Approach to Intra-Brain Communications Using Chaos in a Recurrent Neural Network Model." In NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2011: International Conference on Numerical Analysis and Applied Mathematics. AIP, 2011. http://dx.doi.org/10.1063/1.3637871.

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Kartak, V. M., A. A. Marchenko, A. A. Petunin, A. N. Sesekin, and A. I. Fabarisova. "Optimal and heuristic algorithms of planning of low-rise residential buildings." In APPLICATION OF MATHEMATICS IN TECHNICAL AND NATURAL SCIENCES: 9th International Conference for Promoting the Application of Mathematics in Technical and Natural Sciences - AMiTaNS’17. Author(s), 2017. http://dx.doi.org/10.1063/1.5007408.

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Kumar, Sushant, Prabhat Ranjan, and R. Rajesh. "An Overview of Test Case Optimization Using Meta-Heuristic Approach." In International Conference on Recent Advances in Mathematics, Statistics and Computer Science 2015. WORLD SCIENTIFIC, 2016. http://dx.doi.org/10.1142/9789814704830_0044.

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Mexicano, A., R. Rodríguez, S. Cervantes, et al. "The early stop heuristic: A new convergence criterion for K-means." In INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2015 (ICNAAM 2015). Author(s), 2016. http://dx.doi.org/10.1063/1.4952103.

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