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Relevant bibliographies by topics / Linear search

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Academic literature on the topic 'Linear search'

Author: Grafiati

Published: 25 May 2024

Last updated: 25 July 2025

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Journal articles on the topic "Linear search"

1

Hohzaki, Ryusuke. "A SEARCH GAME TAKING ACCOUNT OF LINEAR EFFECTS AND LINEAR CONSTRAINTS OF SEARCHING RESOURCE." Journal of the Operations Research Society of Japan 55, no. 1 (2012): 1–22. http://dx.doi.org/10.15807/jorsj.55.1.

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Mäkinen, Erkki. "On linear search heuristics." Information Processing Letters 29, no. 1 (1988): 35–36. http://dx.doi.org/10.1016/0020-0190(88)90129-9.

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Hester, J. H., and D. S. Hirschberg. "Self-organizing linear search." ACM Computing Surveys 17, no. 3 (1985): 295–311. http://dx.doi.org/10.1145/5505.5507.

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Arora, Nitin, Garima Bhasin, and Neha Sharma. "Two way Linear Search Algorithm." International Journal of Computer Applications 107, no. 21 (2014): 6–8. http://dx.doi.org/10.5120/19137-9622.

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Limoncelli, Thomas A. "10 optimizations on linear search." Communications of the ACM 59, no. 9 (2016): 44–48. http://dx.doi.org/10.1145/2980976.

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Limoncelli, Thomas A. "10 Optimizations on Linear Search." Queue 14, no. 4 (2016): 20–33. http://dx.doi.org/10.1145/2984629.2984631.

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Korf, Richard E. "Linear-space best-first search." Artificial Intelligence 62, no. 1 (1993): 41–78. http://dx.doi.org/10.1016/0004-3702(93)90045-d.

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Foley, R. D., T. P. Hill, and M. C. Spruill. "Linear search with bounded resources." Naval Research Logistics 38, no. 4 (1991): 555–65. http://dx.doi.org/10.1002/1520-6750(199108)38:4<555::aid-nav3220380408>3.0.co;2-8.

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Kumari, Anchala. "Linear Search Versus Binary Search:A Statistical Comparison For Binomial Inputs." International Journal of Computer Science, Engineering and Applications 2, no. 2 (2012): 29–39. http://dx.doi.org/10.5121/ijcsea.2012.2203.

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Balkhi, Zaid T. "THE GENERALIZED LINEAR SEARCH PROBLEM, EXISTENCE OF OPTIMAL SEARCH PATHS." Journal of the Operations Research Society of Japan 30, no. 4 (1987): 399–421. http://dx.doi.org/10.15807/jorsj.30.399.

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Dissertations / Theses on the topic "Linear search"

1

Rees, Leigh H. "Chirality : in search of organometallic second order non-linear optic materials." Thesis, University of Bristol, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.265324.

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Hepburn, Ian David. "Development of linear InSb array instrumentation and the search for brown dwarfs." Thesis, Imperial College London, 1991. http://hdl.handle.net/10044/1/46816.

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Bothwell, Brian P. "An Iterative Linear Programming Approach to Solving Large Cumulative Search-Evasion Games." Thesis, Monterey, California. Naval Postgraduate School, 1990. http://hdl.handle.net/10945/30678.

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Approved for public release, distribution is unlimited<br>Cumulative search-evasion games (CSEGs) involve two players, a searcher and an evader, who move among some finite set of cells. Neither player is aware of the other player's position during any stage of the game. When the payoff for the game is assumed to be the number of times the searcher and evader occupy the same cell, Eagle and Washburn proposed two solution techniques: one by fictitious play and the other by solving equivalent linear programming formulations. However, both have proved to be time consuming even for moderately sized

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Madabushi, Ananth R. "Lagrangian Relaxation / Dual Approaches For Solving Large-Scale Linear Programming Problems." Thesis, Virginia Tech, 1997. http://hdl.handle.net/10919/36833.

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This research effort focuses on large-scale linear programming problems that arise in the context of solving various problems such as discrete linear or polynomial, and continuous nonlinear, nonconvex programming problems, using linearization and branch-and-cut algorithms for the discrete case, and using polyhedral outer-approximation methods for the continuous case. These problems arise in various applications in production planning, location-allocation, game theory, economics, and many engineering and systems design problems. During the solution process of discrete or continuous nonconvex pr

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Kim, Seongsu. "A BAYESIAN EVIDENCE DEFINING SEARCH." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1429789001.

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Law, Glenn W. (Glenn Woodrow). "Measurements of ocular counterrolling during linear accelerations using an electromagnetic scleral search coil system." Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/43236.

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Stokes, Klara. "Combinatorial structures for anonymous database search." Doctoral thesis, Universitat Rovira i Virgili, 2011. http://hdl.handle.net/10803/52799.

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This thesis treats a protocol for anonymous database search (or if one prefer, a protocol for user-private information retrieval), that is based on the use of combinatorial configurations. The protocol is called P2P UPIR. It is proved that the (v,k,1)-balanced incomplete block designs (BIBD) and in particular the finite projective planes are optimal configurations for this protocol. The notion of n-anonymity is applied to the configurations for P2P UPIR protocol and the transversal designs are proved to be n-anonymous configurations for P2P UPIR, with respect to the neighborhood points of the

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Vasireddy, Jhansi Lakshmi. "Applications of Linear Algebra to Information Retrieval." Digital Archive @ GSU, 2009. http://digitalarchive.gsu.edu/math_theses/71.

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Some of the theory of nonnegative matrices is first presented. The Perron-Frobenius theorem is highlighted. Some of the important linear algebraic methods of information retrieval are surveyed. Latent Semantic Indexing (LSI), which uses the singular value de-composition is discussed. The Hyper-Text Induced Topic Search (HITS) algorithm is next considered; here the power method for finding dominant eigenvectors is employed. Through the use of a theorem by Sinkohrn and Knopp, a modified HITS method is developed. Lastly, the PageRank algorithm is discussed. Numerical examples and MATLAB programs

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Lopez, Soto Claudia Orquidea. "Formulation space search for two-dimensional packing problems." Thesis, Brunel University, 2013. http://bura.brunel.ac.uk/handle/2438/7455.

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The two-dimension packing problem is concerned with the arrangement of items without overlaps inside a container. In particular we have considered the case when the items are circular objects, some of the general examples that can be found in the industry are related with packing, storing and transportation of circular objects. Although there are several approaches we want to investigate the use of formulation space search. Formulation space search is a fairly recent method that provides an easy way to escape from local optima for non-linear problems allowing to achieve better results. Despite

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Lazic, Jasmina. "New variants of variable neighbourhood search for 0-1 mixed integer programming and clustering." Thesis, Brunel University, 2010. http://bura.brunel.ac.uk/handle/2438/4602.

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Many real-world optimisation problems are discrete in nature. Although recent rapid developments in computer technologies are steadily increasing the speed of computations, the size of an instance of a hard discrete optimisation problem solvable in prescribed time does not increase linearly with the computer speed. This calls for the development of new solution methodologies for solving larger instances in shorter time. Furthermore, large instances of discrete optimisation problems are normally impossible to solve to optimality within a reasonable computational time/space and can only be tackl

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Books on the topic "Linear search"

1

Laguna, Manuel. Scatter search: Methodology and implementation in C. Kluwer Academic Publishers, 2003.

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Serafimova, Vera, Ivan Pankeev, and L. G. Tyurina. History of Russian literature of the XX-XXI centuries. INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1866868.

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The textbook consists of review and monographic chapters, presents a modern view of the literary process of the XX — early XXI century, examines the work of poets, novelists, playwrights who caused an extraordinary rise in spirituality and culture of the period under consideration. The analysis of the top works of Nobel Prize laureates is given: I. Bunin, B. Pasternak, M. Sholokhov, A. Solzhenitsyn, I. Brodsky, writers- front—line poets and prose writers. Attention is paid to the work of writers of Russian emigration. The section "Modern prose" includes materials on philosophical and aesthetic

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Serafimova, Vera. History of Russian literature of XX-XXI centuries. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1138897.

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The textbook consists of review and monographic chapters, presents a modern view of the literary process of the XX-beginning of the XXI century, examines the work of poets, prose writers, playwrights who caused an extraordinary rise in spirituality and culture of the period under consideration. The analysis of the top works of Nobel prize winners: I. Bunin, B. Pasternak, M. Sholokhov, A. Solzhenitsyn, V. Shalamov, I. Brodsky, writers-front — line poets and prose writers is given. Attention is paid to the work of writers of Russian emigration. The section "Modern prose" includes materials about

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Aron, Richard M., Luis Bernal-Gonzalez, Daniel M. Pellegrino, and Juan B. Seoane Sepulveda. Lineability: The Search for Linearity in Mathematics. Taylor & Francis Group, 2015.

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Aron, Richard M., Luis Bernal-Gonzalez, Daniel M. Pellegrino, and Juan B. Seoane Sepulveda. Lineability: The Search for Linearity in Mathematics. Taylor & Francis Group, 2015.

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Aron, Richard M., Luis Bernal-Gonzalez, Daniel M. Pellegrino, and Juan B. Seoane Sepulveda. Lineability: The Search for Linearity in Mathematics. Taylor & Francis Group, 2015.

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Aron, Richard M., Luis Bernal-Gonzalez, Daniel M. Pellegrino, and Juan B. Seoane Sepulveda. Lineability: The Search for Linearity in Mathematics. Taylor & Francis Group, 2018.

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8

Fortnow, Lance. Golden Ticket: P, NP, and the Search for the Impossible. Princeton University Press, 2013.

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Fortnow, Lance. Golden Ticket: P, Np, and the Search for the Impossible. Princeton University Press, 2013.

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Fortnow, Lance. The Golden Ticket: P, NP, and the Search for the Impossible. Princeton University Press, 2017.

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Book chapters on the topic "Linear search"

1

Weik, Martin H. "linear search." In Computer Science and Communications Dictionary. Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_10241.

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Feijen, W. H. J., and A. J. M. van Gasteren. "The Parallel Linear Search." In Monographs in Computer Science. Springer New York, 1999. http://dx.doi.org/10.1007/978-1-4757-3126-2_18.

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3

Subero, Armstrong. "Linear and Binary Search." In Codeless Data Structures and Algorithms. Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5725-8_6.

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4

Thordsen, Erik, and Erich Schubert. "On Projections to Linear Subspaces." In Similarity Search and Applications. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17849-8_7.

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Spirtes, Peter, Clark Glymour, and Richard Scheines. "Elaborating Linear Theories with Unmeasured Variables." In Causation, Prediction, and Search. Springer New York, 1993. http://dx.doi.org/10.1007/978-1-4612-2748-9_11.

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6

Collet, Jean-François. "Linear algebra and search engines." In Discrete Stochastic Processes and Applications. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74018-8_2.

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Zhang, Shiwei, Guomin Yang, and Yi Mu. "Linear Encryption with Keyword Search." In Information Security and Privacy. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40367-0_12.

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Boytsov, Leonid. "Super-Linear Indices for Approximate Dictionary Searching." In Similarity Search and Applications. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32153-5_12.

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Hünemörder, Maximilian Archimedes Xaver, Daniyal Kazempour, Peer Kröger, and Thomas Seidl. "SIDEKICK: Linear Correlation Clustering with Supervised Background Knowledge." In Similarity Search and Applications. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32047-8_20.

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Munro, J. Ian. "On the Competitiveness of Linear Search." In Algorithms - ESA 2000. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-45253-2_31.

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Conference papers on the topic "Linear search"

1

Zarnecki, Aleksander Filip, Mikael Berggren, María Teresa Núñez Pardo de Vera, Bartłomiej Brudnowski, and Kamil Zembaczynski. "Search for Exotic Scalars at the International Linear Collider." In 42nd International Conference on High Energy Physics. Sissa Medialab, 2024. https://doi.org/10.22323/1.476.0080.

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Zhang, Gongbo, and Yijie Peng. "Solving Mixed Integer Linear Programs by Monte Carlo Tree Search." In 2024 Winter Simulation Conference (WSC). IEEE, 2024. https://doi.org/10.1109/wsc63780.2024.10838738.

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El Fiky, Ahmed S., Ahmed Younes, A. R. Abdulghany, Salah S. A. Obayya, and Salem F. Hegazy. "Enhanced Quantum Search via Partial Diffusion and Entanglement with Linear Optics." In 2025 42nd National Radio Science Conference (NRSC). IEEE, 2025. https://doi.org/10.1109/nrsc65659.2025.11018556.

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Gumelar, Agil Fuad, Tutun Juhana, and Usman Zakaria. "Optimizing Customer Experience Through Low Latency Search: A Delay Analysis of Heuristic and linear search Methods for E-Commerce Applications." In 2024 10th International Conference on Wireless and Telematics (ICWT). IEEE, 2024. http://dx.doi.org/10.1109/icwt62080.2024.10674742.

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Hossain, Md Emran, Syed Bayazid Hossain, Md Sha Alam Tutul, and Shamsun Nahar. "Optimized Search Functionality with Linear Search Algorithm." In International Conference on Emerging Trends in Engineering and Advanced Science. AIJR Publisher, 2022. http://dx.doi.org/10.21467/proceedings.123.6.

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Linear search is the essential search algorithm used in fact structures. If is likewise called sequential search. Linear search used to discover a specific detail in an array. It is today no longer obligatory to display an array in any order (Ascending or Descending) as in the case of binary search. Linear search initiates advanced with the support of using sequentially scanning the influences within the array and if the detail has been found, if will display the unique detail and the index value of that detail in that array. In this paper we contemporary a unique searching algorithm of modifi

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Francis, Alwin, and Rajesh Ramachandran. "Modulo Ten Search- An Alternative to Linear Search." In 2011 International Conference on Process Automation, Control and Computing (PACC). IEEE, 2011. http://dx.doi.org/10.1109/pacc.2011.5979034.

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Spampinato, Daniele G., Upasana Sridhar, and Tze Meng Low. "Linear algebraic depth-first search." In the 6th ACM SIGPLAN International Workshop. ACM Press, 2019. http://dx.doi.org/10.1145/3315454.3329962.

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Jacob, Asha Elza, Nikhil Ashodariya, and Aakash Dhongade. "Hybrid search algorithm: Combined linear and binary search algorithm." In 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS). IEEE, 2017. http://dx.doi.org/10.1109/icecds.2017.8389704.

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Kong, Taeyong, Taeri Kim, Jinsung Jeon, et al. "Linear, or Non-Linear, That is the Question!" In WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining. ACM, 2022. http://dx.doi.org/10.1145/3488560.3498501.

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Jones, Colin N., and Jan M. Maciejowski. "Reverse Search for Parametric Linear Programming." In Proceedings of the 45th IEEE Conference on Decision and Control. IEEE, 2006. http://dx.doi.org/10.1109/cdc.2006.377799.

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Reports on the topic "Linear search"

1

Ghosh, Subir. Influential Nonegligible Parameters under the Search Linear Model. Defense Technical Information Center, 1986. http://dx.doi.org/10.21236/ada170079.

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Ghosh, Subir. Influential Nonnegligible Parameters Under the Search Linear Model. Defense Technical Information Center, 1986. http://dx.doi.org/10.21236/ada172007.

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Hough, P. D. Stable computation of search directions for near-degenerate linear programming problems. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/477537.

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Lewis, Robert Michael, Virginia Joanne Torczon, and Tamara Gibson Kolda. A generating set direct search augmented Lagrangian algorithm for optimization with a combination of general and linear constraints. Office of Scientific and Technical Information (OSTI), 2006. http://dx.doi.org/10.2172/893121.

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Chen, Z., S. E. Grasby, C. Deblonde, and X. Liu. AI-enabled remote sensing data interpretation for geothermal resource evaluation as applied to the Mount Meager geothermal prospective area. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/330008.

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The objective of this study is to search for features and indicators from the identified geothermal resource sweet spot in the south Mount Meager area that are applicable to other volcanic complexes in the Garibaldi Volcanic Belt. A Landsat 8 multi-spectral band dataset, for a total of 57 images ranging from visible through infrared to thermal infrared frequency channels and covering different years and seasons, were selected. Specific features that are indicative of high geothermal heat flux, fractured permeable zones, and groundwater circulation, the three key elements in exploring for geoth

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Koch, J. A. Imaging crystal/spectral line search. Office of Scientific and Technical Information (OSTI), 1998. http://dx.doi.org/10.2172/670066.

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Lewis, Robert Michael, ), Joshua D. Griffin, and Tamara Gibson Kolda. Asynchronous parallel generating set search for linearly-constrained optimization. Office of Scientific and Technical Information (OSTI), 2006. http://dx.doi.org/10.2172/891372.

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Kolda, Tamara G., Joshua Griffin, and Robert Michael Lewis. Asynchronous parallel generating set search for linearly-constrained optimization. Office of Scientific and Technical Information (OSTI), 2007. http://dx.doi.org/10.2172/1139970.

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Alonso-Robisco, Andrés, José Manuel Carbó, and José Manuel Carbó. Machine Learning methods in climate finance: a systematic review. Banco de España, 2023. http://dx.doi.org/10.53479/29594.

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Preventing the materialization of climate change is one of the main challenges of our time. The involvement of the financial sector is a fundamental pillar in this task, which has led to the emergence of a new field in the literature, climate finance. In turn, the use of Machine Learning (ML) as a tool to analyze climate finance is on the rise, due to the need to use big data to collect new climate-related information and model complex non-linear relationships. Considering the proliferation of articles in this field, and the potential for the use of ML, we propose a review of the academic lite

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Lewis, Robert Michael, Virginia Joanne Torczon, and Tamara Gibson Kolda. Stationarity results for generating set search for linearly constrained optimization. Office of Scientific and Technical Information (OSTI), 2003. http://dx.doi.org/10.2172/918255.

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