Relevant bibliographies by topics / Quadratic programmin

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  1. Journal articles

Academic literature on the topic 'Quadratic programmin'

Author: Grafiati
Published: 1 April 2023

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Journal articles on the topic "Quadratic programmin"

1

Majeed, Amir Sabir, and Fadhil Salman Abed. "A Proposed Method to Solve Quadratic Fractional Programming Problem by Converting to Double Linear Programming." Journal of Zankoy Sulaimani - Part A 19, no. 1 (2016): 239–49. http://dx.doi.org/10.17656/jzs.10602.

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2

Yamashita, Hiroshi, and Hiroshige Dan. "GLOBAL CONVERGENCE OF A TRUST REGION SEQUENTIAL QUADRATIC PROGRAMMING METHOD." Journal of the Operations Research Society of Japan 48, no. 1 (2005): 41–56. http://dx.doi.org/10.15807/jorsj.48.41.

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3

Turlach, Berwin A., and Stephen J. Wright. "Quadratic programming." Wiley Interdisciplinary Reviews: Computational Statistics 7, no. 2 (2015): 153–59. http://dx.doi.org/10.1002/wics.1344.

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4

Serna-Diaz, Raquel, Raimundo Santos Leite, and Paulo J. S. Silva. "A mixed quadratic programming model for a robust support vector machine." Selecciones Matemáticas 8, no. 1 (2021): 27–36. http://dx.doi.org/10.17268/sel.mat.2021.01.03.

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5

Sulaiman, Nejmaddin A., and Maher A. Nawkhass. "Using Standard Division to Solve Multi- Objective Quadratic Fractional Programming Problems." Journal of Zankoy Sulaimani - Part A 18, no. 3 (2016): 157–64. http://dx.doi.org/10.17656/jzs.10544.

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6

Sulaiman, Najmaddin A., and Basiya K. Abulrahim. "Arithmetic Average Transformation Technique to Solve Multi-Objective Quadratic Programming Problem." Journal of Zankoy Sulaimani - Part A 15, no. 1 (2012): 57–69. http://dx.doi.org/10.17656/jzs.10233.

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7

Wilson, G. "Quadratic programming analogs." IEEE Transactions on Circuits and Systems 33, no. 9 (1986): 907–11. http://dx.doi.org/10.1109/tcs.1986.1086021.

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8

Boggs, Paul T., and Jon W. Tolle. "Sequential Quadratic Programming." Acta Numerica 4 (January 1995): 1–51. http://dx.doi.org/10.1017/s0962492900002518.

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Abstract:
Since its popularization in the late 1970s, Sequential Quadratic Programming (SQP) has arguably become the most successful method for solving nonlinearly constrained optimization problems. As with most optimization methods, SQP is not a single algorithm, but rather a conceptual method from which numerous specific algorithms have evolved. Backed by a solid theoretical and computational foundation, both commercial and public-domain SQP algorithms have been developed and used to solve a remarkably large set of important practical problems. Recently large-scale versions have been devised and tested with promising results.
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9

Beck, Amir. "Quadratic Matrix Programming." SIAM Journal on Optimization 17, no. 4 (2007): 1224–38. http://dx.doi.org/10.1137/05064816x.

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10

Koyuncu, Nursel. "Computation of Parameters Using Genetic Algorithm and Sequential Quadratic Programming in Sampling." International Journal of Computer Theory and Engineering 7, no. 5 (2015): 394–97. http://dx.doi.org/10.7763/ijcte.2015.v7.992.

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