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Principles and Practical Applications of the Optimal Values Management and Programming

Year 2016, Volume: 11 Issue: 3, 249 - 254, 30.09.2016

Abstract

In
this paper presented are the methods for solving optimization problems, when
there is a need to find the optimal value. This value may be minimum or maximum
range. For example: the required profit and expenses of a company or
institution, transport & costs minimization, computer network management,
economic management of financial requirements. Also, given is an adequate
method to optimize the function (objective function). The simplex method, Pivot
method, and another approximation method, are the model that can help solving
the question of the max and min problem. Here, presented are the program codes
and the same implemented into C ++ and codes MATLAB. By applying these methods
of optimization, we can have a direct approach and chance to minimize or
maximize the objective function: which is the key point in creating certain
optimum value. An optimization method has a practical use; this practical use is
demonstrated through certain examples. 

References

  • Bazaraa MS, Jarvis JJ, Sherali HD, (2004) Linear programming and network ows, Wiley-Interscience,.
  • Benson S, More JJ, (2001) A limited memory variable metric method for bound constrained minimization. Preprint MCS-P909-0901, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois.
  • Ben-Tal, Nemirovski A, (2002) Robust optimization methodology and applications, Math. Program. Ser. B 92, 453-480.
  • Bradley PS, Mangasarian OL, (1998) Feature selection via concave minimization and support vector machines. In Proceedings of the Twenty Fifth International Conference on Machine Learning (ICML),
  • Danzig GB, (1960) Inductive proof of the simplex method, Tech. report, RAND Corporation,.
  • Friedman JH, Hastie T, Tibshirani R, (2010) Regularization paths for generalized linear models via coordinate descent. Journal of Statistical Software, 33, 22.
  • Kall P, Wallace SW, (1994) Stochastic programming, John Wiley and Sons,.
  • Lang S, (1987) Linear Algebra, Springer-Verlag,.
  • Marsden JE, Tromba A, (2003) Vector calculus, 5 Ed., WH Freeman.
  • Papadimitriou CH, Steiglitz K, (1998) Combinatorial optimization: Algorithms and complexity, Dover Press,.
  • Saul I. Gass. Linear Programming: Methods and Applications: Fifth Edition (Dover Books on Computer Science), 2003.
Year 2016, Volume: 11 Issue: 3, 249 - 254, 30.09.2016

Abstract

References

  • Bazaraa MS, Jarvis JJ, Sherali HD, (2004) Linear programming and network ows, Wiley-Interscience,.
  • Benson S, More JJ, (2001) A limited memory variable metric method for bound constrained minimization. Preprint MCS-P909-0901, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois.
  • Ben-Tal, Nemirovski A, (2002) Robust optimization methodology and applications, Math. Program. Ser. B 92, 453-480.
  • Bradley PS, Mangasarian OL, (1998) Feature selection via concave minimization and support vector machines. In Proceedings of the Twenty Fifth International Conference on Machine Learning (ICML),
  • Danzig GB, (1960) Inductive proof of the simplex method, Tech. report, RAND Corporation,.
  • Friedman JH, Hastie T, Tibshirani R, (2010) Regularization paths for generalized linear models via coordinate descent. Journal of Statistical Software, 33, 22.
  • Kall P, Wallace SW, (1994) Stochastic programming, John Wiley and Sons,.
  • Lang S, (1987) Linear Algebra, Springer-Verlag,.
  • Marsden JE, Tromba A, (2003) Vector calculus, 5 Ed., WH Freeman.
  • Papadimitriou CH, Steiglitz K, (1998) Combinatorial optimization: Algorithms and complexity, Dover Press,.
  • Saul I. Gass. Linear Programming: Methods and Applications: Fifth Edition (Dover Books on Computer Science), 2003.
There are 11 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Nderim Zeqiri This is me

Publication Date September 30, 2016
Acceptance Date September 26, 2018
Published in Issue Year 2016 Volume: 11 Issue: 3

Cite

APA Zeqiri, N. (2016). Principles and Practical Applications of the Optimal Values Management and Programming. Journal of International Environmental Application and Science, 11(3), 249-254.
AMA Zeqiri N. Principles and Practical Applications of the Optimal Values Management and Programming. J. Int. Environmental Application & Science. September 2016;11(3):249-254.
Chicago Zeqiri, Nderim. “Principles and Practical Applications of the Optimal Values Management and Programming”. Journal of International Environmental Application and Science 11, no. 3 (September 2016): 249-54.
EndNote Zeqiri N (September 1, 2016) Principles and Practical Applications of the Optimal Values Management and Programming. Journal of International Environmental Application and Science 11 3 249–254.
IEEE N. Zeqiri, “Principles and Practical Applications of the Optimal Values Management and Programming”, J. Int. Environmental Application & Science, vol. 11, no. 3, pp. 249–254, 2016.
ISNAD Zeqiri, Nderim. “Principles and Practical Applications of the Optimal Values Management and Programming”. Journal of International Environmental Application and Science 11/3 (September 2016), 249-254.
JAMA Zeqiri N. Principles and Practical Applications of the Optimal Values Management and Programming. J. Int. Environmental Application & Science. 2016;11:249–254.
MLA Zeqiri, Nderim. “Principles and Practical Applications of the Optimal Values Management and Programming”. Journal of International Environmental Application and Science, vol. 11, no. 3, 2016, pp. 249-54.
Vancouver Zeqiri N. Principles and Practical Applications of the Optimal Values Management and Programming. J. Int. Environmental Application & Science. 2016;11(3):249-54.

“Journal of International Environmental Application and Science”