LINEAR PROGRAMMING FOR DATABASE ENVIRONMENT

Akira Kawaguchi, Jose Alfredo Perez

Abstract

Solving large-scale optimization problems requires an integration of data-analysis and data-manipulation capabilities. Nevertheless, little attempt has been made to facilitate general linear programming solvers for database environments. Dozens of sophisticated tools and software libraries that implement linear programming model can be found. But, there is no database-embedded linear programming tool seamlessly and transparently utilized for database processing. The focus of this study is to fill out this kind of technical gap of data analysis and data manipulation, in the event of solving large-scale linear programming problems for the applications built on the database environment. Specifically, this paper studies the representation of the linear programming model in relational structures and the computational method to solve the linear programming problems. Foundations for and preliminary experimental results of this study are presented.

References

  1. Alexander, S. (1998). Theory of Linear and Integer Programming. John Wiley & Sons, New York, NY.
  2. Dantzig, G. B. (1963). Linear Programming and Extensions. Princeton University Press, Princeton, N.J.
  3. Gulutzan, P. (2007). MySQL 5.0 New Features: Stored Procedures. MySQL AB, http://www.mysql.com.
  4. Gulutzan, P. and Pelzer, T. (1999). SQL-99 Complete, Really. CMP Books.
  5. Hillier, F. S. and Lieberman, G. J. (2001). Introduction to Operations Research. McGraw-Hill, 8th edition.
  6. Karmarkar, N. K. (1984). A new polynomial-time algorithm for linear programming and extensions. Combinatorica, 4:373-395.
  7. Morgan, S. S. (1976). A comparison of simplex method algorithms. Master's thesis, University of Florida.
  8. Optimization Technology Center, N. U. and Laboratory, A. N. (2007). The linear programming frequently asked questions.
  9. Organization, T. N. (2007). The netlib repository at utk and ornl.
  10. Richard, B. D. (1991). Introduction To Linear Programming: Applications and Extensions. Marcel Dekker, New York, NY.
  11. Saad, Y. and van der Vorst, H. (2000). Iterative solution of linear systems in the 20-th century. JCAM.
  12. Shamir, R. (1987). The efficiency of the simplex method: a survey. Manage. Sci., 33(3):301-334.
  13. Thomas H. Cormen, Charles E. Leiserson, R. L. R. and Stein, C. (2001). Introduction to Algorithms, Chapter29: Linear Programming. MIT Press and McGrawHill, 2nd edition.
  14. Walsh, G. R. (1985). An Introduction to Linear Programming. John Wiley & Sons, New York, NY.
  15. Wang, X. (99). From simplex methods to interior-point methods: A brief survey on linear programming algorithms.
  16. William H. Press, Saul A. Teukolsky, W. T. V. and Flannery, B. P. (2002). Numerical Recipes in C++: The Art of Scientific Computing. Cambridge University.
  17. Winston, W. L. (1994). Operations Research, Applications and Algorithms. Duxbury Press.
Download


Paper Citation


in Harvard Style

Kawaguchi A. and Alfredo Perez J. (2007). LINEAR PROGRAMMING FOR DATABASE ENVIRONMENT . In Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-972-8865-82-5, pages 186-191. DOI: 10.5220/0001652701860191


in Bibtex Style

@conference{icinco07,
author={Akira Kawaguchi and Jose Alfredo Perez},
title={LINEAR PROGRAMMING FOR DATABASE ENVIRONMENT},
booktitle={Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2007},
pages={186-191},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001652701860191},
isbn={978-972-8865-82-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - LINEAR PROGRAMMING FOR DATABASE ENVIRONMENT
SN - 978-972-8865-82-5
AU - Kawaguchi A.
AU - Alfredo Perez J.
PY - 2007
SP - 186
EP - 191
DO - 10.5220/0001652701860191