International Journal of Nonlinear Analysis and Applications

Goals programming multiple linear regression model for optimal estimation of electrical engineering staff according to load Demand

Document Type : Research Paper

Authors

1 Department of Statistics, Administration and Economic College, Karbala University, Iraq.

2 College of computer science and information technology - University of Al-Qadisiyah - Iraq.

3 Faculty of Technical Engineering/Islamic University-Iraq.

Abstract

The linear multiple regression model is one of the prediction models whose parametric estimations could be achieved in different methods. Ordinary Least Square error (OLS) is most popular in this field of application. Although it could accurately achieve the estimation task, it fails in processing the multiple objective models. From the other side of view, the load demand for electrical energy continuously rises around the world. The governments always tackle the increase in electrical load demanding by establishing more electrical power plants and more power distribution directories. Future prediction for several electrical engineers to manage and provide technical supports for these plants and directories becomes, nowadays, urgent. This paper addresses the estimating drawback of OLS by employing the Goals Programming (GP) in the field of parametric estimation. The validity of the proposed method was applied to estimating the required number of electrical engineers, in the next coming years, as the electrical load considerably increases. Thereby, the GP was used, in this work, to determine the best linear representation for a set of data. The obtained results proved that the (GP) method is more flexible and efficient in dealing with such subject area especially in the case of multiple objective models.

Keywords

[1] M. H. Ahmad and et al, “Comparing Least-Squares and Goal Programming Estimates of Linear Regression
Parameters,” MATEMATICA, vol. 21, no. 2, (2005) 101–112.
[2] A. Charne and W. Cooper, “Management Models and Industrial Application of Linear Programming,” Manage.
Sci., vol. 4, no. 1, (1957).
[3] A. Charne and W. Cooper, “Goal Programming and Multiple Objectives Optimizations.,” Eur. J. Oper. Res.,
vol. 1, (1977) 39–54.
[4] L. AL.Degelae, ”Building the workforce planning model in the General Establishment for Electricity Distribution
of Baghdad,” PhD thesis, Mustansiriya University, (1997).[5] J. Ignazio, Goal Programming and Extensions, 2nd ed. Lexington Books, (1976).
[6] Y. Ijiri, “Management Goals and Accounting for Control,” Stud. Math. Manag. Econ., vol. 3, (1965).
[7] S. Kathem, “Comparisons between parameter estimations of linear regression model using OLS and programming
goals,” J. of Administration and Econ. Al Muthana Univ., (2009).
[8] E. Tu, “A Comparison of Three Linear Programming Models for Computing Least Absolute Values Estimates,”
J.OF Math .and Stat, vol. 34, (2005) 95–102.
[9] D. A. Wolfe, ”Nonparametrics: Statistical Methods Based on Ranks and Its Impact on the Field of Non-parametric
Statistics,” Sel. Work. E. L. Lehmann, (2012) 1101–1110.
International Journal of Nonlinear Analysis and Applications
Volume 12, Special Issue
December 2021
Pages 123-132
  • Receive Date: 21 October 2020
  • Revise Date: 12 January 2021
  • Accept Date: 10 February 2021