title: Memetic computing through bio-inspired heuristics integration with sequential quadratic programming for nonlinear systems arising in different physical models.
abstract: BACKGROUND
  In this study, bio-inspired computing is exploited for solving system of nonlinear equations using variants of genetic algorithms (GAs) as a tool for global search method hybrid with sequential quadratic programming (SQP) for efficient local search. The fitness function is constructed by defining the error function for systems of nonlinear equations in mean square sense. The design parameters of mathematical models are trained by exploiting the competency of GAs and refinement are carried out by viable SQP algorithm.
  
  
  RESULTS
  Twelve versions of the memetic approach GA-SQP are designed by taking a different set of reproduction routines in the optimization process. Performance of proposed variants is evaluated on six numerical problems comprising of system of nonlinear equations arising in the interval arithmetic benchmark model, kinematics, neurophysiology, combustion and chemical equilibrium. Comparative studies of the proposed results in terms of accuracy, convergence and complexity are performed with the help of statistical performance indices to establish the worth of the schemes.
  
  
  CONCLUSIONS
  Accuracy and convergence of the memetic computing GA-SQP is found better in each case of the simulation study and effectiveness of the scheme is further established through results of statistics based on different performance indices for accuracy and complexity.
authors.affiliation: Department of Electrical Engineering, COMSATS Institute of Information Technology, Attock Campus, Attock, Pakistan.
authors.forename: Muhammad Asif Zahoor
authors.initials: MA
authors.lastname: Raja
authors.affiliation: Department of Economics, Federal Urdu University of Arts Science and Technology, Islamabad, Pakistan.
authors.forename: Adiqa Kausar
authors.initials: AK
authors.lastname: Kiani
authors.affiliation: Department of Mathematics, Preston University, Kohat, Islamabad Campus, Islamabad, Pakistan.
authors.forename: Azam
authors.initials: A
authors.lastname: Shehzad
authors.affiliation: Department of Computer and Information Sciences, Pakistan Institute of Engineering and Applied Sciences (PIEAS), Nilore, Islamabad, 45650 Pakistan.
authors.forename: Aneela
authors.initials: A
authors.lastname: Zameer
keywords: Genetic algorithms; Hybrid computing; Nonlinear equations; Nonlinear systems; Sequential quadratic programming