Evolutionary strategy based on simulated annealing algorithm to solve the system of nonlinear equations
Chengjuan Zhu · Journal of Hefei University of Technology · 2008
Traditional algorithms such as gradient descent and Newton's method are used to solve the system of nonlinear equations but some problems exist,for instance,convergence and performance characteristics highly sensitive to the initial guess and low efficiency.In allusion to the above-mentioned problems,this paper presents a parallel evolutionary strategy based on simulated annealing algorithm for solving the system of nonlinear equations.Taking the Simulated Annealing algorithm as a genetic operator to actualize combination of the local searching ability of Simulated Annealing and global searching ability of modified evolution strategies can efficiently overcome the problems of high sensitivity to initial guess and low efficiency.The numerical computation results indicate that the algorithm of high convergence and high accuracy offers an effective way to solve the system of nonlinear equations.