摘要：We present a stochastic numerical method based on memetic heuristic computing for the approximate numerical solution of a class of nonlinear singular boundary value problems arising in physiology. The solution of the nonlinear problem is represented by the linear combination of some log sigmoid basis functions. A fitness function representing the mean square error consisting of unknown adaptable parameters (chromosome) is formulated. The minimization of the fitness function is carried out by employing Genetic algorithm (GA), Interior Point algorithm (IPA), and hybrid scheme combining GA and IPA (GA-IPA) for the optimal values of the chromosome. The efficiency of the presented method is testified by solving two examples from physiology. The results prove that the proposed heuristic method provides the approximate numerical solution comparable to some of the existing conventional numerical solutions.
关键词：Nonlinear singular boundary value problem (BVP);Genetic algorithm (GA);Interior point algorithm (IPA);Evolutionary algorithms (EA’s);finite difference method;B-spline method;Oxygen diffusion problem;nonlinear heat conduction model
