Nature Inspired Computational Technique for the Numerical Solution of Nonlinear Singular Boundary Value Problems Arising in Physiology

Table 1

Parameter settings of algorithms.

GA		ASA		IPA
Parameters	Settings	Parameters	Settings	Parameters	Settings
Population size	240	Start point	Optimal values from GA	Start point	Optimal values from GA
Chromosome size	30	Maximum iterations	400	Maximum iterations	1000
Selection function	Stochastic uniform	Maximum function evaluations	150000	Maximum function evaluations	150000
Mutation function	Adaptive feasible	Function tolerance	1𝑒−18	Function tolerance	1𝑒−18
Crossover function	Heuristic	Nonlinear constraint tolerance	1𝑒−18	Nonlinear constraint tolerance	1𝑒−18
Hybridization	PS/IPA	SQP tolerance	1𝑒−18	SQP tolerance	1𝑒−18
		X tolerance	1𝑒−18	X tolerance	1𝑒−18
Number of generations	2000			Hessian	BFGS
Function tolerance	1𝑒−18			Derivative type	Central differences
Nonlinear constraint tolerance	1𝑒−18
Bounds	−15, +15