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This useful framework has been utilized for obtaining approximate solutions to many nonlinear problems [9].
There are many nonlinear problems arising in engineering areas needing more than one constraint.
It is well known that many nonlinear problems can be reduced to the search for solutions of various differential equations.
It is well known that many nonlinear problems can be reduced to the search for solutions of monotone variational inequalities.
Mathematical modeling of many nonlinear problems in science and engineering leads to the qualitative study of nonlinear differential equations with initial and boundary conditions.
Since then, essentiality was applied in many nonlinear problems such as KKM points, vector equilibrium problems and Nash equilibrium problems (see [22 27]).
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We note here that many nonlinear differential problems require the search of positive, meaningful, solutions.
Piecewise linear networks (PLNs) are attractive because they can be trained quickly and provide good performance in many nonlinear approximation problems.
The topic of HAM has been rapidly growing in recent years and successfully applied to many nonlinear boundary problems such as nonlinear oscillators with discontinuities [9, 10, 11, 12].
Many important nonlinear problems of mathematics reduce to nonlinear functional equations such as nonlinear integral equations and boundary value problems for nonlinear ordinary or partial differential equations which can be translated in terms of a fixed point equation T x = x for a given nonlinear mapping T on a Banach space or a metric space.
The study of such types of problems is motivated by an increasing interest to study the behavior and approximation of the solution sets for many important nonlinear problems arising in mechanics, physics, optimization and control, nonlinear programming, economics, finance, regional structural, transportation, elasticity, engineering, and various applied sciences in a general and unified framework.
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