Unfortunately, such grand, unified, one-size-fits-all solutions almost never work — because they radically underestimate the complexity of real world problems.
The failure of old economic ideas, and the intellectual bankruptcy of neoliberalism in the face of real world problems, leaves those who held them exposed and defensive.
There are a lot of real world problems which exist in infinite dimension spaces.
Nowadays, most of real world problems are complex and hence they cannot be solved by exact methods.
However, in mathematical modeling of real world problems, we will encounter some other inconveniences such as complexity and uncertainty or vagueness.
According to our experience, useful methods of real world problems often need to be used to solve several problems arising in different spaces.
Let us now recall some basic definitions of fractional derivative [27] and see how such derivatives appear in the mathematical modeling of real world problems.
Many scholars [37, 38] think that uncertainty or vagueness often appear in mathematical modeling of real world problems, thus it is necessary to take vagueness into consideration.
The mathematical modeling of real world problems, such as earthquake, traffic flow, fluid flow, signal processing, and viscoelastic problems, results in FPDEs.
The methods operate based on mathematical models while in most cases these models are drastically simplified imagine of real world problems.
Real parameter constrained problems are an important class of optimization problems that are encountered frequently in a variety of real world problems.
