# Optimization Is Teleology Optimization = Teleology. This is not an inclusion. This is an equal. First of all, if you accept teleology then the purpose optimizes everything. So it obviously induces an optimization. Conversely: An optimization problem consists of two things. 1. The objective function 2. Constraints An optimization is literally just maximizing or minimizing the objective function with given constraints. For example, you can maximize your sleep (the objective function) while you don't miss out your schedules (constraints). So as you can see, min/maximizing the objective function works as a purpose. And that's especially teleological if solving an optimization problem is not to optimize something, but to explain and to induce the results. A typical example is the principle of least time. It means that a ray always follows the path which minimizes the traveling time. It is clearly an optimization problem. And it is not about "how to optimize", but about "why the results are true". So it induces teleology. Similarily, the principle of least action is an optimization problem that is to explain the results. Another example is economics. Surprisingly, economics uses Lagrangian too (!). Since economics assumes that people are rational, people optimize everything. As a result, if you solve any optimization problem in economics, the solution will be the market equilibrium. How magical! So in this case, everything happens to make market be efficient. The last example is linguistic economy. It means that people simplify languages as long as it doesn't hurt clarity. It is an optimization problem in which the objective function is linguistic complexity and the constraint is clarity. And it induces teleology. Every linguistic event happens to simplify the language. OK. But aren't there still optimization problems that are about how to optimize? In fact, the difference between those two types is just points of view. For example, you can think the maximizing sleep problem objectively. You can explain your actions as following the biological purpose. Regardless of points of view, the optimization problems are mathematically the same.