Generation of Two-Layer Monotonic Functions

TL;DR

This paper presents a genetic algorithm-based method for generating two-layer monotonic functions, demonstrating the feasibility of constructing such functions for up to six variables and expanding the understanding of monotonic function implementation.

Contribution

Introduces a novel genetic algorithm approach for creating two-layer monotonic functions of a specific class, applicable to functions with up to six variables.

Findings

Successfully generated two-layer monotonic functions for up to six variables.

Proved the existence of solutions for constructing monotonic functions from two monotone functions.

Demonstrated the effectiveness of the genetic algorithm in this context.

Abstract

The problem of implementing a class of functions with particular conditions by using monotonic multilayer functions is considered. A genetic algorithm is used to create monotonic functions of a certain class, and these are implemented with two-layer monotonic functions. The existence of a solution to the given problem suggests that from two monotone functions, a monotonic function with the same dimensions can be created. A new algorithm based on the genetic algorithm is proposed, which easily implemented two-layer monotonic functions of a specific class for up to six variables.