Derivation of Upper Bounds on Optimization Time of Population-Based Evolutionary Algorithm on a Function with Fitness Plateaus Using Elitism Levels Traverse Mechanism

TL;DR

This paper develops a method to analyze the optimization time of population-based evolutionary algorithms on functions with fitness plateaus, providing upper bounds and population distribution insights.

Contribution

It introduces a novel analytical tool for deriving asymptotic upper bounds on EA optimization time on plateau functions using elitism levels traverse.

Findings

Derived asymptotic upper bounds for Royal Roads problem

Approximated limiting distribution of a population subset

Provided insights into population dynamics on fitness plateaus

Abstract

In this article a tool for the analysis of population-based EAs is used to derive asymptotic upper bounds on the optimization time of the algorithm solving Royal Roads problem, a test function with plateaus of fitness. In addition to this, limiting distribution of a certain subset of the population is approximated.