Investigating the Efficiency of Evolutionary Algorithms in Optimization Problems

Introduction:

In the field of computer science, optimization problems are ubiquitous and arise in various domains such as engineering, finance, and logistics. The goal is to find the best solution among a set of possible alternatives, typically with constraints. Traditional optimization techniques, such as mathematical programming, have been extensively studied and applied. However, these methods often struggle with complex real-world problems due to their reliance on mathematical models and assumptions. In recent years, evolutionary algorithms (EAs) have gained significant attention for their ability to address optimization problems more efficiently. This article aims to investigate the efficiency of evolutionary algorithms in optimization problems, exploring their advantages, limitations, and potential future developments.