A Comparative Study of State Transition Algorithm with Harmony Search and Artificial Bee Colony

TL;DR

This paper compares three recent nature-inspired optimization algorithms—state transition, harmony search, and artificial bee colony—using benchmark problems to evaluate their performance and applicability.

Contribution

It provides a detailed comparison of the core mechanisms and performance of these three algorithms on standard benchmark problems.

Findings

Performance varies across different problem types

State transition algorithm shows competitive results

Harmony search and artificial bee colony excel in specific scenarios

Abstract

We focus on a comparative study of three recently developed nature-inspired optimization algorithms, including state transition algorithm, harmony search and artificial bee colony. Their core mechanisms are introduced and their similarities and differences are described. Then, a suit of 27 well-known benchmark problems are used to investigate the performance of these algorithms and finally we discuss their general applicability with respect to the structure of optimization problems.