Initial Version of State Transition Algorithm

TL;DR

The paper introduces the State Transition Algorithm (STA), a new optimization method based on state and transition concepts, demonstrating promising performance on benchmark problems.

Contribution

It presents a novel optimization algorithm that simplifies classical and intelligent methods using state transition concepts and introduces specific operators for continuous and discrete problems.

Findings

STA performs well on benchmark functions

The algorithm has strong search capabilities

It simplifies understanding of optimization processes

Abstract

In terms of the concepts of state and state transition, a new algorithm-State Transition Algorithm (STA) is proposed in order to probe into classical and intelligent optimization algorithms. On the basis of state and state transition, it becomes much simpler and easier to understand. As for continuous function optimization problems, three special operators named rotation, translation and expansion are presented. While for discrete function optimization problems, an operator called general elementary transformation is introduced. Finally, with 4 common benchmark continuous functions and a discrete problem used to test the performance of STA, the experiment shows that STA is a promising algorithm due to its good search capability.