2022•Unpublished venueRequires access

Design of hybrid genetic algorithm based on ant colony algorithm

Yibo Zhao, Baozhu Li

Abstract

Genetic algorithm as one of the most classical algorithms, its application scope covers various fields, but with the development of The Times, the basic genetic algorithm has been unable to meet many practical problems in today’s society, so the improvement of genetic algorithm is particularly important. This paper integrates ant colony algorithm and genetic algorithm to design a hybrid genetic algorithm. Firstly, it introduces the basic principle and operation process of genetic algorithm, and then describes the principle and process of ant colony algorithm. Finally, it designs a hybrid genetic algorithm, which has the characteristics of strong global search ability and fast convergence.

About this research paper

What this paper is about

Why it matters

OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Key concepts: Population-based incremental learning, Algorithm, Cultural algorithm, Genetic algorithm, Meta-optimization, Computer science, Ant colony optimization algorithms, Convergence (economics)