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Soft Computing

, Volume 22, Issue 12, pp 3857–3878 | Cite as

A new metaheuristic algorithm: car tracking optimization algorithm

  • Jian Chen
  • Hui Cai
  • Wei Wang
Foundations
  • 567 Downloads

Abstract

Over the last decade, several metaheuristic algorithms have emerged to solve numerical function optimization problems. Since the performance of these algorithms presents a suboptimal behavior, a large number of studies have been carried out to find new and better algorithms. Therefore, this paper proposes a new metaheuristic algorithm, namely the car tracking optimization algorithm; it is inspired by observing the programming methods of other metaheuristic algorithms. And the proposed algorithm has been tested over 55 benchmark functions, and the results have been compared with firefly algorithm (FA), cuckoo searching algorithm (CS), and vortex search algorithm (VS). The results indicate that the performance of the proposed algorithm surpasses FA, CS, and VS algorithm.

Keywords

Metaheuristic Function optimization Firefly algorithm Cuckoo searching algorithm Vortex search algorithm 

Notes

Compliance with ethical standards

Conflict of interest

The authors declared that they have no conflicts of interest to this work.

Ethical approval

This article does not contain any studies with human participants performed by any of the authors.

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.College of Mechanical and Electrical EngineeringChina Jiliang UniversityHangzhouChina

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