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Recent advances in metaheuristic algorithms: Does the Makara dragon exist?

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Abstract

Metaheuristic algorithms (MHs) have a long history that can be traced back to genetic algorithms and evolutionary computing in the 1950s. Since February 2008, with the birth of the Firefly algorithm, MHs started to receive attention from researchers around the globe. Variants and new species of MH algorithms have bloomed like sprouts after rain. However, the necessity for creating more new species of such algorithms is questionable. It can be observed that these algorithms are fundamentally made up of several widely used core components. By explaining these components, the underlying design for a collection of the so-called modern MH optimisation algorithms is revealed. In this paper, the core components in some of the more popular MH algorithms are reviewed, thereby debunking the myths of their novelty, and perhaps dampening claims that something really ‘new’ is invented simply by branding an MH search method with the name of another living creature. Counterintuitive experimentations have shown that by taking snapshots, anyone can show some improvements of an MH over another in some situation. Mixing certain components up indeed adds advantage over the original MH. The same goes to extending MH with slight functional modification. This work also serves as a general guideline and a reference for any algorithm architect who wants to create a new MH algorithm in the future.

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Notes

  1. http://cryptidz.wikia.com/wiki/Makara.

Abbreviations

ABC:

Artificial bee colony algorithm

ACO:

Ant colony optimization

AIS:

Artificial immune system algorithm

BFO:

Bacterial foraging algorithm

CS:

Cuckoo search algorithm

DE:

Differential evolution

FF:

Firefly algorithm

FPA:

Flower pollination algorithm

GA:

Genetic algorithm

GSA:

Gravitational search algorithm

GSS:

Golden section search

HJ:

Hooke Jeeves algorithm

HS:

Harmony search algorithm

IWD:

Intelligent water drops

LS:

Local search algorithm

MO:

Monkey optimization

MS:

Memetic search algorithm

OGRs:

Optimal Golomb rulers

QEA:

Quantum evolutionary algorithm

RFD:

River formation dynamics

SA:

Simulated annealing

SFLA:

Shuffled frog feaping algorithm

SOA:

Seeker optimization algorithm

TS:

Tree search algorithm

TSA:

Tabu search algorithm

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Acknowledgments

The authors are thankful for the financial supports by the Macao Science and Technology Development Fund under the EAE project (No.072/2009/A3), and MYRG2015-00128-FST, by the University of Macau and the Macau SAR government.

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Authors and Affiliations

  1. Department of Computer and Information Science, University of Macau, Macau SAR, China

    Simon Fong, Xi Wang & Qiwen Xu

  2. School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, 2052, Australia

    Raymond Wong

  3. Department of Computer Science, Lakehead University, Thunder Bay, Canada

    Jinan Fiaidhi & Sabah Mohammed

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Correspondence to Simon Fong.

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Fong, S., Wang, X., Xu, Q. et al. Recent advances in metaheuristic algorithms: Does the Makara dragon exist?. J Supercomput 72, 3764–3786 (2016). https://doi.org/10.1007/s11227-015-1592-8

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