Metaheuristics in nature-inspired algorithms

Michael A. Lones

doi:10.1145/2598394.2609841

Metaheuristics in nature-inspired algorithms

Michael A. Lones^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

59 Citations (Scopus)

Abstract

To many people, the terms nature-inspired algorithm and metaheuristic are interchangeable. However, this contemporary usage is not consistent with the original meaning of the term metaheuristic, which referred to something closer to a design pattern than to an algorithm. In this paper, it is argued that the loss of focus on true metaheuristics is a primary reason behind the explosion of "novel" nature-inspired algorithms and the issues this has raised. To address this, this paper attempts to explicitly identify the metaheuristics that are used in conventional optimisation algorithms, discuss whether more recent nature-inspired algorithms have delivered any fundamental new knowledge to the field of metaheuristics, and suggest some guidelines for future research in this field.

Original language	English
Title of host publication	GECCO 2014 - Companion Publication of the 2014 Genetic and Evolutionary Computation Conference
Publisher	Association for Computing Machinery
Pages	1419-1422
Number of pages	4
ISBN (Print)	9781450328814
DOIs	https://doi.org/10.1145/2598394.2609841
Publication status	Published - 1 Jan 2014
Event	16th Genetic and Evolutionary Computation Conference 2014 - Vancouver, Canada Duration: 12 Jul 2014 → 16 Jul 2014

Conference

Conference	16th Genetic and Evolutionary Computation Conference 2014
Abbreviated title	GECCO 2014
Country/Territory	Canada
City	Vancouver
Period	12/07/14 → 16/07/14

Keywords

Design patterns
Metaheuristics

ASJC Scopus subject areas

Computational Theory and Mathematics
Applied Mathematics

Access to Document

10.1145/2598394.2609841

Cite this

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title = "Metaheuristics in nature-inspired algorithms",

abstract = "To many people, the terms nature-inspired algorithm and metaheuristic are interchangeable. However, this contemporary usage is not consistent with the original meaning of the term metaheuristic, which referred to something closer to a design pattern than to an algorithm. In this paper, it is argued that the loss of focus on true metaheuristics is a primary reason behind the explosion of {"}novel{"} nature-inspired algorithms and the issues this has raised. To address this, this paper attempts to explicitly identify the metaheuristics that are used in conventional optimisation algorithms, discuss whether more recent nature-inspired algorithms have delivered any fundamental new knowledge to the field of metaheuristics, and suggest some guidelines for future research in this field.",

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AU - Lones, Michael A.

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N2 - To many people, the terms nature-inspired algorithm and metaheuristic are interchangeable. However, this contemporary usage is not consistent with the original meaning of the term metaheuristic, which referred to something closer to a design pattern than to an algorithm. In this paper, it is argued that the loss of focus on true metaheuristics is a primary reason behind the explosion of "novel" nature-inspired algorithms and the issues this has raised. To address this, this paper attempts to explicitly identify the metaheuristics that are used in conventional optimisation algorithms, discuss whether more recent nature-inspired algorithms have delivered any fundamental new knowledge to the field of metaheuristics, and suggest some guidelines for future research in this field.

AB - To many people, the terms nature-inspired algorithm and metaheuristic are interchangeable. However, this contemporary usage is not consistent with the original meaning of the term metaheuristic, which referred to something closer to a design pattern than to an algorithm. In this paper, it is argued that the loss of focus on true metaheuristics is a primary reason behind the explosion of "novel" nature-inspired algorithms and the issues this has raised. To address this, this paper attempts to explicitly identify the metaheuristics that are used in conventional optimisation algorithms, discuss whether more recent nature-inspired algorithms have delivered any fundamental new knowledge to the field of metaheuristics, and suggest some guidelines for future research in this field.

KW - Design patterns

KW - Metaheuristics

U2 - 10.1145/2598394.2609841

DO - 10.1145/2598394.2609841

M3 - Conference contribution

AN - SCOPUS:84905661425

SN - 9781450328814

SP - 1419

EP - 1422

BT - GECCO 2014 - Companion Publication of the 2014 Genetic and Evolutionary Computation Conference

PB - Association for Computing Machinery

T2 - 16th Genetic and Evolutionary Computation Conference 2014

Y2 - 12 July 2014 through 16 July 2014

ER -

Metaheuristics in nature-inspired algorithms

Abstract

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this