Penguins Huddling Optimisation

In our everyday life, people deal with many optimisation problems, some of which trivial and some more complex. These problems have been frequently addressed using multi-agent, population-based approaches. One of the main sources of inspiration for techniques applicable to complex search space and o...

Full description

Bibliographic Details
Main Author: Mohammad Majid al-Rifaie
Format: Article in Journal/Newspaper
Language:unknown
Subjects:
Online Access:http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijats.2014040101
id ftrepec:oai:RePEc:igg:jats00:v:6:y:2014:i:2:p:1-29
record_format openpolar
spelling ftrepec:oai:RePEc:igg:jats00:v:6:y:2014:i:2:p:1-29 2024-04-14T08:02:12+00:00 Penguins Huddling Optimisation Mohammad Majid al-Rifaie http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijats.2014040101 unknown http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijats.2014040101 article ftrepec 2024-03-19T10:29:39Z In our everyday life, people deal with many optimisation problems, some of which trivial and some more complex. These problems have been frequently addressed using multi-agent, population-based approaches. One of the main sources of inspiration for techniques applicable to complex search space and optimisation problems is nature. This paper proposes a new metaheuristic – Penguin Huddling Optimisation or PHO – whose inspiration is beckoned from the huddling behaviour of emperor penguins in Antarctica. The simplicity of the algorithm, which is the implementation of one such paradigm for continuous optimisation, facilitates the analysis of its behaviour and the derivation of the optimal value for its single adjustable parameter in the update equation. A series of experimental trials confirms the promising performance of the optimiser over a set of benchmarks, as well as its competitiveness when compared against few other well-known population based algorithms. Article in Journal/Newspaper Antarc* Antarctica Emperor penguins RePEc (Research Papers in Economics)
institution Open Polar
collection RePEc (Research Papers in Economics)
op_collection_id ftrepec
language unknown
description In our everyday life, people deal with many optimisation problems, some of which trivial and some more complex. These problems have been frequently addressed using multi-agent, population-based approaches. One of the main sources of inspiration for techniques applicable to complex search space and optimisation problems is nature. This paper proposes a new metaheuristic – Penguin Huddling Optimisation or PHO – whose inspiration is beckoned from the huddling behaviour of emperor penguins in Antarctica. The simplicity of the algorithm, which is the implementation of one such paradigm for continuous optimisation, facilitates the analysis of its behaviour and the derivation of the optimal value for its single adjustable parameter in the update equation. A series of experimental trials confirms the promising performance of the optimiser over a set of benchmarks, as well as its competitiveness when compared against few other well-known population based algorithms.
format Article in Journal/Newspaper
author Mohammad Majid al-Rifaie
spellingShingle Mohammad Majid al-Rifaie
Penguins Huddling Optimisation
author_facet Mohammad Majid al-Rifaie
author_sort Mohammad Majid al-Rifaie
title Penguins Huddling Optimisation
title_short Penguins Huddling Optimisation
title_full Penguins Huddling Optimisation
title_fullStr Penguins Huddling Optimisation
title_full_unstemmed Penguins Huddling Optimisation
title_sort penguins huddling optimisation
url http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijats.2014040101
genre Antarc*
Antarctica
Emperor penguins
genre_facet Antarc*
Antarctica
Emperor penguins
op_relation http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijats.2014040101
_version_ 1796313320255389696