Self-Organizing Migrating Algorithm

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F16%3A86100471" target="_blank" >RIV/61989100:27240/16:86100471 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-28161-2" target="_blank" >http://dx.doi.org/10.1007/978-3-319-28161-2</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-28161-2" target="_blank" >10.1007/978-3-319-28161-2</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Self-Organizing Migrating Algorithm

Popis výsledku v původním jazyce

Swarm-based algorithms have become one of the foremost researched and applied heuristics in the field of evolutionary computation within the past decade. One of the new and novel approaches is that of the self-organizing migrating algorithm (SOMA). Initially developed and published in 2001 by Prof. Ivan Zelinka, SOMA has been actively researched by a select group of researchers over the past decade and a half. SOMA is conceptualized on a predator/prey relationship, where the sampling of the search space is conducted on a multidimensional facet, with the dimension selection conducted pre-sampling, using a randomly generated PRT vector. Two unique aspects of SOMA, which differentiate it from other swarm-based algorithms, are the creation and application of the PRT vector, and the path length, which specifi es the distance and sampling required within a particular dimension. Over the past few years, SOMA has been modified to solve combinatorial optimization problems. This discrete variant so-called discrete self-organizing migrating algorithm (DSOMA) has been proven to be robust and efficient. With its ever-expanding applications and utilization, it was thought beneficial and timely to produce a collated work of all the active applications of SOMA, which shows its current state of the art. To this effect, we have reached out and have obtained original research topics in SOMA and its application from a very diverse group of academics and researchers. This provides a rich source of material and ideas for both students and researchers.

Název v anglickém jazyce

Self-Organizing Migrating Algorithm

Popis výsledku anglicky

Swarm-based algorithms have become one of the foremost researched and applied heuristics in the field of evolutionary computation within the past decade. One of the new and novel approaches is that of the self-organizing migrating algorithm (SOMA). Initially developed and published in 2001 by Prof. Ivan Zelinka, SOMA has been actively researched by a select group of researchers over the past decade and a half. SOMA is conceptualized on a predator/prey relationship, where the sampling of the search space is conducted on a multidimensional facet, with the dimension selection conducted pre-sampling, using a randomly generated PRT vector. Two unique aspects of SOMA, which differentiate it from other swarm-based algorithms, are the creation and application of the PRT vector, and the path length, which specifi es the distance and sampling required within a particular dimension. Over the past few years, SOMA has been modified to solve combinatorial optimization problems. This discrete variant so-called discrete self-organizing migrating algorithm (DSOMA) has been proven to be robust and efficient. With its ever-expanding applications and utilization, it was thought beneficial and timely to produce a collated work of all the active applications of SOMA, which shows its current state of the art. To this effect, we have reached out and have obtained original research topics in SOMA and its application from a very diverse group of academics and researchers. This provides a rich source of material and ideas for both students and researchers.

Druh

B - Odborná kniha

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GA15-06700S" target="_blank" >GA15-06700S: Nekonvenční řízení komplexních systémů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

ISBN

978-3-319-28159-9

Počet stran knihy

289

Název nakladatele

Springer International Publishing

Místo vydání

US

Kód UT WoS knihy

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